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Wang K, Cunha GM, Hasenstab K, Henderson WC, Middleton MS, Cole SA, Umans JG, Ali T, Hsiao A, Sirlin CB. Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data. AJR Am J Roentgenol 2023; 221:620-631. [PMID: 37466189 DOI: 10.2214/ajr.23.29607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.
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Affiliation(s)
- Kang Wang
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Radiology, Stanford University, 500 Pasteur Dr, Palo Alto, CA 94304
| | | | - Kyle Hasenstab
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA
| | - Walter C Henderson
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Michael S Middleton
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX
| | - Jason G Umans
- MedStar Health Research Institute, Field Studies Division, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Tauqeer Ali
- Department of Biostatistics and Epidemiology, Center for American Indian Health Research, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Albert Hsiao
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
| | - Claude B Sirlin
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
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Fowler KJ, Venkatesh SK, Obuchowski N, Middleton MS, Chen J, Pepin K, Magnuson J, Brown KJ, Batakis D, Henderson WC, Shankar SS, Kamphaus TN, Pasek A, Calle RA, Sanyal AJ, Loomba R, Ehman R, Samir AE, Sirlin CB, Sherlock SP. Repeatability of MRI Biomarkers in Nonalcoholic Fatty Liver Disease: The NIMBLE Consortium. Radiology 2023; 309:e231092. [PMID: 37815451 PMCID: PMC10625902 DOI: 10.1148/radiol.231092] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/30/2023] [Accepted: 08/29/2023] [Indexed: 10/11/2023]
Abstract
Background There is a need for reliable noninvasive methods for diagnosing and monitoring nonalcoholic fatty liver disease (NAFLD). Thus, the multidisciplinary Non-invasive Biomarkers of Metabolic Liver disease (NIMBLE) consortium was formed to identify and advance the regulatory qualification of NAFLD imaging biomarkers. Purpose To determine the different-day same-scanner repeatability coefficient of liver MRI biomarkers in patients with NAFLD at risk for steatohepatitis. Materials and Methods NIMBLE 1.2 is a prospective, observational, single-center short-term cross-sectional study (October 2021 to June 2022) in adults with NAFLD across a spectrum of low, intermediate, and high likelihood of advanced fibrosis as determined according to the fibrosis based on four factors (FIB-4) index. Participants underwent up to seven MRI examinations across two visits less than or equal to 7 days apart. Standardized imaging protocols were implemented with six MRI scanners from three vendors at both 1.5 T and 3 T, with central analysis of the data performed by an independent reading center (University of California, San Diego). Trained analysts, who were blinded to clinical data, measured the MRI proton density fat fraction (PDFF), liver stiffness at MR elastography (MRE), and visceral adipose tissue (VAT) for each participant. Point estimates and CIs were calculated using χ2 distribution and statistical modeling for pooled repeatability measures. Results A total of 17 participants (mean age, 58 years ± 8.5 [SD]; 10 female) were included, of which seven (41.2%), six (35.3%), and four (23.5%) participants had a low, intermediate, or high likelihood of advanced fibrosis, respectively. The different-day same-scanner mean measurements were 13%-14% for PDFF, 6.6 L for VAT, and 3.15 kPa for two-dimensional MRE stiffness. The different-day same-scanner repeatability coefficients were 0.22 L (95% CI: 0.17, 0.29) for VAT, 0.75 kPa (95% CI: 0.6, 0.99) for MRE stiffness, 1.19% (95% CI: 0.96, 1.61) for MRI PDFF using magnitude reconstruction, 1.56% (95% CI: 1.26, 2.07) for MRI PDFF using complex reconstruction, and 19.7% (95% CI: 15.8, 26.2) for three-dimensional MRE shear modulus. Conclusion This preliminary study suggests that thresholds of 1.2%-1.6%, 0.22 L, and 0.75 kPa for MRI PDFF, VAT, and MRE, respectively, should be used to discern measurement error from real change in patients with NAFLD. ClinicalTrials.gov registration no. NCT05081427 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kozaka and Matsui in this issue.
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Affiliation(s)
| | | | - Nancy Obuchowski
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Michael S. Middleton
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Jun Chen
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Kay Pepin
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Jessica Magnuson
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Kathy J. Brown
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Danielle Batakis
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Walter C. Henderson
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Sudha S. Shankar
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Tania N. Kamphaus
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Alex Pasek
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Roberto A. Calle
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Arun J. Sanyal
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Rohit Loomba
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Richard Ehman
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
| | - Anthony E. Samir
- From the Liver Imaging Group (K.J.F., M.S.M., D.B., W.C.H., C.B.S.)
and Department of Hepatology (R.L.), University of California–San Diego,
6206 Lakewood St, San Diego, CA 92122; Department of Radiology, Mayo Clinic,
Rochester, Minn (S.K.V., J.C., K.P., J.M., K.J.B., R.E.); Department of
Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (N.O.); Pfizer
Research and Development, Pfizer, Inc, Sacramento, Calif (S.S.S.); Foundation
for the National Institutes of Health, North Bethesda, Md (T.N.K., A.P.);
Regeneron Pharmaceuticals, Inc, Tarrytown, NY (R.A.C.); Department of
Gastroenterology, Virginia Commonwealth University, Richmond, Va (A.J.S.);
Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.E.S.);
and Department of Imaging Alliances, Pfizer, Inc, New York, NY (S.P.S.)
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3
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Malki GJ, Goyal NP, Ugalde-Nicalo P, Chun LF, Zhang J, Ding Z, Wei Y, Knott C, Batakis D, Henderson W, Sirlin CB, Middleton MS, Schwimmer JB. Association of Hepatic Steatosis with Adipose and Muscle Mass and Distribution in Children. Metab Syndr Relat Disord 2023; 21:222-230. [PMID: 37083405 PMCID: PMC10181799 DOI: 10.1089/met.2023.0002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
Background: Pediatric studies have shown associations between hepatic steatosis and total body fat, visceral fat, and lean mass. However, these associations have not been assessed simultaneously, leaving their relative importance unknown. Objective: To evaluate associations between hepatic steatosis and total-body adiposity, visceral adiposity, and lean mass in children. Method: In children at risk for fatty liver, hepatic steatosis, adipose, and lean mass were estimated with magnetic resonance imaging and dual-energy X-ray absorptiometry. Results: Two hundred twenty-seven children with mean age 12.1 years had mean percent body fat of 38.9% and mean liver fat of 8.4%. Liver fat was positively associated with total-body adiposity, visceral adiposity, and lean mass (P < 0.001), and negatively associated with lean mass percentage (P < 0.001). After weight adjustment, liver fat was only positively associated with measures of central adiposity (P < 0.001). Visceral adiposity also had the strongest association with liver fat (P < 0.001). Conclusions: In children, hepatic steatosis is more strongly associated with visceral adiposity than total adiposity, and the association of lean mass is not independent of weight or fat mass. These relationships may help guide the choice of future interventions to target hepatic steatosis.
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Affiliation(s)
- Ghattas J Malki
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Nidhi P Goyal
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California, USA
- Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | | | - Lauren F Chun
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Jasen Zhang
- Division of Biostatistics and Bioinformatics, University of California San Diego Herbert Wertheim School of Public Health and Human Longevity Science, San Diego, California, USA
| | - Ziyi Ding
- Division of Biostatistics and Bioinformatics, University of California San Diego Herbert Wertheim School of Public Health and Human Longevity Science, San Diego, California, USA
| | - Yingjia Wei
- Division of Biostatistics and Bioinformatics, University of California San Diego Herbert Wertheim School of Public Health and Human Longevity Science, San Diego, California, USA
| | - Cynthia Knott
- Altman Clinical and Translational Research Institute, School of Medicine, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Danielle Batakis
- Liver Imaging Group, Department of Radiology, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Walter Henderson
- Liver Imaging Group, Department of Radiology, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California San Diego School of Medicine, La Jolla, California, USA
| | - Jeffrey B Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California, USA
- Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
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4
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Nedrud MA, Chaudhry M, Middleton MS, Moylan CA, Lerebours R, Luo S, Farjat A, Guy C, Loomba R, Abdelmalek MF, Sirlin CB, Bashir MR. MRI Quantification of Placebo Effect in Nonalcoholic Steatohepatitis Clinical Trials. Radiology 2023; 306:e220743. [PMID: 36318027 PMCID: PMC9968769 DOI: 10.1148/radiol.220743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 07/21/2022] [Accepted: 09/09/2022] [Indexed: 02/22/2023]
Abstract
Background Several early-phase clinical trials for the treatment of nonalcoholic steatohepatitis (NASH) use liver fat content as measured with the MRI-derived proton density fat fraction (PDFF) for a primary outcome. These trials have shown relative reductions in liver fat content with placebo treatment alone, a phenomenon termed "the placebo effect." This phenomenon confounds the results and limits generalizability to future trials. Purpose To quantify the effect of placebo treatment on change in the absolute PDFF value and to identify variables associated with this observed change. Materials and Methods This is a secondary analysis of prospectively collected data from seven early phase clinical trials that included participants with a diagnosis of NASH based on MRI and/or liver biopsy who received placebo treatment. The primary outcome was a greater than or equal to 30% relative reduction in PDFF after placebo treatment. Normalization of PDFF, relative change in alanine aminotransferase (ALT) level, and normalization of ALT level were also examined. An exploratory linear mixed-effects model was used to estimate an overall change in absolute PDFF and to explore parameters associated with this response. Results A total of 187 participants (median age, 52 years [IQR, 43-60 years]; 114 women) who received placebo treatment were evaluated. A greater than or equal to 30% relative reduction in baseline PDFF was seen in 20% of participants after 12 weeks of placebo treatment (10 of 49), 9% of participants after 16 weeks (two of 22), and 28% of participants after 24 weeks (34 of 122). A repeated-measures linear mixed-effects model estimated a decrease of 2.3 units (median relative reduction of 13%) in absolute PDFF values after 24 weeks of placebo treatment (95% CI: 3.2, 1.4; P < .001). Conclusion In this analysis of 187 participants, a clinically relevant decrease in PDFF was observed with placebo treatment. Based on the study model, assuming an absolute PDFF decrease of approximately 3 units (upper limit of 95% CI) to account for this "placebo effect" in sample size calculations for future clinical trials is suggested. Clinical trial registration nos. NCT01066364, NCT01766713, NCT01963845, NCT02443116, NCT02546609, NCT02316717, and NCT02442687 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Yoon in this issue.
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Affiliation(s)
| | | | - Michael S. Middleton
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Cynthia A. Moylan
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Reginald Lerebours
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Sheng Luo
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Alfredo Farjat
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Cynthia Guy
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Rohit Loomba
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Manal F. Abdelmalek
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Claude B. Sirlin
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
| | - Mustafa R. Bashir
- From the Department of Radiology (M.A.N., M.R.B.), Division of
Gastroenterology, Department of Medicine (C.A.M., M.R.B.), Department of
Biostatistics & Bioinformatics (R. Lerebours, S.L., A.F.), Department of
Pathology (C.G.), and Center for Advanced Magnetic Resonance Development
(M.R.B.), Duke University Medical Center, Department of Radiology, Box 3808,
Durham, NC 27710; Rutgers University Hospital, School of Medicine, Newark, NJ
(M.C.); Liver Imaging Group, Department of Radiology (M.S.M., C.B.S.), and
Division of Gastroenterology, Department of Medicine (R. Loomba), University of
California at San Diego School of Medicine, San Diego, Calif; Department of
Medicine, Durham Veterans Affairs Medical Center, Durham, NC (C.A.M.); and
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minn
(M.F.A.)
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5
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Shen W, Middleton MS, Cunha GM, Delgado TI, Wolfson T, Gamst A, Fowler KJ, Alazraki A, Trout AT, Ohliger MA, Shah SN, Bashir MR, Kleiner DE, Loomba R, Neuschwander-Tetri BA, Sanyal AJ, Zhou J, Sirlin CB, Lavine JE. Changes in abdominal adipose tissue depots assessed by MRI correlate with hepatic histologic improvement in non-alcoholic steatohepatitis. J Hepatol 2023; 78:238-246. [PMID: 36368598 PMCID: PMC9852022 DOI: 10.1016/j.jhep.2022.10.027] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 10/10/2022] [Accepted: 10/12/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND & AIMS Non-alcoholic steatohepatitis (NASH) is prevalent in adults with obesity and can progress to cirrhosis. In a secondary analysis of prospectively acquired data from the multicenter, randomized, placebo-controlled FLINT trial, we investigated the relationship between reduction in adipose tissue compartment volumes and hepatic histologic improvement. METHODS Adult participants in the FLINT trial with paired liver biopsies and abdominal MRI exams at baseline and end-of-treatment (72 weeks) were included (n = 76). Adipose tissue compartment volumes were obtained using MRI. RESULTS Treatment and placebo groups did not differ in baseline adipose tissue volumes, or in change in adipose tissue volumes longitudinally (p = 0.107 to 0.745). Deep subcutaneous adipose tissue (dSAT) and visceral adipose tissue volume reductions were associated with histologic improvement in NASH (i.e., NAS [non-alcoholic fatty liver disease activity score] reductions of ≥2 points, at least 1 point from lobular inflammation and hepatocellular ballooning, and no worsening of fibrosis) (p = 0.031, and 0.030, respectively). In a stepwise logistic regression procedure, which included demographics, treatment group, baseline histology, baseline and changes in adipose tissue volumes, MRI hepatic proton density fat fraction (PDFF), and serum aminotransferases as potential predictors, reductions in dSAT and PDFF were associated with histologic improvement in NASH (regression coefficient = -2.001 and -0.083, p = 0.044 and 0.033, respectively). CONCLUSIONS In adults with NASH in the FLINT trial, those with greater longitudinal reductions in dSAT and potentially visceral adipose tissue volumes showed greater hepatic histologic improvements, independent of reductions in hepatic PDFF. CLINICAL TRIAL NUMBER NCT01265498. IMPACT AND IMPLICATIONS Although central obesity has been identified as a risk factor for obesity-related disorders including insulin resistance and cardiovascular disease, the role of central obesity in non-alcoholic steatohepatitis (NASH) warrants further clarification. Our results highlight that a reduction in central obesity, specifically deep subcutaneous adipose tissue and visceral adipose tissue, may be related to histologic improvement in NASH. The findings from this analysis should increase awareness of the importance of lifestyle intervention in NASH for clinical researchers and clinicians. Future studies and clinical practice may design interventions that assess the reduction of deep subcutaneous adipose tissue and visceral adipose tissue as outcome measures, rather than simply weight reduction.
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Affiliation(s)
- Wei Shen
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA;; Institute of Human Nutrition, College of Physicians & Surgeons, Columbia University Irving Medical Center; NY, USA;; Columbia Magnetic Resonance Research Center (CMRRC), Columbia University, USA.
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, CA, USA
| | | | - Timoteo I Delgado
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, CA, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center at UCSD, San Diego, CA, USA
| | - Anthony Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center at UCSD, San Diego, CA, USA;; Department of Mathematics, UCSD, San Diego, CA, USA
| | - Kathryn J Fowler
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, CA, USA
| | - Adina Alazraki
- Emory University School of Medicine, Department of Radiology and Imaging Sciences and Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Andrew T Trout
- Department of Radiology, Cincinnati Children's Hospital Medical Center and Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Michael A Ohliger
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Shetal N Shah
- Section of Abdominal Imaging and Nuclear Medicine Department, Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Mustafa R Bashir
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA;; Center for Advanced Magnetic Resonance Development, (CAMRD), Department of Radiology, Duke University Medical Center, Durham, NC, USA;; Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - David E Kleiner
- Laboratory of Pathology, National Cancer Institute, Bethesda, MD, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California-San Diego, La Jolla, CA, USA
| | | | | | - Jane Zhou
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, CA, USA
| | - Joel E Lavine
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA;; Institute of Human Nutrition, College of Physicians & Surgeons, Columbia University Irving Medical Center; NY, USA
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6
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Tang A, Dzyubak B, Yin M, Schlein A, Henderson WC, Hooker JC, Delgado TI, Middleton MS, Zheng L, Wolfson T, Gamst A, Loomba R, Ehman RL, Sirlin CB. MR elastography in nonalcoholic fatty liver disease: inter-center and inter-analysis-method measurement reproducibility and accuracy at 3T. Eur Radiol 2022; 32:2937-2948. [PMID: 34928415 PMCID: PMC9038857 DOI: 10.1007/s00330-021-08381-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 09/15/2021] [Accepted: 10/04/2021] [Indexed: 12/17/2022]
Abstract
OBJECTIVES To assess reproducibility and fibrosis classification accuracy of magnetic resonance elastography (MRE)-determined liver stiffness measured manually at two different centers, and by automated analysis software in adults with nonalcoholic fatty liver disease (NAFLD), using histopathology as a reference standard. METHODS This retrospective, cross-sectional study included 91 adults with NAFLD who underwent liver MRE and biopsy. MRE-determined liver stiffness was measured independently for this analysis by an image analyst at each of two centers using standardized manual analysis methodology, and separately by an automated analysis. Reproducibility was assessed pairwise by intraclass correlation coefficient (ICC) and Bland-Altman analysis. Diagnostic accuracy was assessed by receiver operating characteristic (ROC) analyses. RESULTS ICC of liver stiffness measurements was 0.95 (95% CI: 0.93, 0.97) between center 1 and center 2 analysts, 0.96 (95% CI: 0.94, 0.97) between the center 1 analyst and automated analysis, and 0.94 (95% CI: 0.91, 0.96) between the center 2 analyst and automated analysis. Mean bias and 95% limits of agreement were 0.06 ± 0.38 kPa between center 1 and center 2 analysts, 0.05 ± 0.32 kPa between the center 1 analyst and automated analysis, and 0.11 ± 0.41 kPa between the center 2 analyst and automated analysis. The area under the ROC curves for the center 1 analyst, center 2 analyst, and automated analysis were 0.834, 0.833, and 0.847 for distinguishing fibrosis stage 0 vs. ≥ 1, and 0.939, 0.947, and 0.940 for distinguishing fibrosis stage ≤ 2 vs. ≥ 3. CONCLUSION MRE-determined liver stiffness can be measured with high reproducibility and fibrosis classification accuracy at different centers and by an automated analysis. KEY POINTS • Reproducibility of MRE liver stiffness measurements in adults with nonalcoholic fatty liver disease is high between two experienced centers and between manual and automated analysis methods. • Analysts at two centers had similar high diagnostic accuracy for distinguishing dichotomized fibrosis stages. • Automated analysis provides similar diagnostic accuracy as manual analysis for advanced fibrosis.
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Affiliation(s)
- An Tang
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada
| | - Bogdan Dzyubak
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Alexandra Schlein
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Walter C Henderson
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Timoteo I Delgado
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Lin Zheng
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
- Department of Mathematics, University of California San Diego, San Diego, CA, USA
| | - Tanya Wolfson
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA
- Department of Mathematics, University of California San Diego, San Diego, CA, USA
| | - Anthony Gamst
- Department of Mathematics, University of California San Diego, San Diego, CA, USA
- Computational and Applied Statistics Laboratory (CASL), SDSC - University of California, San Diego, CA, USA
| | - Rohit Loomba
- Division of Gastroenterology, Hepatology, and Medicine, University of California San Diego, San Diego, California, USA
| | | | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
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7
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Qu Y, Middleton MS, Loomba R, Glaser KJ, Chen J, Hooker JC, Wolfson T, Covarrubias Y, Valasek MA, Fowler KJ, Zhang YN, Sy E, Gamst AC, Wang K, Mamidipalli A, Schwimmer JB, Song B, Reeder SB, Yin M, Ehman RL, Sirlin CB. Magnetic resonance elastography biomarkers for detection of histologic alterations in nonalcoholic fatty liver disease in the absence of fibrosis. Eur Radiol 2021; 31:8408-8419. [PMID: 33899143 PMCID: PMC8530863 DOI: 10.1007/s00330-021-07988-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 03/25/2021] [Accepted: 04/02/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To investigate associations between histology and hepatic mechanical properties measured using multiparametric magnetic resonance elastography (MRE) in adults with known or suspected nonalcoholic fatty liver disease (NAFLD) without histologic fibrosis. METHODS This was a retrospective analysis of 88 adults who underwent 3T MR exams including hepatic MRE and MR imaging to estimate proton density fat fraction (MRI-PDFF) within 180 days of liver biopsy. Associations between MRE mechanical properties (mean shear stiffness (|G*|) by 2D and 3D MRE, and storage modulus (G'), loss modulus (G″), wave attenuation (α), and damping ratio (ζ) by 3D MRE) and histologic, demographic and anthropometric data were assessed. RESULTS In univariate analyses, patients with lobular inflammation grade ≥ 2 had higher 2D |G*| and 3D G″ than those with grade ≤ 1 (p = 0.04). |G*| (both 2D and 3D), G', and G″ increased with age (rho = 0.25 to 0.31; p ≤ 0.03). In multivariable regression analyses, the association between inflammation grade ≥ 2 remained significant for 2D |G*| (p = 0.01) but not for 3D G″ (p = 0.06); age, sex, or BMI did not affect the MRE-inflammation relationship (p > 0.20). CONCLUSIONS 2D |G*| and 3D G″ were weakly associated with moderate or severe lobular inflammation in patients with known or suspected NAFLD without fibrosis. With further validation and refinement, these properties might become useful biomarkers of inflammation. Age adjustment may help MRE interpretation, at least in patients with early-stage disease. KEY POINTS • Moderate to severe lobular inflammation was associated with hepatic elevated shear stiffness and elevated loss modulus (p =0.04) in patients with known or suspected NAFLD without liver fibrosis; this suggests that with further technical refinement these MRE-assessed mechanical properties may permit detection of inflammation before the onset of fibrosis in NAFLD. • Increasing age is associated with higher hepatic shear stiffness, and storage and loss moduli (rho = 0.25 to 0.31; p ≤ 0.03); this suggests that age adjustment may help interpret MRE results, at least in patients with early-stage NAFLD.
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Affiliation(s)
- Yali Qu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California at San Diego, La Jolla, CA, USA
- Department of Family Medicine and Public Health, University of California at San Diego, La Jolla, CA, USA
| | - Kevin J Glaser
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Jun Chen
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, the San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA, USA
| | - Yesenia Covarrubias
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Mark A Valasek
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Kathryn J Fowler
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Yingzhen N Zhang
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Ethan Sy
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory, the San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA, USA
| | - Kang Wang
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Jeffrey B Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California at San Diego, La Jolla, CA, USA
- Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, CA, USA
| | - Bin Song
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Scott B Reeder
- Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin, Madison, WI, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA.
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8
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Hong CW, Cui JY, Batakis D, Xu Y, Wolfson T, Gamst AC, Schlein AN, Negrete LM, Middleton MS, Hamilton G, Loomba R, Schwimmer JB, Fowler KJ, Sirlin CB. Repeatability and accuracy of various region-of-interest sampling strategies for hepatic MRI proton density fat fraction quantification. Abdom Radiol (NY) 2021; 46:3105-3116. [PMID: 33609166 DOI: 10.1007/s00261-021-02965-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 01/13/2021] [Accepted: 01/16/2021] [Indexed: 12/19/2022]
Abstract
PURPOSE To evaluate repeatability of ROI-sampling strategies for quantifying hepatic proton density fat fraction (PDFF) and to assess error relative to the 9-ROI PDFF. METHODS This was a secondary analysis in subjects with known or suspected nonalcoholic fatty liver disease who underwent MRI for magnitude-based hepatic PDFF quantification. Each subject underwent three exams, each including three acquisitions (nine acquisitions total). An ROI was placed in each hepatic segment on the first acquisition of the first exam and propagated to other acquisitions. PDFF was calculated for each of 511 sampling strategies using every combination of 1, 2, …, all 9 ROIs. Intra- and inter-exam intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs) were estimated for each sampling strategy. Mean absolute error (MAE) was estimated relative to the 9-ROI PDFF. Strategies that sampled both lobes evenly ("balanced") were compared with those that did not ("unbalanced") using two-sample t tests. RESULTS The 29 enrolled subjects (23 male, mean age 24 years) had mean 9-ROI PDFF 11.8% (1.1-36.3%). With more ROIs, ICCs increased, RCs decreased, and MAE decreased. Of the 60 balanced strategies with 4 ROIs, all (100%) achieved inter- and intra-exam ICCs > 0.998, 55 (92%) achieved intra-exam RC < 1%, 50 (83%) achieved inter-exam RC < 1%, and all (100%) achieved MAE < 1%. Balanced sampling strategies had higher ICCs and lower RCs, and lower MAEs than unbalanced strategies in aggregate (p < 0.001 for comparisons between balanced vs. unbalanced strategies). CONCLUSION Repeatability improves and error diminishes with more ROIs. Balanced 4-ROI strategies provide high repeatability and low error.
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9
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Chun LF, Yu EL, Sawh MC, Bross C, Nichols J, Polgreen L, Knott C, Schlein A, Sirlin CB, Middleton MS, Kado DM, Schwimmer JB. Hepatic Steatosis is Negatively Associated with Bone Mineral Density in Children. J Pediatr 2021; 233:105-111.e3. [PMID: 33545191 PMCID: PMC8154638 DOI: 10.1016/j.jpeds.2021.01.064] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/12/2021] [Accepted: 01/27/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate the relationship between hepatic steatosis and bone mineral density (BMD) in children. In addition, to assess 25-hydroxyvitamin D levels in the relationship between hepatic steatosis and BMD. STUDY DESIGN A community-based sample of 235 children was assessed for hepatic steatosis, BMD, and serum 25-hydroxyvitamin D. Hepatic steatosis was measured by liver magnetic resonance imaging proton density fat fraction (MRI-PDFF). BMD was measured by whole-body dual-energy x-ray absorptiometry. RESULTS The mean age of the study population was 12.5 years (SD 2.5 years). Liver MRI-PDFF ranged from 1.1% to 40.1% with a mean of 9.3% (SD 8.5%). Across this broad spectrum of hepatic fat content, there was a significant negative relationship between liver MRI-PDFF and BMD z score (R = -0.421, P < .001). Across the states of sufficiency, insufficiency, and deficiency, there was a significant negative association between 25-hydroxyvitamin D and liver MRI-PDFF (P < .05); however, there was no significant association between vitamin D status and BMD z score (P = .94). Finally, children with clinically low BMD z scores were found to have higher alanine aminotransferase (P < .05) and gamma-glutamyl transferase (P < .05) levels compared with children with normal BMD z scores. CONCLUSIONS Across the full range of liver MRI-PDFF, there was a strong negative relationship between hepatic steatosis and BMD z score. Given the prevalence of nonalcoholic fatty liver disease and the critical importance of childhood bone mineralization in protecting against osteoporosis, clinicians should prioritize supporting bone development in children with nonalcoholic fatty liver disease.
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Affiliation(s)
- Lauren F. Chun
- Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, University of California San Diego School of Medicine, La Jolla, California
| | - Elizabeth L. Yu
- Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, University of California San Diego School of Medicine, La Jolla, California,Department of Gastroenterology, Rady Children’s Hospital, San Diego, California
| | - Mary Catherine Sawh
- Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, University of California San Diego School of Medicine, La Jolla, California,Department of Gastroenterology, Rady Children’s Hospital, San Diego, California
| | - Craig Bross
- Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, University of California San Diego School of Medicine, La Jolla, California
| | - Jeanne Nichols
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California,Graduate School of Public Health, San Diego State University, San Diego, California
| | - Lynda Polgreen
- Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California
| | - Cynthia Knott
- Altman Clinical and Translational Research Institute, School of Medicine, University of California San Diego School of Medicine, Ja Jolla, California
| | - Alexandra Schlein
- Liver Imaging Group, Department of Radiology, University of California San Diego School of Medicine, La Jolla, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego School of Medicine, La Jolla, California
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California San Diego School of Medicine, La Jolla, California
| | - Deborah M. Kado
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California,Department of Internal Medicine, University of California San Diego, La Jolla, California
| | - Jeffrey B. Schwimmer
- Department of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, University of California San Diego School of Medicine, La Jolla, California,Department of Gastroenterology, Rady Children’s Hospital, San Diego, California
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10
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Sawh MC, Wallace M, Shapiro E, Goyal NP, Newton KP, Yu EL, Bross C, Durelle J, Knott C, Gangoiti JA, Barshop BA, Gengatharan JM, Meurs N, Schlein A, Middleton MS, Sirlin CB, Metallo CM, Schwimmer JB. Dairy Fat Intake, Plasma Pentadecanoic Acid, and Plasma Iso-heptadecanoic Acid Are Inversely Associated With Liver Fat in Children. J Pediatr Gastroenterol Nutr 2021; 72:e90-e96. [PMID: 33399331 PMCID: PMC8842839 DOI: 10.1097/mpg.0000000000003040] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVES We sought to evaluate the relevance of pediatric dairy fat recommendations for children at risk for nonalcoholic fatty liver disease (NAFLD) by studying the association between dairy fat intake and the amount of liver fat. The effects of dairy fat may be mediated by odd chain fatty acids (OCFA), such as pentadecanoic acid (C15:0), and monomethyl branched chain fatty acids (BCFA), such as iso-heptadecanoic acid (iso-C17:0). Therefore, we also evaluated the association between plasma levels of OCFA and BCFA with the amount of liver fat. METHODS Observational, cross-sectional, community-based sample of 237 children ages 8 to 17. Dairy fat intake was assessed by 3 24-hour dietary recalls. Plasma fatty acids were measured by gas chromatography-mass spectrometry. Main outcome was hepatic steatosis measured by whole liver magnetic resonance imaging proton density fat fraction (MRI-PDFF). RESULTS Median dairy fat intake was 10.6 grams/day (range 0.0--44.5 g/day). Median liver MRI-PDFF was 4.5% (range 0.9%-45.1%). Dairy fat intake was inversely correlated with liver MRI-PDFF (r = -0.162; P = .012). In multivariable log linear regression, plasma C15:0 and iso-C17:0 were inverse predictors of liver MRI-PDFF (B = -0.247, P = 0.048; and B = -0.234, P = 0.009). CONCLUSIONS Dairy fat intake, plasma C15:0, and plasma iso-C17:0 were inversely correlated with hepatic steatosis in children. These hypothesis-generating findings should be tested through clinical trials to better inform dietary guidelines.
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Affiliation(s)
- Mary Catherine Sawh
- Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics; University of California San Diego; La Jolla, California
| | - Martina Wallace
- Department of Bioengineering, University of California, San Diego, La Jolla, California
| | - Emma Shapiro
- Boston University College of Health & Rehabilitation Sciences: Sargent College, Boston, Massachusetts
| | - Nidhi P. Goyal
- Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics; University of California San Diego; La Jolla, California
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Kimberly P. Newton
- Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics; University of California San Diego; La Jolla, California
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Elizabeth L. Yu
- Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics; University of California San Diego; La Jolla, California
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Craig Bross
- Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics; University of California San Diego; La Jolla, California
| | - Janis Durelle
- Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics; University of California San Diego; La Jolla, California
| | - Cynthia Knott
- Altman Clinical and Translational Research Institute, School of Medicine, University of California, San Diego, La Jolla
| | - Jon A. Gangoiti
- Division of Genetics, Biochemical Genetics and Metabolomics Laboratory, Department of Pediatrics; University of California San Diego; La Jolla, California
| | - Bruce A. Barshop
- Division of Genetics, Biochemical Genetics and Metabolomics Laboratory, Department of Pediatrics; University of California San Diego; La Jolla, California
| | - Jivani M. Gengatharan
- Department of Bioengineering, University of California, San Diego, La Jolla, California
| | - Noah Meurs
- Department of Bioengineering, University of California, San Diego, La Jolla, California
| | - Alexandra Schlein
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, California
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, California
| | - Christian M. Metallo
- Department of Bioengineering, University of California, San Diego, La Jolla, California
| | - Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics; University of California San Diego; La Jolla, California
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
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11
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Navaratna R, Zhao R, Colgan TJ, Hu HH, Bydder M, Yokoo T, Bashir MR, Middleton MS, Serai SD, Malyarenko D, Chenevert T, Smith M, Henderson W, Hamilton G, Shu Y, Sirlin CB, Tkach JA, Trout AT, Brittain JH, Hernando D, Reeder SB. Temperature-corrected proton density fat fraction estimation using chemical shift-encoded MRI in phantoms. Magn Reson Med 2021; 86:69-81. [PMID: 33565112 DOI: 10.1002/mrm.28669] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 12/07/2020] [Accepted: 12/08/2020] [Indexed: 12/20/2022]
Abstract
PURPOSE Chemical shift-encoded MRI (CSE-MRI) is well-established to quantify proton density fat fraction (PDFF) as a quantitative biomarker of hepatic steatosis. However, temperature is known to bias PDFF estimation in phantom studies. In this study, strategies were developed and evaluated to correct for the effects of temperature on PDFF estimation through simulations, temperature-controlled experiments, and a multi-center, multi-vendor phantom study. THEORY AND METHODS A technical solution that assumes and automatically estimates a uniform, global temperature throughout the phantom is proposed. Computer simulations modeled the effect of temperature on PDFF estimation using magnitude-, complex-, and hybrid-based CSE-MRI methods. Phantom experiments were performed to assess the temperature correction on PDFF estimation at controlled phantom temperatures. To assess the temperature correction method on a larger scale, the proposed method was applied to data acquired as part of a nine-site multi-vendor phantom study and compared to temperature-corrected PDFF estimation using an a priori guess for ambient room temperature. RESULTS Simulations and temperature-controlled experiments show that as temperature deviates further from the assumed temperature, PDFF bias increases. Using the proposed correction method and a reasonable a priori guess for ambient temperature, PDFF bias and variability were reduced using magnitude-based CSE-MRI, across MRI systems, field strengths, protocols, and varying phantom temperature. Complex and hybrid methods showed little PDFF bias and variability both before and after correction. CONCLUSION Correction for temperature reduces temperature-related PDFF bias and variability in phantoms across MRI vendors, sites, field strengths, and protocols for magnitude-based CSE-MRI, even without a priori information about the temperature.
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Affiliation(s)
- Ruvini Navaratna
- Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Ruiyang Zhao
- Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Timothy J Colgan
- Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Houchun Harry Hu
- Department of Radiology, Nationwide Children's Hospital, Columbus, Ohio, USA
| | - Mark Bydder
- Department of Radiological Sciences, University of California - Los Angeles, Los Angeles, California, USA
| | - Takeshi Yokoo
- Department of Radiology, University of Texas - Southwestern Medical Center, Dallas, Texas, USA
| | - Mustafa R Bashir
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.,Division of Hepatology, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA.,Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, North Carolina, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Suraj D Serai
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Dariya Malyarenko
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Thomas Chenevert
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Mark Smith
- Department of Radiology, Nationwide Children's Hospital, Columbus, Ohio, USA
| | - Walter Henderson
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Yunhong Shu
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Jean A Tkach
- Department of Radiology, Cincinnati Children's Hospital and Medical Center, Cincinnati, Ohio, USA
| | - Andrew T Trout
- Department of Radiology, Cincinnati Children's Hospital and Medical Center, Cincinnati, Ohio, USA.,Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | | | - Diego Hernando
- Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Medicine, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Emergency Medicine, University of Wisconsin - Madison, Madison, Wisconsin, USA
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12
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Hu HH, Yokoo T, Bashir MR, Sirlin CB, Hernando D, Malyarenko D, Chenevert TL, Smith MA, Serai SD, Middleton MS, Henderson WC, Hamilton G, Shaffer J, Shu Y, Tkach JA, Trout AT, Obuchowski N, Brittain JH, Jackson EF, Reeder SB. Linearity and Bias of Proton Density Fat Fraction as a Quantitative Imaging Biomarker: A Multicenter, Multiplatform, Multivendor Phantom Study. Radiology 2021; 298:640-651. [PMID: 33464181 DOI: 10.1148/radiol.2021202912] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background Proton density fat fraction (PDFF) estimated by using chemical shift-encoded (CSE) MRI is an accepted imaging biomarker of hepatic steatosis. This work aims to promote standardized use of CSE MRI to estimate PDFF. Purpose To assess the accuracy of CSE MRI methods for estimating PDFF by determining the linearity and range of bias observed in a phantom. Materials and Methods In this prospective study, a commercial phantom with 12 vials of known PDFF values were shipped across nine U.S. centers. The phantom underwent 160 independent MRI examinations on 27 1.5-T and 3.0-T systems from three vendors. Two three-dimensional CSE MRI protocols with minimal T1 bias were included: vendor and standardized. Each vendor's confounder-corrected complex or hybrid magnitude-complex based reconstruction algorithm was used to generate PDFF maps in both protocols. The Siemens reconstruction required a configuration change to correct for water-fat swaps in the phantom. The MRI PDFF values were compared with the known PDFF values by using linear regression with mixed-effects modeling. The 95% CIs were calculated for the regression slope (ie, proportional bias) and intercept (ie, constant bias) and compared with the null hypothesis (slope = 1, intercept = 0). Results Pooled regression slope for estimated PDFF values versus phantom-derived reference PDFF values was 0.97 (95% CI: 0.96, 0.98) in the biologically relevant 0%-47.5% PDFF range. The corresponding pooled intercept was -0.27% (95% CI: -0.50%, -0.05%). Across vendors, slope ranges were 0.86-1.02 (vendor protocols) and 0.97-1.0 (standardized protocol) at 1.5 T and 0.91-1.01 (vendor protocols) and 0.87-1.01 (standardized protocol) at 3.0 T. The intercept ranges (absolute PDFF percentage) were -0.65% to 0.18% (vendor protocols) and -0.69% to -0.17% (standardized protocol) at 1.5 T and -0.48% to 0.10% (vendor protocols) and -0.78% to -0.21% (standardized protocol) at 3.0 T. Conclusion Proton density fat fraction estimation derived from three-dimensional chemical shift-encoded MRI in a commercial phantom was accurate across vendors, imaging centers, and field strengths, with use of the vendors' product acquisition and reconstruction software. © RSNA, 2021 See also the editorial by Dyke in this issue.
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Affiliation(s)
- Houchun H Hu
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Takeshi Yokoo
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Mustafa R Bashir
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Claude B Sirlin
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Diego Hernando
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Dariya Malyarenko
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Thomas L Chenevert
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Mark A Smith
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Suraj D Serai
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Michael S Middleton
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Walter C Henderson
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Gavin Hamilton
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Jean Shaffer
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Yunhong Shu
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Jean A Tkach
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Andrew T Trout
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Nancy Obuchowski
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Jean H Brittain
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Edward F Jackson
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
| | - Scott B Reeder
- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
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- From the Department of Radiology, Nationwide Children's Hospital, 700 Children's Dr, Columbus, OH 43235 (H.H.H., M.A.S.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Radiology (M.R.B., J.S.), Department of Medicine, Division of Gastroenterology (M.R.B.), and Center for Advanced Magnetic Resonance Development (M.R.B., J.S.), Duke University Medical Center, Durham, NC; Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, Calif (C.B.S., M.S.M., W.C.H., G.H.); Departments of Radiology (D.H., J.H.B., S.B.R.), Medical Physics (D.H., E.F.J., S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, University of Michigan, Ann Arbor, Mich (D.M., T.L.C.); Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.D.S.); Department of Radiology, Mayo Clinic, Rochester, Minn (Y.S.); Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.A.T., A.T.T.); Department of Quantitative Health Science, Cleveland Clinic Foundation, Cleveland, Ohio (N.O.); and Calimetrix, LLC, Madison, Wis (J.H.B.)
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Loomba R, Neuschwander-Tetri BA, Sanyal A, Chalasani N, Diehl AM, Terrault N, Kowdley K, Dasarathy S, Kleiner D, Behling C, Lavine J, Van Natta M, Middleton M, Tonascia J, Sirlin C, Allende D, Dasarathy S, McCullough AJ, Penumatsa R, Dasarathy J, Lavine JE, Abdelmalek MF, Bashir M, Buie S, Diehl AM, Guy C, Kigongo C, Kopping M, Malik D, Piercy D, Chalasani N, Cummings OW, Gawrieh S, Ragozzino L, Sandrasegaran K, Vuppalanchi R, Brunt EM, Cattoor T, Carpenter D, Freebersyser J, King D, Lai J, Neuschwander‐Tetri BA, Siegner J, Stewart S, Torretta S, Wriston K, Gonzalez MC, Davila J, Jhaveri M, Kowdley KV, Mukhtar N, Ness E, Poitevin M, Quist B, Soo S, Ang B, Behling C, Bhatt A, Loomba R, Middleton MS, Sirlin C, Akhter MF, Bass NM, Brandman D, Gill R, Hameed B, Maher J, Terrault N, Ungermann A, Yeh M, Boyett S, Contos MJ, Kirwin S, Luketic VA, Puri P, Sanyal AJ, Schlosser J, Siddiqui MS, Yost‐Schomer L, Brunt EM, Fowler K, Kleiner DE, Doo EC, Hall S, Hoofnagle JH, Robuck PR, Sherker AH, Torrance R, Belt P, Clark JM, Dodge J, Donithan M, Isaacson M, Lazo M, Meinert J, Miriel L, Sharkey EP, Smith J, Smith M, Sternberg A, Tonascia J, Van Natta ML, Wagoner A, Wilson LA, Yamada G, Yates K, Covarrubias Y, Gamst A, Hamilton G, Henderson W, Hooker J, Lavine JE, Loomba R, Middleton MS, Schlein A, Schwimmer JB, Shen W, Sirlin C, Wolfson T. Multicenter Validation of Association Between Decline in MRI-PDFF and Histologic Response in NASH. Hepatology 2020; 72:1219-1229. [PMID: 31965579 PMCID: PMC8055244 DOI: 10.1002/hep.31121] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 12/23/2019] [Indexed: 02/05/2023]
Abstract
BACKGROUND AND AIMS Emerging data from a single-center study suggests that a 30% relative reduction in liver fat content as assessed by magnetic resonance imaging-proton density fat fraction (MRI-PDFF) from baseline may be associated with histologic improvement in nonalcoholic steatohepatitis (NASH). There are limited multicenter data comparing an active drug versus placebo on the association between the quantity of liver fat reduction assessed by MRI-PDFF and histologic response in NASH. This study aims to examine the association between 30% relative reduction in MRI-PDFF and histologic response in obeticholic acid (OCA) versus placebo-treated patients in the FLINT (farnesoid X receptor ligand obeticholic acid in NASH trial). APPROACH AND RESULTS This is a secondary analysis of the FLINT trial including 78 patients with MRI-PDFF measured before and after treatment along with paired liver histology assessment. Histologic response was defined as a 2-point improvement in nonalcoholic fatty liver disease activity score without worsening of fibrosis. OCA (25 mg orally once daily) was better than placebo in improving MRI-PDFF by an absolute difference of -3.4% (95% confidence interval [CI], -6.5 to -0.2%, P value = 0.04) and relative difference of -17% (95% CI, -34 to 0%, P value = 0.05). The optimal cutoff point for relative decline in MRI-PDFF for histologic response was 30% (using Youden's index). The rate of histologic response in those who achieved less than 30% decline in MRI-PDFF versus those who achieved a 30% or greater decline in MRI-PDFF (MRI-PDFF responders) relative to baseline was 19% versus 50%, respectively. Compared with MRI-PDFF nonresponders, MRI-PDFF responders demonstrated both a statistically and clinically significant higher odds 4.86 (95% CI, 1.4-12.8, P value < 0.009) of histologic response, including significant improvements in both steatosis and ballooning. CONCLUSION OCA was better than placebo in reducing liver fat. This multicenter trial provides data regarding the association between 30% decline in MRI-PDFF relative to baseline and histologic response in NASH.
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Affiliation(s)
- Rohit Loomba
- University of California San Diego, La Jolla, CA, USA
| | | | - Arun Sanyal
- Virginia Commonwealth University, Richmond, VA, USA
| | | | | | - Norah Terrault
- University of California San Francisco, San Francisco, CA USA
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Patel K, Harrison SA, Elkhashab M, Trotter JF, Herring R, Rojter SE, Kayali Z, Wong VWS, Greenbloom S, Jayakumar S, Shiffman ML, Freilich B, Lawitz EJ, Gane EJ, Harting E, Xu J, Billin AN, Chung C, Djedjos CS, Subramanian GM, Myers RP, Middleton MS, Rinella M, Noureddin M. Cilofexor, a Nonsteroidal FXR Agonist, in Patients With Noncirrhotic NASH: A Phase 2 Randomized Controlled Trial. Hepatology 2020; 72:58-71. [PMID: 32115759 DOI: 10.1002/hep.31205] [Citation(s) in RCA: 194] [Impact Index Per Article: 48.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 01/06/2020] [Accepted: 02/12/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND AIMS We evaluated the safety and efficacy of cilofexor (formerly GS-9674), a small-molecule nonsteroidal agonist of farnesoid X receptor, in patients with nonalcoholic steatohepatitis (NASH). APPROACH AND RESULTS In this double-blind, placebo-controlled, phase 2 trial, 140 patients with noncirrhotic NASH, diagnosed by magnetic resonance imaging-proton density fat fraction (MRI-PDFF) ≥8% and liver stiffness ≥2.5 kPa by magnetic resonance elastography (MRE) or historical liver biopsy, were randomized to receive cilofexor 100 mg (n = 56), 30 mg (n = 56), or placebo (n = 28) orally once daily for 24 weeks. MRI-PDFF, liver stiffness by MRE and transient elastography, and serum markers of fibrosis were measured at baseline and week 24. At baseline, median MRI-PDFF was 16.3% and MRE-stiffness was 3.27 kPa. At week 24, patients receiving cilofexor 100 mg had a median relative decrease in MRI-PDFF of -22.7%, compared with an increase of 1.9% in those receiving placebo (P = 0.003); the 30-mg group had a relative decrease of -1.8% (P = 0.17 vs. placebo). Declines in MRI-PDFF of ≥30% were experienced by 39% of patients receiving cilofexor 100 mg (P = 0.011 vs. placebo), 14% of those receiving cilofexor 30 mg (P = 0.87 vs. placebo), and 13% of those receiving placebo. Serum gamma-glutamyltransferase, C4, and primary bile acids decreased significantly at week 24 in both cilofexor treatment groups, whereas significant changes in Enhanced Liver Fibrosis scores and liver stiffness were not observed. Cilofexor was generally well-tolerated. Moderate to severe pruritus was more common in patients receiving cilofexor 100 mg (14%) than in those receiving cilofexor 30 mg (4%) and placebo (4%). CONCLUSIONS Cilofexor for 24 weeks was well-tolerated and provided significant reductions in hepatic steatosis, liver biochemistry, and serum bile acids in patients with NASH. ClinicalTrials.gov No. NCT02854605.
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Affiliation(s)
| | | | | | | | | | | | | | - Vincent Wai-Sun Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | | | | | | | | | - Eric J Lawitz
- Texas Liver Institute, University of Texas Health San Antonio, San Antonio, TX
| | - Edward J Gane
- Liver Unit, Auckland City Hospital, Auckland, New Zealand
| | | | - Jun Xu
- Gilead Sciences, Inc., Foster City, CA
| | | | | | | | | | | | | | - Mary Rinella
- Feinberg School of Medicine, Northwestern University, Chicago, IL
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15
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Hamilton G, Schlein AN, Wolfson T, Cunha GM, Fowler KJ, Middleton MS, Loomba R, Sirlin CB. The relationship between liver triglyceride composition and proton density fat fraction as assessed by 1 H MRS. NMR Biomed 2020; 33:e4286. [PMID: 32128921 PMCID: PMC7211117 DOI: 10.1002/nbm.4286] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 02/11/2020] [Accepted: 02/12/2020] [Indexed: 05/05/2023]
Abstract
The aim of this study was to estimate parameters determining liver triglyceride composition (TC) using 1 H MRS and to assess how TC estimability is affected by proton density fat fraction (PDFF) in adults with nonalcoholic fatty liver disease (NAFLD). In this prospective single-site study, 199 adults with known or suspected NAFLD in whom other causes of liver disease were excluded underwent two 1 H MRS STimulated Echo Acquisition Method (STEAM) sequences at 3 T. A respiratory-gated water-suppressed free breathing sequence (TE 10 ms, 16 signal averages) was used to assess TC in terms of the number of double bonds (ndb) and methylene-interrupted double bonds (nmidb), and a single breath-hold-long TR, multi-TE sequence (TR 3500 ms), which acquired five single average spectra over TE 10-30 ms, was used to estimate liver PDFF. Ndb and nmidb estimability was qualitatively assessed for each case and summarized descriptively. The consistency of ndb and nmidb estimation was examined using ROC analysis. The relationship between ndb and nmidb values and PDFF was presented graphically. Quality-of-fit of ndb and nmidb versus PDFF was evaluated by Pearson-r correlation. A significance level of 0.05 was used. In 263 1 H MRS examinations performed on 199 adult participants, ndb and nmidb were successfully estimated in 7/53 (13.2%) examinations with PDFF < 4%, 13/30 (43.3%) examinations with PDFF between 4% and 7%, 33/41 (80.5%) examinations with PDFF between 7% and 10%, and 124/139 (89.2%) examinations with PDFF > 10% (maximum PDFF 38.1%). Liver TC could be estimated consistently for PDFF > 6.7%. Both ndb and nmidb decreased with increasing PDFF (ndb = 2.83-0.0160·PDFF, r = -0.449, P < 0.0001); nmidb = 0.75-0.0088·PDFF, r = -0.350, P < 0.0001). In a cohort of adults with known or suspected NAFLD, liver TC becomes more saturated as PDFF increases.
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Affiliation(s)
- Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of
California San Diego, La Jolla, California, USA
| | - Alex N. Schlein
- Liver Imaging Group, Department of Radiology, University of
California San Diego, La Jolla, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistic Laboratory, San Diego
Supercomputing Center, University of California San Diego, San Diego, California,
USA
| | - Guilherme M. Cunha
- Liver Imaging Group, Department of Radiology, University of
California San Diego, La Jolla, California, USA
| | - Kathryn J. Fowler
- Liver Imaging Group, Department of Radiology, University of
California San Diego, La Jolla, California, USA
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of
California San Diego, La Jolla, California, USA
| | - Rohit Loomba
- Division of Epidemiology, Department of Family Medicine and
Public Health, University of California San Diego, La Jolla, California, USA
- NAFLD Research Center, Division of Gastroenterology,
Department of Medicine, University of California San Diego, La Jolla, California,
USA
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of
California San Diego, La Jolla, California, USA
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16
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Mamidipalli A, Fowler KJ, Hamilton G, Wolfson T, Covarrubias Y, Tran C, Fazeli S, Wiens CN, McMillan A, Artz NS, Funk LM, Campos GM, Greenberg JA, Gamst A, Middleton MS, Schwimmer JB, Reeder SB, Sirlin CB. Prospective comparison of longitudinal change in hepatic proton density fat fraction (PDFF) estimated by magnitude-based MRI (MRI-M) and complex-based MRI (MRI-C). Eur Radiol 2020; 30:5120-5129. [PMID: 32318847 DOI: 10.1007/s00330-020-06858-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 03/11/2020] [Accepted: 04/01/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE To compare longitudinal hepatic proton density fat fraction (PDFF) changes estimated by magnitude- vs. complex-based chemical-shift-encoded MRI during a weight loss surgery (WLS) program in severely obese adults with biopsy-proven nonalcoholic fatty liver disease (NAFLD). METHODS This was a secondary analysis of a prospective dual-center longitudinal study of 54 adults (44 women; mean age 52 years; range 27-70 years) with obesity, biopsy-proven NAFLD, and baseline PDFF ≥ 5%, enrolled in a WLS program. PDFF was estimated by confounder-corrected chemical-shift-encoded MRI using magnitude (MRI-M)- and complex (MRI-C)-based techniques at baseline (visit 1), after a 2- to 4-week very low-calorie diet (visit 2), and at 1, 3, and 6 months (visits 3 to 5) after surgery. At each visit, PDFF values estimated by MRI-M and MRI-C were compared by a paired t test. Rates of PDFF change estimated by MRI-M and MRI-C for visits 1 to 3, and for visits 3 to 5 were assessed by Bland-Altman analysis and intraclass correlation coefficients (ICCs). RESULTS MRI-M PDFF estimates were lower by 0.5-0.7% compared with those of MRI-C at all visits (p < 0.001). There was high agreement and no difference between PDFF change rates estimated by MRI-M vs. MRI-C for visits 1 to 3 (ICC 0.983, 95% CI 0.971, 0.99; bias = - 0.13%, p = 0.22), or visits 3 to 5 (ICC 0.956, 95% CI 0.919-0.977%; bias = 0.03%, p = 0.36). CONCLUSION Although MRI-M underestimates PDFF compared with MRI-C cross-sectionally, this bias is consistent and MRI-M and MRI-C agree in estimating the rate of hepatic PDFF change longitudinally. KEY POINTS • MRI-M demonstrates a significant but small and consistent bias (0.5-0.7%; p < 0.001) towards underestimation of PDFF compared with MRI-C at 3 T. • Rates of PDFF change estimated by MRI-M and MRI-C agree closely (ICC 0.96-0.98) in adults with severe obesity and biopsy- proven NAFLD enrolled in a weight loss surgery program. • Our findings support the use of either MRI technique (MRI-M or MRI-C) for clinical care or by individual sites or for multi-center trials that include PDFF change as an endpoint. However, since there is a bias in their measurements, the same technique should be used in any given patient for longitudinal follow-up.
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Affiliation(s)
- Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA
| | - Kathryn J Fowler
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, Supercomputer Center, University of California - San Diego, San Diego, CA, USA
| | - Yesenia Covarrubias
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA
| | - Calvin Tran
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA
| | - Soudabeh Fazeli
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA
| | - Curtis N Wiens
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - Alan McMillan
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - Nathan S Artz
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - Luke M Funk
- Department of Surgery, University of Wisconsin, Madison, WI, USA.,William S. Middleton VA, Madison, WI, USA
| | - Guilherme M Campos
- Department of Surgery, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, Virginia, USA
| | | | - Anthony Gamst
- Computational and Applied Statistics Laboratory, Supercomputer Center, University of California - San Diego, San Diego, CA, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA
| | - Jeffrey B Schwimmer
- Division of Gastroenterology; Hepatology and Nutrition; Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.,Department of Gastroenterology, Rady Children's Hospital, San Diego, CA, USA
| | - Scott B Reeder
- Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin, Madison, WI, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, CA, USA.
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17
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Cunha GM, Thai TT, Hamilton G, Covarrubias Y, Schlein A, Middleton MS, Wiens CN, McMillan A, Agni R, Funk LM, Campos GM, Horgan S, Jacobson G, Wolfson T, Gamst A, Schwimmer JB, Reeder SB, Sirlin CB. Accuracy of common proton density fat fraction thresholds for magnitude- and complex-based chemical shift-encoded MRI for assessing hepatic steatosis in patients with obesity. Abdom Radiol (NY) 2020; 45:661-671. [PMID: 31781899 DOI: 10.1007/s00261-019-02350-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
PURPOSE MRI proton density fat fraction (PDFF) can be calculated using magnitude (MRI-M) or complex (MRI-C) MRI data. The purpose of this study was to identify, assess, and compare the accuracy of common PDFF thresholds for MRI-M and MRI-C for assessing hepatic steatosis in patients with obesity, using histology as reference. METHODS This two-center prospective study included patients undergoing MRI-C- and MRI-M-PDFF estimations within 3 days before weight loss surgery. Liver biopsy was performed, and histology-determined steatosis grades were used as reference standard. Using receiver operating characteristics (ROC) analysis on data pooled from both methods, single common thresholds for diagnosing and differentiating none or mild (0-1) from moderate to severe steatosis (2-3) were selected as the ones achieving the highest sensitivity while providing at least 90% specificity. Selection methods were cross-validated. Performances were compared using McNemar's tests. RESULTS Of 81 included patients, 54 (67%) had steatosis. The common PDFF threshold for diagnosing steatosis was 5.4%, which provided a cross-validated 0.88 (95% CI 0.77-0.95) sensitivity and 0.92 (0.75-0.99) specificity for MRI-M and 0.87 sensitivity (0.75-0.94) with 0.81 (0.61-0.93) specificity for MRI-C. The common PDFF threshold to differentiate steatosis grades 0-1 from 2 to 3 was 14.7%, which provided cross-validated 0.86 (95% CI 0.59-0.98) sensitivity and 0.95 (0.87-0.99) specificity for MRI-M and 0.93 sensitivity (0.68-0.99) with 0.97(0.89-0.99) specificity for MRI-C. CONCLUSION If independently validated, diagnostic thresholds of 5.4% and 14.7% could be adopted for both techniques for detecting and differentiating none to mild from moderate to severe steatosis, respectively, with high diagnostic accuracy.
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Affiliation(s)
- Guilherme Moura Cunha
- Liver Imaging Group, Radiology, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA.
- Liver Imaging Group, Radiology, Altman Clinical Translational Research Institute, 9452 Medical Center Drive, Lower Level 501, La Jolla, CA, 92037, USA.
| | - Tydus T Thai
- Liver Imaging Group, Radiology, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Gavin Hamilton
- Liver Imaging Group, Radiology, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Yesenia Covarrubias
- Liver Imaging Group, Radiology, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Alexandra Schlein
- Liver Imaging Group, Radiology, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Michael S Middleton
- Liver Imaging Group, Radiology, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Curtis N Wiens
- Department of Radiology, E3/366 Clinical Science Center, University of Wisconsin, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI, 53792-3252, USA
| | - Alan McMillan
- Department of Radiology, E3/366 Clinical Science Center, University of Wisconsin, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI, 53792-3252, USA
| | - Rashmi Agni
- Department of Pathology and Laboratory Medicine, University of Wisconsin School of Medicine and Public Health, 3170 UW Medical Foundation Centennial Building (MFCB), 1685 Highland Avenue, Madison, WI, 53705-2281, USA
| | - Luke M Funk
- Surgery, University of Wisconsin, Clinical Science Center, 600 Highland Avenue, Madison, WI, 53792-3252, USA
| | - Guilherme M Campos
- Department of Surgery, West Hospital, Virginia Commonwealth University, 1200 East Broad Street 16th Floor, West Wing Box 980645, Richmond, VA, 23298-0645, USA
| | - Santiago Horgan
- Surgery, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Garth Jacobson
- Surgery, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Anthony Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Jeffrey B Schwimmer
- Pediatrics, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
| | - Scott B Reeder
- Department of Radiology, E3/366 Clinical Science Center, University of Wisconsin, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI, 53792-3252, USA
- Medical Physics, University of Wisconsin Madison, Clinical Science Center, 600 Highland Avenue, Madison, WI, 53792-3252, USA
- Biomedical Engineering, Madison, WI, Clinical Science Center, 600 Highland Avenue, Madison, WI, 53792-3252, USA
| | - Claude B Sirlin
- Liver Imaging Group, Radiology, University of California-San Diego, 9500 Gilman Drive, San Diego, CA, 92037, USA
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18
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Goyal NP, Sawh MC, Ugalde-Nicalo P, Angeles JE, Proudfoot JA, Newton KP, Middleton MS, Sirlin CB, Schwimmer JB. Evaluation of Quantitative Imaging Biomarkers for Early-phase Clinical Trials of Steatohepatitis in Adolescents. J Pediatr Gastroenterol Nutr 2020; 70:99-105. [PMID: 31633654 PMCID: PMC8053386 DOI: 10.1097/mpg.0000000000002535] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Early-phase pediatric nonalcoholic fatty liver disease (NAFLD) clinical trials are designed with noninvasive parameters to assess potential efficacy. Increasingly, these parameters include magnetic resonance imaging (MRI)-derived proton density fat fraction (PDFF) and MR elastography (MRE)-derived shear stiffness as biomarkers of hepatic steatosis and fibrosis, respectively. Understanding fluctuations in these measures is essential for calculating trial sample sizes, interpreting results, and planning clinical drug trials in children with NAFLD. Lack of such data in children constitutes a critical knowledge gap. Therefore, the primary aim of this study was to assess whole-liver MRI-PDFF change in adolescents with nonalcoholic steatohepatitis (NASH) over 12 weeks. METHODS Adolescents 12 to 19 years with biopsy-proven NASH undergoing standard-of-care treatment were enrolled. Baseline and week-12 assessments of anthropometrics, transaminases, MRI-PDFF, and MRE stiffness were obtained. RESULTS Fifteen adolescents were included (mean age 15.7 [SD 2.9] years). Hepatic MRI-PDFF was stable over 12 weeks (mean absolute change -0.8%, P = 0.24). Correlation between baseline and week-12 values of MRI-PDFF was high (ICC = 0.97, 95% CI 0.90-0.99). MRE stiffness was stable (mean percentage change 2.7%, P = 0.44); correlation between baseline and week-12 values was moderate (ICC = 0.47; 95% CI 0-0.79). Changes in weight, BMI, and aminotransferases were not statistically significant. CONCLUSION In adolescents with NASH, fluctuations in hepatic MRI-PDFF and MRE stiffness over 12 weeks of standard-of-care were small. These data on the natural fluctuations in quantitative imaging biomarkers can serve as a reference for interventional trials in pediatric NASH and inform the interpretation and planning of clinical trials.
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Affiliation(s)
- Nidhi P. Goyal
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
- Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, California
| | - Mary Catherine Sawh
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
- Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, California
| | - Patricia Ugalde-Nicalo
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Jorge E. Angeles
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - James A. Proudfoot
- Clinical and Translational Research Institute, University of California, San Diego
| | - Kimberly P. Newton
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
- Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, California
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
- Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, California
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19
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Wang K, Mamidipalli A, Retson T, Bahrami N, Hasenstab K, Blansit K, Bass E, Delgado T, Cunha G, Middleton MS, Loomba R, Neuschwander-Tetri BA, Sirlin CB, Hsiao A. Automated CT and MRI Liver Segmentation and Biometry Using a Generalized Convolutional Neural Network. Radiol Artif Intell 2019; 1. [PMID: 32582883 DOI: 10.1148/ryai.2019180022] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Purpose To assess feasibility of training a convolutional neural network (CNN) to automate liver segmentation across different imaging modalities and techniques used in clinical practice and apply this to enable automation of liver biometry. Methods We trained a 2D U-Net CNN for liver segmentation in two stages using 330 abdominal MRI and CT exams acquired at our institution. First, we trained the neural network with non-contrast multi-echo spoiled-gradient-echo (SGPR)images with 300 MRI exams to provide multiple signal-weightings. Then, we used transfer learning to generalize the CNN with additional images from 30 contrast-enhanced MRI and CT exams.We assessed the performance of the CNN using a distinct multi-institutional data set curated from multiple sources (n = 498 subjects). Segmentation accuracy was evaluated by computing Dice scores. Utilizing these segmentations, we computed liver volume from CT and T1-weighted (T1w) MRI exams, and estimated hepatic proton- density-fat-fraction (PDFF) from multi-echo T2*w MRI exams. We compared quantitative volumetry and PDFF estimates between automated and manual segmentation using Pearson correlation and Bland-Altman statistics. Results Dice scores were 0.94 ± 0.06 for CT (n = 230), 0.95 ± 0.03 (n = 100) for T1w MR, and 0.92 ± 0.05 for T2*w MR (n = 169). Liver volume measured by manual and automated segmentation agreed closely for CT (95% limit-of-agreement (LoA) = [-298 mL, 180 mL]) and T1w MR (LoA = [-358 mL, 180 mL]). Hepatic PDFF measured by the two segmentations also agreed closely (LoA = [-0.62%, 0.80%]). Conclusions Utilizing a transfer-learning strategy, we have demonstrated the feasibility of a CNN to be generalized to perform liver segmentations across different imaging techniques and modalities. With further refinement and validation, CNNs may have broad applicability for multimodal liver volumetry and hepatic tissue characterization.
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Affiliation(s)
- Kang Wang
- Artificial Intelligence and Data Analytic Laboratory (AiDA lab), Department of Radiology, University of California, San Diego. La Jolla, CA 92092.,Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Tara Retson
- Artificial Intelligence and Data Analytic Laboratory (AiDA lab), Department of Radiology, University of California, San Diego. La Jolla, CA 92092.,Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Naeim Bahrami
- Artificial Intelligence and Data Analytic Laboratory (AiDA lab), Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Kyle Hasenstab
- Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Kevin Blansit
- Artificial Intelligence and Data Analytic Laboratory (AiDA lab), Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Emily Bass
- Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Timoteo Delgado
- Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Guilherme Cunha
- Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Rohit Loomba
- Department of Hepatology, University of California, San Diego. La Jolla, CA 92029
| | | | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego. La Jolla, CA 92092
| | - Albert Hsiao
- Artificial Intelligence and Data Analytic Laboratory (AiDA lab), Department of Radiology, University of California, San Diego. La Jolla, CA 92092
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20
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Schwimmer JB, Ugalde-Nicalo P, Welsh JA, Angeles JE, Cordero M, Harlow KE, Alazraki A, Durelle J, Knight-Scott J, Newton KP, Cleeton R, Knott C, Konomi J, Middleton MS, Travers C, Sirlin CB, Hernandez A, Sekkarie A, McCracken C, Vos MB. Effect of a Low Free Sugar Diet vs Usual Diet on Nonalcoholic Fatty Liver Disease in Adolescent Boys: A Randomized Clinical Trial. JAMA 2019; 321:256-265. [PMID: 30667502 PMCID: PMC6440226 DOI: 10.1001/jama.2018.20579] [Citation(s) in RCA: 142] [Impact Index Per Article: 28.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
IMPORTANCE Pediatric guidelines for the management of nonalcoholic fatty liver disease (NAFLD) recommend a healthy diet as treatment. Reduction of sugary foods and beverages is a plausible but unproven treatment. OBJECTIVE To determine the effects of a diet low in free sugars (those sugars added to foods and beverages and occurring naturally in fruit juices) in adolescent boys with NAFLD. DESIGN, SETTING, AND PARTICIPANTS An open-label, 8-week randomized clinical trial of adolescent boys aged 11 to 16 years with histologically diagnosed NAFLD and evidence of active disease (hepatic steatosis >10% and alanine aminotransferase level ≥45 U/L) randomized 1:1 to an intervention diet group or usual diet group at 2 US academic clinical research centers from August 2015 to July 2017; final date of follow-up was September 2017. INTERVENTIONS The intervention diet consisted of individualized menu planning and provision of study meals for the entire household to restrict free sugar intake to less than 3% of daily calories for 8 weeks. Twice-weekly telephone calls assessed diet adherence. Usual diet participants consumed their regular diet. MAIN OUTCOMES AND MEASURES The primary outcome was change in hepatic steatosis estimated by magnetic resonance imaging proton density fat fraction measurement between baseline and 8 weeks. The minimal clinically important difference was assumed to be 4%. There were 12 secondary outcomes, including change in alanine aminotransferase level and diet adherence. RESULTS Forty adolescent boys were randomly assigned to either the intervention diet group or the usual diet group (20 per group; mean [SD] age, 13.0 [1.9] years; most were Hispanic [95%]) and all completed the trial. The mean decrease in hepatic steatosis from baseline to week 8 was significantly greater for the intervention diet group (25% to 17%) vs the usual diet group (21% to 20%) and the adjusted week 8 mean difference was -6.23% (95% CI, -9.45% to -3.02%; P < .001). Of the 12 prespecified secondary outcomes, 7 were null and 5 were statistically significant including alanine aminotransferase level and diet adherence. The geometric mean decrease in alanine aminotransferase level from baseline to 8 weeks was significantly greater for the intervention diet group (103 U/L to 61 U/L) vs the usual diet group (82 U/L to 75 U/L) and the adjusted ratio of the geometric means at week 8 was 0.65 U/L (95% CI, 0.53 to 0.81 U/L; P < .001). Adherence to the diet was high in the intervention diet group (18 of 20 reported intake of <3% of calories from free sugar during the intervention). There were no adverse events related to participation in the study. CONCLUSIONS AND RELEVANCE In this study of adolescent boys with NAFLD, 8 weeks of provision of a diet low in free sugar content compared with usual diet resulted in significant improvement in hepatic steatosis. However, these findings should be considered preliminary and further research is required to assess long-term and clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02513121.
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Affiliation(s)
- Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Patricia Ugalde-Nicalo
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla
| | - Jean A. Welsh
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Emory University, Atlanta, Georgia
- Children’s Healthcare of Atlanta, Atlanta, Georgia
- Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, Georgia
| | - Jorge E. Angeles
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla
| | - Maria Cordero
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Emory University, Atlanta, Georgia
| | - Kathryn E. Harlow
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Adina Alazraki
- Department of Radiology, Children’s Healthcare of Atlanta, Atlanta, Georgia
| | - Janis Durelle
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla
| | - Jack Knight-Scott
- Department of Radiology, Children’s Healthcare of Atlanta, Atlanta, Georgia
| | - Kimberly P. Newton
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Rebecca Cleeton
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Emory University, Atlanta, Georgia
| | - Cynthia Knott
- Altman Clinical and Translational Research Institute, School of Medicine, University of California, San Diego, La Jolla
| | - Juna Konomi
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Emory University, Atlanta, Georgia
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, La Jolla
| | - Curtis Travers
- Pediatric Biostatistics Core, Department of Pediatrics, Emory University, Atlanta, Georgia
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, La Jolla
| | - Albert Hernandez
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Emory University, Atlanta, Georgia
| | - Ahlia Sekkarie
- Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, Georgia
| | - Courtney McCracken
- Children’s Healthcare of Atlanta, Atlanta, Georgia
- Pediatric Biostatistics Core, Department of Pediatrics, Emory University, Atlanta, Georgia
| | - Miriam B. Vos
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Emory University, Atlanta, Georgia
- Children’s Healthcare of Atlanta, Atlanta, Georgia
- Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, Georgia
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21
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Jayakumar S, Middleton MS, Lawitz EJ, Mantry PS, Caldwell SH, Arnold H, Mae Diehl A, Ghalib R, Elkhashab M, Abdelmalek MF, Kowdley KV, Stephen Djedjos C, Xu R, Han L, Mani Subramanian G, Myers RP, Goodman ZD, Afdhal NH, Charlton MR, Sirlin CB, Loomba R. Longitudinal correlations between MRE, MRI-PDFF, and liver histology in patients with non-alcoholic steatohepatitis: Analysis of data from a phase II trial of selonsertib. J Hepatol 2019; 70:133-141. [PMID: 30291868 DOI: 10.1016/j.jhep.2018.09.024] [Citation(s) in RCA: 132] [Impact Index Per Article: 26.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 09/18/2018] [Accepted: 09/24/2018] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Non-invasive tools for monitoring treatment response and disease progression in non-alcoholic steatohepatitis (NASH) are needed. Our objective was to evaluate the utility of magnetic resonance (MR)-based hepatic imaging measures for the assessment of liver histology in patients with NASH. METHODS We analyzed data from patients with NASH and stage 2 or 3 fibrosis enrolled in a phase II study of selonsertib. Pre- and post-treatment assessments included centrally read MR elastography (MRE)-estimated liver stiffness, MR imaging-estimated proton density fat fraction (MRI-PDFF), and liver biopsies evaluated according to the NASH Clinical Research Network classification and the non-alcoholic fatty liver disease activity score (NAS). RESULTS Among 54 patients with MRE and biopsies at baseline and week 24, 18 (33%) had fibrosis improvement (≥1-stage reduction) after undergoing 24 weeks of treatment with the study drug. The area under the receiver operating characteristic curve (AUROC) of MRE-stiffness to predict fibrosis improvement was 0.62 (95% CI 0.46-0.78) and the optimal threshold was a ≥0% relative reduction. At this threshold, MRE had 67% sensitivity, 64% specificity, 48% positive predictive value, 79% negative predictive value. Among 65 patients with MRI-PDFF and biopsies at baseline and week 24, a ≥1-grade reduction in steatosis was observed in 18 (28%). The AUROC of MRI-PDFF to predict steatosis response was 0.70 (95% CI 0.57-0.83) and the optimal threshold was a ≥0% relative reduction. At this threshold, MRI-PDFF had 89% sensitivity and 47% specificity, 39% positive predictive value, and 92% negative predictive value. CONCLUSIONS These preliminary data support the further evaluation of MRE-stiffness and MRI-PDFF for the longitudinal assessment of histologic response in patients with NASH. LAY SUMMARY Liver biopsy is a potentially painful and risky method to assess damage to the liver due to non-alcoholic steatohepatitis (NASH). We analyzed data from a clinical trial to determine if 2 methods of magnetic resonance imaging - 1 to measure liver fat and 1 to measure liver fibrosis (scarring) - could potentially replace liver biopsy in evaluating NASH-related liver injury. Both imaging methods were correlated with biopsy in showing the effects of NASH on the liver.
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Affiliation(s)
- Saumya Jayakumar
- University of California at San Diego, San Diego, CA, United States
| | | | - Eric J Lawitz
- Texas Liver Institute, University of Texas Health San Antonio, San Antonio, TX, United States
| | - Parvez S Mantry
- The Liver Institute at Methodist Dallas, Dallas, TX, United States
| | | | - Hays Arnold
- Gastroenterology Consultants of San Antonio, San Antonio, TX, United States
| | | | - Reem Ghalib
- Texas Clinical Research Institute, Arlington, TX, United States
| | | | | | | | | | - Ren Xu
- Gilead Sciences, Inc., Foster City, CA, United States
| | - Ling Han
- Gilead Sciences, Inc., Foster City, CA, United States
| | | | | | | | - Nezam H Afdhal
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | | | - Claude B Sirlin
- University of California at San Diego, San Diego, CA, United States
| | - Rohit Loomba
- University of California at San Diego, San Diego, CA, United States.
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22
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Lawitz EJ, Coste A, Poordad F, Alkhouri N, Loo N, McColgan BJ, Tarrant JM, Nguyen T, Han L, Chung C, Ray AS, McHutchison JG, Subramanian GM, Myers RP, Middleton MS, Sirlin C, Loomba R, Nyangau E, Fitch M, Li K, Hellerstein M. Acetyl-CoA Carboxylase Inhibitor GS-0976 for 12 Weeks Reduces Hepatic De Novo Lipogenesis and Steatosis in Patients With Nonalcoholic Steatohepatitis. Clin Gastroenterol Hepatol 2018; 16:1983-1991.e3. [PMID: 29705265 DOI: 10.1016/j.cgh.2018.04.042] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 03/15/2018] [Accepted: 04/17/2018] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Increased de novo lipogenesis (DNL) contributes to the pathogenesis of nonalcoholic steatohepatitis (NASH). Acetyl-CoA carboxylase catalyzes the rate-limiting step in DNL. We evaluated the safety and efficacy of GS-0976, a small molecule inhibitor of acetyl-CoA carboxylase, in patients with NASH. METHODS In an open-label prospective study, patients with NASH (n = 10) received GS-0976 20 mg orally once daily for 12 weeks. NASH was diagnosed based on a proton density fat fraction estimated by magnetic resonance imaging (MRI-PDFF) ≥10% and liver stiffness by magnetic resonance elastography (MRE) ≥2.88 kPa. The contribution from hepatic DNL to plasma palmitate was measured by 14 days of heavy water labeling before and at the end of treatment. We performed the same labelling protocol in an analysis of healthy volunteers who were not given DNL (controls, n = 10). MRI-PDFF and MRE at baseline, and at weeks 4 and 12 of GS-0976 administration, were measured. We analyzed markers of liver injury and serum markers of fibrosis. RESULTS The contribution of hepatic DNL to plasma palmitate was significantly greater in patients with NASH compared with controls (43% vs 18%) (P = .003). After 12 weeks administration of GS-0976, the median hepatic DNL was reduced 22% from baseline in patients with NASH (P = .004). Compared with baseline, reductions in MRI-PDFF at week 12 (15.7% vs 9.1% at baseline; P = .006), liver stiffness by MRE (3.4 kPa vs 3.1 kPa at baseline; P = .049), TIMP metallopeptidase inhibitor 1 (275 ng/mL vs 244 ng/mL at baseline; P = .049), and serum level of alanine aminotransferase (101 U/L vs 57 U/L at baseline; P = .23) were consistent with decreased hepatic lipid content and liver injury. At week 12, 7 patients (70%) had a ≥30% decrease in MRI-PDFF. CONCLUSION In an open-label study, patients with NASH given GS-0976 for 12 weeks had reduced hepatic DNL, steatosis, and markers of liver injury. ClinicalTrials.gov no: NCT02856555.
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Affiliation(s)
- Eric J Lawitz
- Texas Liver Institute and University of Texas Health San Antonio, San Antonio, Texas.
| | - Angie Coste
- Texas Liver Institute and University of Texas Health San Antonio, San Antonio, Texas
| | - Fred Poordad
- Texas Liver Institute and University of Texas Health San Antonio, San Antonio, Texas
| | - Naim Alkhouri
- Texas Liver Institute and University of Texas Health San Antonio, San Antonio, Texas
| | - Nicole Loo
- Texas Liver Institute and University of Texas Health San Antonio, San Antonio, Texas
| | | | | | - Tuan Nguyen
- Gilead Sciences, Inc, Foster City, California
| | - Ling Han
- Gilead Sciences, Inc, Foster City, California
| | | | | | | | | | | | | | - Claude Sirlin
- University of California at San Diego, San Diego, California
| | - Rohit Loomba
- University of California at San Diego, San Diego, California
| | - Edna Nyangau
- University of California Berkeley, Berkeley, California
| | - Mark Fitch
- University of California Berkeley, Berkeley, California
| | - Kelvin Li
- University of California Berkeley, Berkeley, California
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23
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Loomba R, Kayali Z, Noureddin M, Ruane P, Lawitz EJ, Bennett M, Wang L, Harting E, Tarrant JM, McColgan BJ, Chung C, Ray AS, Subramanian GM, Myers RP, Middleton MS, Lai M, Charlton M, Harrison SA. GS-0976 Reduces Hepatic Steatosis and Fibrosis Markers in Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology 2018; 155:1463-1473.e6. [PMID: 30059671 PMCID: PMC6318218 DOI: 10.1053/j.gastro.2018.07.027] [Citation(s) in RCA: 216] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 06/18/2018] [Accepted: 07/21/2018] [Indexed: 12/16/2022]
Abstract
BACKGROUND & AIMS De novo lipogenesis is increased in livers of patients with nonalcoholic steatohepatitis (NASH). Acetyl-coenzyme carboxylase catalyzes the rate-limiting step in this process. We evaluated the safety and efficacy of GS-0976, an inhibitor of acetyl-coenzyme A carboxylase in liver, in a phase 2 randomized placebo-controlled trial of patients with NASH. METHODS We analyzed data from 126 patients with hepatic steatosis of at least 8%, based on the magnetic resonance imaging-estimated proton density fat fraction (MRI-PDFF), and liver stiffness of at least 2.5 kPa, based on magnetic resonance elastography measurement or historical biopsy result consistent with NASH and F1-F3 fibrosis. Patients were randomly assigned (2:2:1) to groups given GS-0976 20 mg, GS-0976 5 mg, or placebo daily for 12 weeks, from August 8, 2016 through July 18, 2017. Measures of hepatic steatosis, stiffness, serum markers of fibrosis, and plasma metabolomics were evaluated. The primary aims were to confirm previous findings and evaluate the relation between dose and efficacy. RESULTS A relative decrease of at least 30% from baseline in MRI-PDFF (PDFF response) occurred in 48% of patients given GS-0976 20 mg (P = .004 vs placebo), 23% given GS-0976 5 mg (P = .43 vs placebo), and 15% given placebo. Median relative decreases in MRI-PDFF were greater in patients given GS-0976 20 mg (decrease of 29%) than those given placebo (decrease of 8%; P = .002). Changes in magnetic resonance elastography-measured stiffness did not differ among groups, but a dose-dependent decrease in the fibrosis marker tissue inhibitor of metalloproteinase 1 was observed in patients given GS-0976 20 mg. Plasma levels of acylcarnitine species also decreased in patients with a PDFF response given GS-0976 20 mg. GS-0976 was safe, but median relative increases of 11% and 13% in serum levels of triglycerides were observed in patients given GS-0976. CONCLUSIONS In a randomized placebo-controlled trial of patients with NASH, we found 12-week administration of GS-0976 20 mg decreased hepatic steatosis, selected markers of fibrosis, and liver biochemistry. ClinicalTrials.gov ID NCT02856555.
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Affiliation(s)
- Rohit Loomba
- University of California at San Diego, La Jolla, California.
| | - Zeid Kayali
- Inland Empire Liver Foundation, Rialto, California
| | | | - Peter Ruane
- Ruane Medical and Liver Health Institute, Los Angeles, California
| | - Eric J. Lawitz
- Texas Liver Institute, University of Texas Health San Antonio, San Antonio, Texas
| | - Michael Bennett
- Atlanta Gastroenterology Associates, Atlanta, Georgia; (6)Medical Research Associates Group, San Diego, California
| | - Lulu Wang
- Gilead Sciences, Inc, Foster City, California
| | | | | | | | | | | | | | | | | | - Michelle Lai
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
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24
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Bashir MR, Wolfson T, Gamst AC, Fowler KJ, Ohliger M, Shah SN, Alazraki A, Trout AT, Behling C, Allende DS, Loomba R, Sanyal A, Schwimmer J, Lavine JE, Shen W, Tonascia J, Van Natta ML, Mamidipalli A, Hooker J, Kowdley KV, Middleton MS, Sirlin CB. Hepatic R2* is more strongly associated with proton density fat fraction than histologic liver iron scores in patients with nonalcoholic fatty liver disease. J Magn Reson Imaging 2018; 49:1456-1466. [PMID: 30318834 DOI: 10.1002/jmri.26312] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 08/09/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The liver R2* value is widely used as a measure of liver iron but may be confounded by the presence of hepatic steatosis and other covariates. PURPOSE To identify the most influential covariates for liver R2* values in patients with nonalcoholic fatty liver disease (NAFLD). STUDY TYPE Retrospective analysis of prospectively acquired data. POPULATION Baseline data from 204 subjects enrolled in NAFLD/NASH (nonalcoholic steatohepatitis) treatment trials. FIELD STRENGTH 1.5T and 3T; chemical-shift encoded multiecho gradient echo. ASSESSMENT Correlation between liver proton density fat fraction and R2*; assessment for demographic, metabolic, laboratory, MRI-derived, and histological covariates of liver R2*. STATISTICAL TESTS Pearson's and Spearman's correlations; univariate analysis; gradient boosting machines (GBM) multivariable machine-learning method. RESULTS Hepatic proton density fat fraction (PDFF) was the most strongly correlated covariate for R2* at both 1.5T (r = 0.652, P < 0.0001) and at 3T (r = 0.586, P < 0.0001). In the GBM analysis, hepatic PDFF was the most influential covariate for hepatic R2*, with relative influences (RIs) of 61.3% at 1.5T and 47.5% at 3T; less influential covariates had RIs of up to 11.5% at 1.5T and 16.7% at 3T. Nonhepatocellular iron was weakly associated with R2* at 3T only (RI 6.7%), and hepatocellular iron was not associated with R2* at either field strength. DATA CONCLUSION Hepatic PDFF is the most influential covariate for R2* at both 1.5T and 3T; nonhepatocellular iron deposition is weakly associated with liver R2* at 3T only. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1456-1466.
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Affiliation(s)
- Mustafa R Bashir
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.,Center for Advanced Magnetic Resonance Development (CAMRD), Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.,Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, North Carolina
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California-San Diego, San Diego, California, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California-San Diego, San Diego, California, USA
| | - Kathryn J Fowler
- Department of Radiology, Washington University, St. Louis, Missouri, USA
| | - Michael Ohliger
- Departments of Radiology and Biomedical Engineering, University of California-San Francisco, San Francisco, California, USA
| | - Shetal N Shah
- Section of Abdominal Imaging and Nuclear Medicine Department, Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Adina Alazraki
- Departments of Radiology and Pediatrics, Emory University School of Medicine/Children's Healthcare of Atlanta, Atlanta, Georgia, USA
| | - Andrew T Trout
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Cynthia Behling
- Department of Pathology, University of California-San Diego, La Jolla, California, USA
| | | | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California-San Diego, La Jolla, California, USA
| | - Arun Sanyal
- Division of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Jeffrey Schwimmer
- Department of Pediatrics, University of California-San Diego, San Diego, California, USA
| | - Joel E Lavine
- Department of Pediatrics, Columbia College of Physicians and Surgeons, New York, New York, USA
| | - Wei Shen
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics and the Institute of Human Nutrition, Columbia University Medical Center, New York, New York, USA
| | - James Tonascia
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Mark L Van Natta
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Jonathan Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Kris V Kowdley
- Liver Care Network and Organ Care Research, Swedish Medical Center, Seattle, Washington, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
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- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
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25
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Ajmera V, Park CC, Caussy C, Singh S, Hernandez C, Bettencourt R, Hooker J, Sy E, Behling C, Xu R, Middleton MS, Valasek MA, Faulkner C, Rizo E, Richards L, Sirlin CB, Loomba R. Magnetic Resonance Imaging Proton Density Fat Fraction Associates With Progression of Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology 2018; 155:307-310.e2. [PMID: 29660324 PMCID: PMC6090543 DOI: 10.1053/j.gastro.2018.04.014] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Revised: 03/28/2018] [Accepted: 04/10/2018] [Indexed: 02/06/2023]
Abstract
Markers are needed to predict progression of nonalcoholic fatty liver disease (NAFLD). The proton density fat fraction, measured by magnetic resonance imaging (MRI-PDFF), provides an accurate, validated marker of hepatic steatosis; however, it is not clear whether the PDFF identifies patients at risk for NAFLD progression. We performed a follow-up study of 95 well-characterized patients with biopsy-proven NAFLD and examined the association between liver fat content and fibrosis progression. MRI-PDFF measurements were made at study entry (baseline). Biopsies were collected from patients at baseline and after a mean time period of 1.75 years. Among patients with no fibrosis at baseline, a higher proportion of patients in the higher liver fat group (MRI-PDFF ≥15.7%) had fibrosis progression (38.1%) than in the lower liver fat group (11.8%) (P = .067). In multivariable-adjusted logistic regression models (adjusted for age, sex, ethnicity, and body mass index), patients in the higher liver fat group had a significantly higher risk of fibrosis progression (multivariable-adjusted odds ratio 6.7; 95% confidence interval 1.01-44.1; P = .049). Our findings associate higher liver fat content, measured by MRI-PDFF, with fibrosis progression.
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Affiliation(s)
- Veeral Ajmera
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | - Charlie C. Park
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | - Cyrielle Caussy
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA,Université Lyon 1, Hospices Civils de Lyon, Lyon, France
| | - Seema Singh
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | - Carolyn Hernandez
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | - Ricki Bettencourt
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | - Jonathan Hooker
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA
| | - Ethan Sy
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA
| | | | - Ronghui Xu
- Department of Family Medicine and Public Health and Department of Mathematics and Division of Epidemiology, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, CA
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA
| | - Mark A. Valasek
- Department of Pathology, University of California, San Diego, CA
| | - Claire Faulkner
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | - Emily Rizo
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | - Lisa Richards
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, CA
| | | | - Rohit Loomba
- NAFLD Research Center, Department of Medicine, University of California San Diego, La Jolla, California; Division of Gastroenterology, Department of Medicine, University of California at San Diego, La Jolla, California.
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26
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Middleton MS, Van Natta ML, Heba ER, Alazraki A, Trout AT, Masand P, Brunt EM, Kleiner DE, Doo E, Tonascia J, Lavine JE, Shen W, Hamilton G, Schwimmer JB, Sirlin CB. Diagnostic accuracy of magnetic resonance imaging hepatic proton density fat fraction in pediatric nonalcoholic fatty liver disease. Hepatology 2018; 67:858-872. [PMID: 29028128 PMCID: PMC6211296 DOI: 10.1002/hep.29596] [Citation(s) in RCA: 98] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Revised: 09/11/2017] [Accepted: 10/12/2017] [Indexed: 12/11/2022]
Abstract
UNLABELLED We assessed the performance of magnetic resonance imaging (MRI) proton density fat fraction (PDFF) in children to stratify hepatic steatosis grade before and after treatment in the Cysteamine Bitartrate Delayed-Release for the Treatment of Nonalcoholic Fatty Liver Disease in Children (CyNCh) trial, using centrally scored histology as reference. Participants had multiecho 1.5 Tesla (T) or 3T MRI on scanners from three manufacturers. Of 169 enrolled children, 110 (65%) and 83 (49%) had MRI and liver biopsy at baseline and at end of treatment (EOT; 52 weeks), respectively. At baseline, 17% (19 of 110), 28% (31 of 110), and 55% (60 of 110) of liver biopsies showed grades 1, 2, and 3 histological steatosis; corresponding PDFF (mean ± SD) values were 10.9 ± 4.1%, 18.4 ± 6.2%, and 25.7 ± 9.7%, respectively. PDFF classified grade 1 versus 2-3 and 1-2 versus 3 steatosis with areas under receiving operator characteristic curves (AUROCs) of 0.87 (95% confidence interval [CI], 0.80, 0.94) and 0.79 (0.70, 0.87), respectively. PDFF cutoffs at 90% specificity were 17.5% for grades 2-3 steatosis and 23.3% for grade 3 steatosis. At EOT, 47% (39 of 83), 41% (34 of 83), and 12% (10 of 83) of biopsies showed improved, unchanged, and worsened steatosis grade, respectively, with corresponding PDFF (mean ± SD) changes of -7.8 ± 6.3%, -1.2 ± 7.8%, and 4.9 ± 5.0%, respectively. PDFF change classified steatosis grade improvement and worsening with AUROCs (95% CIs) of 0.76 (0.66, 0.87) and 0.83 (0.73, 0.92), respectively. PDFF change cut-off values at 90% specificity were -11.0% and +5.5% for improvement and worsening. CONCLUSION MRI-estimated PDFF has high diagnostic accuracy to both classify and predict histological steatosis grade and change in histological steatosis grade in children with NAFLD. (Hepatology 2018;67:858-872).
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Affiliation(s)
- Michael S. Middleton
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, California
| | - Mark L. Van Natta
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Elhamy R. Heba
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, California
| | - Adina Alazraki
- Emory University School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, Georgia
| | - Andrew T. Trout
- Cincinnati Children’s Hospital, Department of Radiology, Cincinnati, Ohio
| | | | | | | | - Edward Doo
- Liver Diseases Section, Digestive Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases
| | - James Tonascia
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Joel E. Lavine
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Columbia University Medical Center, New York, New York
| | - Wei Shen
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Columbia University Medical Center, New York, New York
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, California
| | - Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California; and Department of Gastroenterology, Rady Children’s Hospital, San Diego, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, UCSD School of Medicine, San Diego, California
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Mamidipalli A, Hamilton G, Manning P, Hong CW, Park CC, Wolfson T, Hooker J, Heba E, Schlein A, Gamst A, Durelle J, Paiz M, Middleton MS, Schwimmer JB, Sirlin CB. Cross-sectional correlation between hepatic R2* and proton density fat fraction (PDFF) in children with hepatic steatosis. J Magn Reson Imaging 2018; 47:418-424. [PMID: 28543915 PMCID: PMC5702271 DOI: 10.1002/jmri.25748] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Accepted: 04/10/2017] [Indexed: 12/28/2022] Open
Abstract
PURPOSE To determine the relationship between hepatic proton density fat fraction (PDFF) and R2* in vivo. MATERIALS AND METHODS In this Health Insurance Portability and Accountability Act (HIPAA)-compliant, Institutional Review Board (IRB)-approved, cross-sectional study, we conducted a secondary analysis of 3T magnetic resonance imaging (MRI) exams performed as part of prospective research studies in children in whom conditions associated with iron overload were excluded clinically. Each exam included low-flip-angle, multiecho magnitude (-M) and complex (-C) based chemical-shift-encoded MRI techniques with spectral modeling of fat to generate hepatic PDFF and R2* parametric maps. For each technique and each patient, regions of interest were placed on the maps in each of the nine Couinaud segments, and composite whole-liver PDFF and R2* values were calculated. Pearson's correlation coefficients between PDFF and R2* were computed for each MRI technique. Correlations were compared using Steiger's test. RESULTS In all, 184 children (123 boys, 61 girls) were included in this analysis. PDFF estimated by MRI-M and MRI-C ranged from 1.1-35.4% (9.44 ± 8.76) and 2.1-38.1% (10.1 ± 8.7), respectively. R2* estimated by MRI-M and MRI-C ranged from 32.6-78.7 s-1 (48.4 ± 9.8) and 27.2-71.5 s-1 (42.2 ± 8.6), respectively. There were strong and significant correlations between hepatic PDFF and R2* values estimated by MRI-M (r = 0.874; P < 0.0001) and MRI-C (r = 0.853; P < 0.0001). The correlation coefficients (0.874 vs. 0.853) were not significantly different (P = 0.15). CONCLUSION Hepatic PDFF and R2* are strongly correlated with each other in vivo. This relationship was observed using two different MRI techniques. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:418-424.
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Affiliation(s)
- Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Paul Manning
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Cheng William Hong
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Charlie C. Park
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California – San Diego, San Diego, California, USA
| | - Jonathan Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Elhamy Heba
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Alexandra Schlein
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Anthony Gamst
- Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California – San Diego, San Diego, California, USA
| | - Janis Durelle
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Melissa Paiz
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California - San Diego, San Diego, California
- Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
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Yokoo T, Serai SD, Pirasteh A, Bashir MR, Hamilton G, Hernando D, Hu HH, Hetterich H, Kühn JP, Kukuk GM, Loomba R, Middleton MS, Obuchowski NA, Song JS, Tang A, Wu X, Reeder SB, Sirlin CB. Linearity, Bias, and Precision of Hepatic Proton Density Fat Fraction Measurements by Using MR Imaging: A Meta-Analysis. Radiology 2018; 286:486-498. [PMID: 28892458 PMCID: PMC5813433 DOI: 10.1148/radiol.2017170550] [Citation(s) in RCA: 195] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Purpose To determine the linearity, bias, and precision of hepatic proton density fat fraction (PDFF) measurements by using magnetic resonance (MR) imaging across different field strengths, imager manufacturers, and reconstruction methods. Materials and Methods This meta-analysis was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic literature search identified studies that evaluated the linearity and/or bias of hepatic PDFF measurements by using MR imaging (hereafter, MR imaging-PDFF) against PDFF measurements by using colocalized MR spectroscopy (hereafter, MR spectroscopy-PDFF) or the precision of MR imaging-PDFF. The quality of each study was evaluated by using the Quality Assessment of Studies of Diagnostic Accuracy 2 tool. De-identified original data sets from the selected studies were pooled. Linearity was evaluated by using linear regression between MR imaging-PDFF and MR spectroscopy-PDFF measurements. Bias, defined as the mean difference between MR imaging-PDFF and MR spectroscopy-PDFF measurements, was evaluated by using Bland-Altman analysis. Precision, defined as the agreement between repeated MR imaging-PDFF measurements, was evaluated by using a linear mixed-effects model, with field strength, imager manufacturer, reconstruction method, and region of interest as random effects. Results Twenty-three studies (1679 participants) were selected for linearity and bias analyses and 11 studies (425 participants) were selected for precision analyses. MR imaging-PDFF was linear with MR spectroscopy-PDFF (R2 = 0.96). Regression slope (0.97; P < .001) and mean Bland-Altman bias (-0.13%; 95% limits of agreement: -3.95%, 3.40%) indicated minimal underestimation by using MR imaging-PDFF. MR imaging-PDFF was precise at the region-of-interest level, with repeatability and reproducibility coefficients of 2.99% and 4.12%, respectively. Field strength, imager manufacturer, and reconstruction method each had minimal effects on reproducibility. Conclusion MR imaging-PDFF has excellent linearity, bias, and precision across different field strengths, imager manufacturers, and reconstruction methods. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on October 2, 2017.
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Wang K, Manning P, Szeverenyi N, Wolfson T, Hamilton G, Middleton MS, Vaida F, Yin M, Glaser K, Ehman RL, Sirlin CB. Repeatability and reproducibility of 2D and 3D hepatic MR elastography with rigid and flexible drivers at end-expiration and end-inspiration in healthy volunteers. Abdom Radiol (NY) 2017; 42:2843-2854. [PMID: 28612163 DOI: 10.1007/s00261-017-1206-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
PURPOSE To evaluate the repeatability and reproducibility of 2D and 3D hepatic MRE with rigid and flexible drivers at end-expiration and end-inspiration in healthy volunteers. MATERIALS AND METHODS Nine healthy volunteers underwent two same-day MRE exams separated by a 5- to 10-min break. In each exam, 2D and 3D MRE scans were performed, each under four conditions (2 driver types [rigid, flexible] × 2 breath-hold phases [end-expiration, end-inspiration]). Repeatability (measurements under identical conditions) and reproducibility (measurements under different conditions) were analyzed by calculating bias, limit of agreement, repeatability coefficient (RC), reproducibility coefficient (RDC), intraclass correlation coefficient (ICC), and concordance correlation coefficient (CCC), as appropriate. RESULTS For 2D MRE, RCs and ICCs range between 0.29-0.49 and 0.71-0.91, respectively. For 3D MRE, RCs and ICCs range between 0.16-0.26 and 0.84-0.96, respectively. Stiffness values were biased by breath-hold phase, being higher at end-inspiration than end-expiration, and the differences were significant for 3D MRE (p < 0.01). No bias was found between driver types. Inspiration vs. expiration RDCs and CCCs ranged between 0.30-0.54 and 0.61-0.72, respectively. Rigid vs. flexible driver RDCs and CCCs ranged between 0.10-0.44 and 0.79-0.94, respectively. CONCLUSION This preliminary study suggests that 2D MRE and 3D MRE under most conditions potentially have good repeatability. Our result also points to the possibility that stiffness measured with the rigid and flexible drivers is reproducible. Reproducibility between breath-hold phases was modest, suggesting breath-hold phase might be a confounding factor in MRE-based stiffness measurement. However, larger studies are required to validate these preliminary results.
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Schwimmer JB, Behling C, Angeles JE, Paiz M, Durelle J, Africa J, Newton KP, Brunt EM, Lavine JE, Abrams SH, Masand P, Krishnamurthy R, Wong K, Ehman RL, Yin M, Glaser KJ, Dzyubak B, Wolfson T, Gamst AC, Hooker J, Haufe W, Schlein A, Hamilton G, Middleton MS, Sirlin CB. Magnetic resonance elastography measured shear stiffness as a biomarker of fibrosis in pediatric nonalcoholic fatty liver disease. Hepatology 2017; 66:1474-1485. [PMID: 28493388 PMCID: PMC5650504 DOI: 10.1002/hep.29241] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 03/23/2017] [Accepted: 04/24/2017] [Indexed: 12/14/2022]
Abstract
UNLABELLED Magnetic resonance elastography (MRE) is a promising technique for noninvasive assessment of fibrosis, a major determinant of outcome in nonalcoholic fatty liver disease (NAFLD). However, data in children are limited. The purpose of this study was to determine the accuracy of MRE for the detection of fibrosis and advanced fibrosis in children with NAFLD and to assess agreement between manual and novel automated reading methods. We performed a prospective, multicenter study of two-dimensional (2D) MRE in children with NAFLD. MR elastograms were analyzed manually at two reading centers, and using a new automated technique. Analysis using each approach was done independently. Correlations were determined between MRE analysis methods and fibrosis stage. Thresholds for classifying the presence of fibrosis and of advanced fibrosis were computed and cross-validated. In 90 children with a mean age of 13.1 ± 2.4 years, median hepatic stiffness was 2.35 kPa. Stiffness values derived by each reading center were strongly correlated with each other (r = 0.83). All three analyses were significantly correlated with fibrosis stage (center 1, ρ = 0.53; center 2, ρ = 0.55; and automated analysis, ρ = 0.52; P < 0.001). Overall cross-validated accuracy for detecting any fibrosis was 72.2% for all methods (95% confidence interval [CI], 61.8%-81.1%). Overall cross-validated accuracy for assessing advanced fibrosis was 88.9% (95% CI, 80.5%-94.5%) for center 1, 90.0% (95% CI, 81.9%-95.3%) for center 2, and 86.7% (95% CI, 77.9%-92.9%) for automated analysis. CONCLUSION 2D MRE can estimate hepatic stiffness in children with NAFLD. Further refinement and validation of automated analysis techniques will be an important step in standardizing MRE. How to best integrate MRE into clinical protocols for the assessment of NAFLD in children will require prospective evaluation. (Hepatology 2017;66:1474-1485).
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Affiliation(s)
- Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California,Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Cynthia Behling
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Jorge Eduardo Angeles
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Melissa Paiz
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Janis Durelle
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Jonathan Africa
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Kimberly P. Newton
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Elizabeth M. Brunt
- Department of Pathology and Immunology, Washington University, St. Louis, Missouri
| | | | - Stephanie H. Abrams
- Columbia University, New York, NY,Baylor College of Medicine, Houston, Texas,Houston Methodist Hospital, Houston, Texas
| | | | | | - Kelvin Wong
- Miller Children’s & Women’s Hospital Long Beach, California
| | | | - Meng Yin
- Mayo Clinic, Rochester, Minnesota
| | | | | | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California, San Diego, California
| | - Anthony C. Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California, San Diego, California
| | - Jonathan Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - William Haufe
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Alexandra Schlein
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
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Middleton MS, Heba ER, Hooker CA, Bashir MR, Fowler KJ, Sandrasegaran K, Brunt EM, Kleiner DE, Doo E, Van Natta ML, Tonascia J, Lavine JE, Neuschwander-Tetri BA, Sanyal A, Loomba R, Sirlin CB. Agreement Between Magnetic Resonance Imaging Proton Density Fat Fraction Measurements and Pathologist-Assigned Steatosis Grades of Liver Biopsies From Adults With Nonalcoholic Steatohepatitis. Gastroenterology 2017; 153. [PMID: 28624576 PMCID: PMC5695870 DOI: 10.1053/j.gastro.2017.06.005] [Citation(s) in RCA: 188] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND & AIMS We assessed the diagnostic performance of magnetic resonance imaging (MRI) proton density fat fraction (PDFF) in grading hepatic steatosis and change in hepatic steatosis in adults with nonalcoholic steatohepatitis (NASH) in a multi-center study, using central histology as reference. METHODS We collected data from 113 adults with NASH participating in a multi-center, randomized, double-masked, placebo-controlled, phase 2b trial to compare the efficacy cross-sectionally and longitudinally of obeticholic acid vs placebo. Hepatic steatosis was assessed at baseline and after 72 weeks of obeticholic acid or placebo by liver biopsy and MRI (scanners from different manufacturers, at 1.5T or 3T). We compared steatosis estimates by PDFF vs histology. Histologic steatosis grade was scored in consensus by a pathology committee. Cross-validated receiver operating characteristic (ROC) analyses were performed. RESULTS At baseline, 34% of subjects had steatosis grade 0 or 1, 39% had steatosis grade 2, and 27% had steatosis grade 3; corresponding mean PDFF values were 9.8%±3.7%, 18.1%±4.3%, and 30.1%±8.1%. PDFF classified steatosis grade 0-1 vs 2-3 with an area under the ROC curve (AUROC) of 0.95 (95% CI, 0.91-0.98), and grade 0-2 vs grade 3 steatosis with an AUROC of 0.96 (95% CI, 0.93-0.99). PDFF cut-off values at 90% specificity were 16.3% for grades 2-3 and 21.7% for grade 3, with corresponding sensitivities of 83% and 84%. After 72 weeks' of obeticholic vs placebo, 42% of subjects had a reduced steatosis grade (mean reduction in PDFF from baseline of 7.4%±8.7%), 49% had no change in steatosis grade (mean increase in PDFF from baseline of 0.3%±6.3%), and 9% had an increased steatosis grade (mean increase in PDFF from baseline of 7.7%±6.0%). PDFF change identified subjects with reduced steatosis grade with an AUROC of 0.81 (95% CI, 0.71-0.91) and increased steatosis grade with an AUROC of 0.81 (95% CI, 0.63-0.99). A PDFF reduction of 5.15% identified subjects with reduced steatosis grade with 90% specificity and 58% sensitivity, whereas a PDFF increase of 5.6% identified those with increased steatosis grade with 90% specificity and 57% sensitivity. CONCLUSIONS Based on data from a phase 2 randomized controlled trial of adults with NASH, PDFF estimated by MRI scanners of different field strength and at different sites, accurately classifies grades and changes in hepatic steatosis when histologic analysis of biopsies is used as a reference.
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Affiliation(s)
| | - Elhamy R. Heba
- Department of Radiology, UCSD School of Medicine, San Diego, California
| | | | - Mustafa R. Bashir
- Department of Radiology, Duke University Medical Center, 3808, Durham, North Carolina
| | | | - Kumar Sandrasegaran
- Department of Radiology, Indiana University School of Medicine, Indianapolis, Indiana
| | | | | | - Edward Doo
- Liver Diseases Section, Digestive Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases
| | - Mark L. Van Natta
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - James Tonascia
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Joel E. Lavine
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Columbia University Medical Center, New York, New York
| | | | - Arun Sanyal
- Virginia Commonwealth University School of Medicine, Richmond, Virginia
| | - Rohit Loomba
- NAFLD Translational Research Unit, Division of Gastroenterology, UCSD School of Medicine, San Diego, California
| | - Claude B. Sirlin
- Department of Radiology, UCSD School of Medicine, San Diego, California
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Hong CW, Mamidipalli A, Hooker JC, Hamilton G, Wolfson T, Chen DH, Fazeli Dehkordy S, Middleton MS, Reeder SB, Loomba R, Sirlin CB. MRI proton density fat fraction is robust across the biologically plausible range of triglyceride spectra in adults with nonalcoholic steatohepatitis. J Magn Reson Imaging 2017; 47:995-1002. [PMID: 28851124 DOI: 10.1002/jmri.25845] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Accepted: 08/08/2017] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Proton density fat fraction (PDFF) estimation requires spectral modeling of the hepatic triglyceride (TG) signal. Deviations in the TG spectrum may occur, leading to bias in PDFF quantification. PURPOSE To investigate the effects of varying six-peak TG spectral models on PDFF estimation bias. STUDY TYPE Retrospective secondary analysis of prospectively acquired clinical research data. POPULATION Forty-four adults with biopsy-confirmed nonalcoholic steatohepatitis. FIELD STRENGTH/SEQUENCE Confounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy. ASSESSMENT In each patient, 61 pairs of colocalized MRI-PDFF and MRS-PDFF values were estimated: one pair used the standard six-peak spectral model, the other 60 were six-peak variants calculated by adjusting spectral model parameters over their biologically plausible ranges. MRI-PDFF values calculated using each variant model and the standard model were compared, and the agreement between MRI-PDFF and MRS-PDFF was assessed. STATISTICAL TESTS MRS-PDFF and MRI-PDFF were summarized descriptively. Bland-Altman (BA) analyses were performed between PDFF values calculated using each variant model and the standard model. Linear regressions were performed between BA biases and mean PDFF values for each variant model, and between MRI-PDFF and MRS-PDFF. RESULTS Using the standard model, mean MRS-PDFF of the study population was 17.9 ± 8.0% (range: 4.1-34.3%). The difference between the highest and lowest mean variant MRI-PDFF values was 1.5%. Relative to the standard model, the model with the greatest absolute BA bias overestimated PDFF by 1.2%. Bias increased with increasing PDFF (P < 0.0001 for 59 of the 60 variant models). MRI-PDFF and MRS-PDFF agreed closely for all variant models (R2 = 0.980, P < 0.0001). DATA CONCLUSION Over a wide range of hepatic fat content, PDFF estimation is robust across the biologically plausible range of TG spectra. Although absolute estimation bias increased with higher PDFF, its magnitude was small and unlikely to be clinically meaningful. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:995-1002.
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Affiliation(s)
- Cheng William Hong
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, University of California San Diego, San Diego, California, USA
| | - Dennis H Chen
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Soudabeh Fazeli Dehkordy
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Scott B Reeder
- Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin Madison, Madison, Wisconsin
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
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Park CC, Hamilton G, Desai A, Zand KA, Wolfson T, Hooker JC, Costa E, Heba E, Clark L, Gamst A, Loomba R, Middleton MS, Sirlin CB. Effect of intravenous gadoxetate disodium and flip angle on hepatic proton density fat fraction estimation with six-echo, gradient-recalled-echo, magnitude-based MR imaging at 3T. Abdom Radiol (NY) 2017; 42:1189-1198. [PMID: 28028556 DOI: 10.1007/s00261-016-0992-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
PURPOSE The aim of the study was to determine in patients undergoing gadoxetate disodium (Gx)-enhanced MR exams whether proton density fat fraction (PDFF) estimation accuracy of magnitude-based multi-gradient-echo MRI (MRI-M) could be improved by using high flip angle (FA) on post-contrast images. MATERIALS AND METHODS Thirty-one adults with known or suspected hepatic steatosis undergoing 3T clinical Gx-enhanced liver MRI were enrolled prospectively. MR spectroscopy (MRS), the reference standard, was performed before Gx to measure MRS-PDFF. Low (10°)- and high (50°)-flip angle (FA) MRI-M sequences were acquired before and during the hepatobiliary phase after Gx administration; MRI-PDFF was estimated in the MRS-PDFF voxel location. Linear regression parameters (slope, intercept, average bias, R 2) were calculated for MRS-PDFF as a function of MRI-PDFF for each MRI-M sequence (pre-Gx low-FA, pre-Gx high-FA, post-Gx low-FA, post-Gx high-FA) for all patients and for patients with MRS-PDFF <10%. Regression parameters were compared (Bonferroni-adjusted bootstrap-based tests). RESULTS Three of the four MRI-M sequences (pre-Gx low-FA, post-Gx low-FA, post-Gx high-FA) provided relatively unbiased PDFF estimates overall and in the low-PDFF range, with regression slopes close to 1 and intercepts and biases close to zero. Pre-Gx high-FA MRI overestimated PDFF in proportion to MRS-PDFF, with slopes of 0.72 (overall) and 0.63 (low-PDFF range). Based on regression bias closest to 0, the post-Gx high-FA sequence was the most accurate overall and in the low-PDFF range. This sequence provided statistically significant improvements in at least two regression parameters compared to every other sequence. CONCLUSION In patients undergoing Gx-enhanced MR exams, PDFF estimation accuracy of MRI-M can be improved by using high-FA on post-contrast images.
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Affiliation(s)
- Charlie C Park
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Gavin Hamilton
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Ajinkya Desai
- Department of Diagnostic and Interventional Radiology, Rochester General Hospital, Rochester, NY, USA
| | - Kevin A Zand
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center (SDSC), University of California, San Diego, La Jolla, CA, USA
| | - Jonathan C Hooker
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Eduardo Costa
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Elhamy Heba
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Lisa Clark
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Anthony Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center (SDSC), University of California, San Diego, La Jolla, CA, USA
| | - Rohit Loomba
- Division of Gastroenterology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
- Division of Epidemiology, Department of Family Medicine and Preventive Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Michael S Middleton
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA
| | - Claude B Sirlin
- MR3T Bydder Laboratory, Liver Imaging Group, Department of Radiology, University of California, San Diego, 408 Dickinson Street, MC 8226, San Diego, CA, 92103-8226, USA.
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Haufe WM, Wolfson T, Hooker CA, Hooker JC, Covarrubias Y, Schlein AN, Hamilton G, Middleton MS, Angeles JE, Hernando D, Reeder SB, Schwimmer JB, Sirlin CB. Accuracy of PDFF estimation by magnitude-based and complex-based MRI in children with MR spectroscopy as a reference. J Magn Reson Imaging 2017; 46:1641-1647. [PMID: 28323377 DOI: 10.1002/jmri.25699] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 02/21/2017] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To assess and compare the accuracy of magnitude-based magnetic resonance imaging (MRI-M) and complex-based MRI (MRI-C) for estimating hepatic proton density fat fraction (PDFF) in children, using MR spectroscopy (MRS) as the reference standard. A secondary aim was to assess the agreement between MRI-M and MRI-C. MATERIALS AND METHODS This was a HIPAA-compliant, retrospective analysis of data collected in children enrolled in prospective, Institutional Review Board (IRB)-approved studies between 2012 and 2014. Informed consent was obtained from 200 children (ages 8-19 years) who subsequently underwent 3T MR exams that included MRI-M, MRI-C, and T1 -independent, T2 -corrected, single-voxel stimulated echo acquisition mode (STEAM) MRS. Both MRI methods acquired six echoes at low flip angles. T2*-corrected PDFF parametric maps were generated. PDFF values were recorded from regions of interest (ROIs) drawn on the maps in each of the nine Couinaud segments and three ROIs colocalized to the MRS voxel location. Regression analyses assessing agreement with MRS were performed to evaluate the accuracy of each MRI method, and Bland-Altman and intraclass correlation coefficient (ICC) analyses were performed to assess agreement between the MRI methods. RESULTS MRI-M and MRI-C PDFF were accurate relative to the colocalized MRS reference standard, with regression intercepts of 0.63% and -0.07%, slopes of 0.998 and 0.975, and proportion-of-explained-variance values (R2 ) of 0.982 and 0.979, respectively. For individual Couinaud segments and for the whole liver averages, Bland-Altman biases between MRI-M and MRI-C were small (ranging from 0.04 to 1.11%) and ICCs were high (≥0.978). CONCLUSION Both MRI-M and MRI-C accurately estimated hepatic PDFF in children, and high intermethod agreement was observed. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1641-1647.
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Affiliation(s)
- William M Haufe
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California - San Diego, San Diego, California, USA
| | - Catherine A Hooker
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Yesenia Covarrubias
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Alex N Schlein
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
| | - Jorge E Angeles
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California - San Diego, San Diego, California, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Medicine, University of Wisconsin - Madison, Madison, Wisconsin, USA.,Department of Emergency Medicine, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Jeffrey B Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California - San Diego, San Diego, California, USA.,Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California - San Diego, San Diego, California, USA
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Middleton MS, Haufe W, Hooker J, Borga M, Dahlqvist Leinhard O, Romu T, Tunón P, Hamilton G, Wolfson T, Gamst A, Loomba R, Sirlin CB. Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method. Radiology 2017; 283:438-449. [PMID: 28278002 DOI: 10.1148/radiol.2017160606] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Purpose To determine the repeatability and accuracy of a commercially available magnetic resonance (MR) imaging-based, semiautomated method to quantify abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction (PDFF). Materials and Methods This prospective study was institutional review board- approved and HIPAA compliant. All subjects provided written informed consent. Inclusion criteria were age of 18 years or older and willingness to participate. The exclusion criterion was contraindication to MR imaging. Three-dimensional T1-weighted dual-echo body-coil images were acquired three times. Source images were reconstructed to generate water and calibrated fat images. Abdominal adipose tissue and thigh muscle were segmented, and their volumes were estimated by using a semiautomated method and, as a reference standard, a manual method. Hepatic PDFF was estimated by using a confounder-corrected chemical shift-encoded MR imaging method with hybrid complex-magnitude reconstruction and, as a reference standard, MR spectroscopy. Tissue volume and hepatic PDFF intra- and interexamination repeatability were assessed by using intraclass correlation and coefficient of variation analysis. Tissue volume and hepatic PDFF accuracy were assessed by means of linear regression with the respective reference standards. Results Adipose and thigh muscle tissue volumes of 20 subjects (18 women; age range, 25-76 years; body mass index range, 19.3-43.9 kg/m2) were estimated by using the semiautomated method. Intra- and interexamination intraclass correlation coefficients were 0.996-0.998 and coefficients of variation were 1.5%-3.6%. For hepatic MR imaging PDFF, intra- and interexamination intraclass correlation coefficients were greater than or equal to 0.994 and coefficients of variation were less than or equal to 7.3%. In the regression analyses of manual versus semiautomated volume and spectroscopy versus MR imaging, PDFF slopes and intercepts were close to the identity line, and correlations of determination at multivariate analysis (R2) ranged from 0.744 to 0.994. Conclusion This MR imaging-based, semiautomated method provides high repeatability and accuracy for estimating abdominal adipose tissue and thigh muscle volumes and hepatic PDFF. © RSNA, 2017.
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Affiliation(s)
- Michael S Middleton
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - William Haufe
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Jonathan Hooker
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Magnus Borga
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Olof Dahlqvist Leinhard
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Thobias Romu
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Patrik Tunón
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Gavin Hamilton
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Tanya Wolfson
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Anthony Gamst
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Rohit Loomba
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Claude B Sirlin
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
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Manning PM, Hamilton G, Wang K, Park C, Hooker JC, Wolfson T, Gamst A, Haufe WM, Schlein AN, Middleton MS, Sirlin CB. Agreement between region-of-interest- and parametric map-based hepatic proton density fat fraction estimation in adults with chronic liver disease. Abdom Radiol (NY) 2017; 42:833-841. [PMID: 27688063 DOI: 10.1007/s00261-016-0925-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
PURPOSE To compare agreement between region-of-interest (ROI)- and parametric map-based methods of hepatic proton density fat fraction (PDFF) estimation in adults with known or suspected hepatic steatosis secondary to chronic liver disease over a range of imaging and analysis conditions. MATERIALS AND METHODS In this IRB approved HIPAA compliant prospective single-site study, 31 adults with chronic liver disease undergoing clinical gadoxetic acid-enhanced liver magnetic resonance imaging at 3 T were recruited. Multi-echo gradient-echo imaging at flip angles of 10° and 50° was performed before and after administration of gadoxetic acid. Six echoes were acquired at successive nominally out-of-phase and in-phase echo times. PDFF was estimated with a nonlinear fitting algorithm using the first two, three, four, five, and (all) six echoes. Hence, 20 different imaging and analysis conditions were used (pre/post contrast x low/high flip angle x 2/3/4/5/6 echoes). For each condition, PDFF estimation was done in corresponding liver locations using two methods: a region-of-interest (ROI)-based method in which mean signal intensity values within ROIs were run through the fitting algorithm, and a parametric map-based method in which individual signal intensities were run through the fitting algorithm pixel by pixel. Agreement between ROI- and map-based PDFF estimation was assessed by Bland-Altman and intraclass correlation (ICC) analysis. RESULTS Depending on the condition and method, PDFF ranged from -2.52% to 45.57%. Over all conditions, mean differences between ROI- and map-based PDFF estimates ranged from 0.04% to 0.24%, with all ICCs ≥0.999. CONCLUSION Agreement between ROI- and parametric map-based PDFF estimation is excellent over a wide range of imaging and analysis conditions.
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Affiliation(s)
- Paul M Manning
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA.
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
| | - Kang Wang
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
| | - Chulhyun Park
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), SDSC, University of California, San Diego, La Jolla, CA, USA
| | - Anthony Gamst
- Computational and Applied Statistics Laboratory (CASL), SDSC, University of California, San Diego, La Jolla, CA, USA
| | - William M Haufe
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
| | - Alex N Schlein
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 408 Dickinson Street, San Diego, CA, 92103-8226, USA
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Manning P, Murphy P, Wang K, Hooker J, Wolfson T, Middleton MS, Newton KP, Behling C, Awai HI, Durelle J, Paiz MN, Angeles JE, De La Pena D, McCutchan JA, Schwimmer JB, Sirlin CB. Liver histology and diffusion-weighted MRI in children with nonalcoholic fatty liver disease: A MAGNET study. J Magn Reson Imaging 2017; 46:1149-1158. [PMID: 28225568 DOI: 10.1002/jmri.25663] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Accepted: 01/25/2017] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To determine potential associations between histologic features of pediatric nonalcoholic fatty liver disease (NAFLD) and estimated quantitative magnetic resonance diffusion-weighted imaging (DWI) parameters. MATERIALS AND METHODS This prospective, cross-sectional study was performed as part of the Magnetic Resonance Assessment Guiding NAFLD Evaluation and Treatment (MAGNET) ancillary study to the Nonalcoholic Steatohepatitis Clinical Research Network (NASH CRN). Sixty-four children underwent a 3T DWI scan (b-values: 0, 100, and 500 s/mm2 ) within 180 days of a clinical liver biopsy of the right hepatic lobe. Three parameters were estimated in the right hepatic lobe: apparent diffusion coefficient (ADC), diffusivity (D), and perfusion fraction (F); the first assuming exponential decay and the latter two assuming biexponential intravoxel incoherent motion. Grading and staging of liver histology were done using the NASH CRN scoring system. Associations between histologic scores and DWI-estimated parameters were tested using multivariate linear regression. RESULTS Estimated means ± standard deviations were: ADC: 1.3 (0.94-1.8) × 10-3 mm2 /s; D: 0.82 (0.56-1.0) × 10-3 mm2 /s; and F: 17 (6.0-28)%. Multivariate analyses showed ADC and D decreased with steatosis and F decreased with fibrosis (P < 0.05). Associations between DWI-estimated parameters and other histologic features were not significant: ADC: fibrosis (P = 0.12), lobular inflammation (P = 0.20), portal inflammation (P = 0.27), hepatocellular inflammation (P = 0.29), NASH (P = 0.30); D: fibrosis (P = 0.34), lobular inflammation (P = 0.84), portal inflammation (P = 0.76), hepatocellular inflammation (P = 0.38), NASH (P = 0.81); F: steatosis (P = 0.57), lobular inflammation (P = 0.22), portal inflammation (P = 0.42), hepatocellular inflammation (P = 0.59), NASH (P = 0.07). CONCLUSION In children with NAFLD, steatosis and fibrosis have independent effects on DWI-estimated parameters ADC, D, and F. Further research is needed to determine the underlying mechanisms and clinical implications of these effects. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1149-1158.
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Affiliation(s)
- Paul Manning
- Liver Imaging Group, Department of Radiology, University of California, San Diego, School of Medicine, San Diego, California, USA
| | - Paul Murphy
- Liver Imaging Group, Department of Radiology, University of California, San Diego, School of Medicine, San Diego, California, USA
| | - Kang Wang
- Liver Imaging Group, Department of Radiology, University of California, San Diego, School of Medicine, San Diego, California, USA
| | - Jonathan Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, School of Medicine, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), SDSC, University of California, San Diego, La Jolla, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, School of Medicine, San Diego, California, USA
| | - Kimberly P Newton
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Cynthia Behling
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Hannah I Awai
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Janis Durelle
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Melissa N Paiz
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Jorge E Angeles
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Diana De La Pena
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | | | - Jeffrey B Schwimmer
- Department of Pediatrics, UCSD and Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, School of Medicine, San Diego, California, USA
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Yu NY, Wolfson T, Middleton MS, Hamilton G, Gamst A, Angeles JE, Schwimmer JB, Sirlin CB. Bone marrow fat content is correlated with hepatic fat content in paediatric non-alcoholic fatty liver disease. Clin Radiol 2017; 72:425.e9-425.e14. [PMID: 28063601 DOI: 10.1016/j.crad.2016.11.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2016] [Revised: 10/03/2016] [Accepted: 11/21/2016] [Indexed: 10/20/2022]
Abstract
AIM To investigate the relationship between bone marrow fat content and hepatic fat content in children with known or suspected non-alcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS This was an institutional review board-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant, cross-sectional, prospective analysis of data collected between October 2010 to March 2013 in 125 children with known or suspected NAFLD. Written informed consent was obtained for same-day research magnetic resonance imaging (MRI) of the lumbar spine, liver, and abdominal adiposity. Lumbar spine bone marrow proton density fat fraction (PDFF) and hepatic PDFF were estimated using complex-based MRI (C-MRI) techniques and magnitude-based MRI (M-MRI), respectively. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SCAT) were quantified using high-resolution MRI. All images were acquired by two MRI technologists. Hepatic M-MRI images were analysed by an image analyst; all other images were analysed by a single investigator. The relationship between lumbar spine bone marrow PDFF and hepatic PDFF was assessed with and without adjusting for the presence of covariates using correlation and regression analysis. RESULTS Lumbar spine bone marrow PDFF was positively associated with hepatic PDFF in children with known or suspected NAFLD prior to adjusting for covariates (r=0.33, p=0.0002). Lumbar spine bone marrow PDFF was positively associated with hepatic PDFF in children with known or suspected NAFLD (r=0.24, p=0.0079) after adjusting for age, sex, body mass index z-score, VAT, and SCAT in a multivariable regression analysis. CONCLUSION Bone marrow fat content is positively associated with hepatic fat content in children with known or suspected NAFLD. Further research is needed to confirm these results and understand their clinical and biological implications.
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Affiliation(s)
- N Y Yu
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - T Wolfson
- Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, USA
| | - M S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - G Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - A Gamst
- Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, USA
| | - J E Angeles
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - J B Schwimmer
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, CA, USA; Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, CA, USA; Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, CA, USA
| | - C B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, CA, USA.
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Achmad E, Yokoo T, Hamilton G, Heba ER, Hooker JC, Changchien C, Schroeder M, Wolfson T, Gamst A, Schwimmer JB, Lavine JE, Sirlin CB, Middleton MS. Feasibility of and agreement between MR imaging and spectroscopic estimation of hepatic proton density fat fraction in children with known or suspected nonalcoholic fatty liver disease. ACTA ACUST UNITED AC 2016. [PMID: 26205992 DOI: 10.1007/s00261-015-0506-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE To assess feasibility of and agreement between magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) for estimating hepatic proton density fat fraction (PDFF) in children with known or suspected nonalcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS Children were included in this study from two previous research studies in each of which three MRI and three MRS acquisitions were obtained. Sequence acceptability, and MRI- and MRS-estimated PDFF were evaluated. Agreement of MRI- with MRS-estimated hepatic PDFF was assessed by linear regression and Bland-Altman analysis. Age, sex, BMI-Z score, acquisition time, and artifact score effects on MRI- and MRS-estimated PDFF agreement were assessed by multiple linear regression. RESULTS Eighty-six children (61 boys and 25 girls) were included in this study. Slope and intercept from regressing MRS-PDFF on MRI-PDFF were 0.969 and 1.591%, respectively, and the Bland-Altman bias and 95% limits of agreement were 1.17% ± 2.61%. MRI motion artifact score was higher in boys than girls (by 0.21, p = 0.021). Higher BMI-Z score was associated with lower agreement between MRS and MRI (p = 0.045). CONCLUSION Hepatic PDFF estimation by both MRI and MRS is feasible, and MRI- and MRS-estimated PDFF agree closely in children with known or suspected NAFLD.
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Affiliation(s)
- Emil Achmad
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
| | - Takeshi Yokoo
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern School of Medicine, Dallas, TX, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
| | - Elhamy R Heba
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
| | - Christopher Changchien
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
| | - Michael Schroeder
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California, San Diego, San Diego, CA, USA
| | - Anthony Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California, San Diego, San Diego, CA, USA
| | - Jeffrey B Schwimmer
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of Medicine, University of California, San Diego, San Diego, CA, USA
- Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, CA, USA
| | - Joel E Lavine
- Department of Pediatrics, Columbia University, New York, NY, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, School of Medicine, University of California, San Diego, San Diego, CA, USA.
- UCSD Department of Radiology, UCSD MRI Institute, 410 West Dickinson Street, San Diego, CA, 92103-8749, USA.
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Hamilton G, Schlein AN, Middleton MS, Hooker CA, Wolfson T, Gamst AC, Loomba R, Sirlin CB. In vivo triglyceride composition of abdominal adipose tissue measured by 1 H MRS at 3T. J Magn Reson Imaging 2016; 45:1455-1463. [PMID: 27571403 DOI: 10.1002/jmri.25453] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 08/16/2016] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To investigate the regional variability of adipose tissue triglyceride composition in vivo using 1 H MRS, examining potential confounders and corrections for artifacts, to allow for adipose tissue spectrum estimation. MATERIALS AND METHODS 1 H magnetic resonance (MR) stimulated echo acquisition mode (STEAM) spectra were acquired in vivo at 3T from 340 adult patients (mean age 48.9 years, range 21-79 years; 172 males, 168 females; mean body mass index [BMI] 34.0, range 22-49 kg/m2 ) with known or suspected nonalcoholic fatty liver disease (NAFLD) in deep (dSCAT), surface (sSCAT) subcutaneous adipose tissue, and visceral adipose tissue (VAT). Triglyceride composition was characterized by the number of double bonds (ndb) and number of methylene-interrupted double bonds (nmidb). A subset of patients (dSCAT n = 80, sSCAT n = 55, VAT n = 194) had the acquisition repeated three times to examine the repeatability of ndb and nmidb estimation. RESULTS Mean ndb and nmidb showed significant (P < 0.0001) differences between depots except for dSCAT and sSCAT nmidb (dSCAT ndb 2.797, nmidb 0.745; sSCAT ndb 2.826, nmidb 0.737; VAT ndb 2.723, nmidb 0.687). All ndb and nmidb estimates were highly repeatable (VAT ndb ICC = 0.888, nmidb ICC = 0.853; sSCAT: ndb ICC = 0.974, nmidb ICC = 0.964; dSCAT: ndb ICC = 0.959, nmidb ICC = 0.948). CONCLUSION Adipose tissue composition can be estimated repeatably using 1 H MRS and different fat depots have different triglyceride compositions. LEVEL OF EVIDENCE 2 J. MAGN. RESON. IMAGING 2017;45:1455-1463.
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Affiliation(s)
- Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Alexandra N Schlein
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Catherine A Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Lab, San Diego Supercomputing Center, San Diego, California, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Lab, San Diego Supercomputing Center, San Diego, California, USA
| | - Rohit Loomba
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.,NAFLD Translational Research Unit, Division of Gastroenterology, Department of Medicine, University of California, San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
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McClellan TR, Motosugi U, Middleton MS, Allen BC, Jaffe TA, Miller CM, Reeder SB, Sirlin CB, Bashir MR. Intravenous Gadoxetate Disodium Administration Reduces Breath-holding Capacity in the Hepatic Arterial Phase: A Multi-Center Randomized Placebo-controlled Trial. Radiology 2016; 282:361-368. [PMID: 27509544 DOI: 10.1148/radiol.2016160482] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Purpose To determine, in a multicenter double-blinded placebo-controlled trial, whether maximal hepatic arterial phase breath-holding duration is affected by gadoxetate disodium administration. Materials and Methods Institutional review board approval was obtained for this prospective multi-institutional HIPAA-compliant study; written informed consent was obtained from all subjects. At three sites, a total of 44 volunteers underwent a magnetic resonance (MR) imaging examination in which images were acquired before and dynamically after bolus injection of gadoxetate disodium, normal saline, and gadoterate meglumine, administered in random order in a single session. The technologist and volunteer were blinded to the agent. Arterial phase breath-holding duration was timed after each injection, and volunteers reported subjective symptoms. Heart rate (HR) and oxygen saturation were monitored. Images were independently analyzed for motion artifacts by three radiologists. Arterial phase breath-holding duration and motion artifacts after each agent were compared by using the Mann-Whitney U test and the McNemar test. Factors affecting the above outcomes were assessed by using a univariate, multivariable model. Results Arterial phase breath holds were shorter after gadoxetate disodium (mean, 32 seconds ± 19) than after saline (mean, 40 seconds ± 17; P < .001) or gadoterate meglumine (43 seconds ± 21, P < .001) administration. In 80% (35 of 44) of subjects, arterial phase breath holds were shorter after gadoxetate disodium than after both saline and gadoterate meglumine. Three (7%) of 44 volunteers had severe arterial phase motion artifacts after gadoxetate disodium administration, one (2%; P = .62) had them after gadoterate meglumine administration, and none (P = .25) had them after saline administration. HR and oxygen saturation changes were not significantly associated with contrast agent. Conclusion Maximal hepatic arterial phase breath-holding duration is reduced after gadoxetate disodium administration in healthy volunteers, and reduced breath-holding duration is associated with motion artifacts. © RSNA, 2016.
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Affiliation(s)
- Taylor R McClellan
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Utaroh Motosugi
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Michael S Middleton
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Brian C Allen
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Tracy A Jaffe
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Chad M Miller
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Scott B Reeder
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Claude B Sirlin
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
| | - Mustafa R Bashir
- From the Department of Radiology (T.R.M., B.C.A., T.A.J., C.M.M., M.R.B.) and Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University Medical Center, DUMC 3808, Durham, NC 27710; Departments of Radiology (U.M., S.B.R.), Medical Physics (S.B.R.), Biomedical Engineering (S.B.R.), Medicine (S.B.R.), and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; and Liver Imaging Group, Department of Radiology, University of California-San Diego, San Diego, Calif (M.S.M., C.B.S.)
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Tanabe M, Kanki A, Wolfson T, Costa EAC, Mamidipalli A, Ferreira MPFD, Santillan C, Middleton MS, Gamst AC, Kono Y, Kuo A, Sirlin CB. Imaging Outcomes of Liver Imaging Reporting and Data System Version 2014 Category 2, 3, and 4 Observations Detected at CT and MR Imaging. Radiology 2016; 281:129-39. [PMID: 27115054 DOI: 10.1148/radiol.2016152173] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To determine the proportion of untreated Liver Imaging Reporting and Data System (LI-RADS) version 2014 category 2, 3, and 4 observations that progress, remain stable, or decrease in category and to compare the cumulative incidence of progression in category. Materials and Methods In this retrospective, longitudinal, single-center, HIPAA-compliant, institutional review board-approved study, 157 patients (86 men and 71 women; mean age ± standard deviation, 59.0 years ± 9.7) underwent two or more multiphasic computed tomographic (CT) or magnetic resonance (MR) imaging examinations for hepatocellular carcinoma surveillance, with the first examination in 2011 or 2012. One radiologist reviewed baseline and follow-up CT and MR images (mean follow-up, 614 days). LI-RADS categories issued in the clinical reports by using version 1.0 or version 2013 were converted to version 2014 retrospectively; category modifications were verified with another radiologist. For index category LR-2, LR-3, and LR-4 observations, the proportions that progressed, remained stable, or decreased in category were calculated. Cumulative incidence curves for progression were compared according to baseline LI-RADS category (by using log-rank tests). Results All 63 index LR-2 observations remained stable or decreased in category. Among 166 index LR-3 observations, seven (4%) progressed to LR-5, and eight (5%) progressed to LR-4. Among 52 index LR-4 observations, 20 (38%) progressed to a malignant category. The cumulative incidence of progression to a malignant category was higher for index LR-4 observations than for index LR-3 or LR-2 observations (each P < .001) but was not different between LR-3 and LR-2 observations (P = .155). The cumulative incidence of progression to at least category LR-4 was trend-level higher for index LR-3 observations than for LR-2 observations (P = .0502). Conclusion Observations classified according to LI-RADS version 2014 categories are associated with different imaging outcomes. (©) RSNA, 2016 Online supplemental material is available for this article.
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Affiliation(s)
- Masahiro Tanabe
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Akihiko Kanki
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Tanya Wolfson
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Eduardo A C Costa
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Adrija Mamidipalli
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Marilia P F D Ferreira
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Cynthia Santillan
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Michael S Middleton
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Anthony C Gamst
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Yuko Kono
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Alexander Kuo
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Claude B Sirlin
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
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Tang A, Chen J, Le TA, Changchien C, Hamilton G, Middleton MS, Loomba R, Sirlin CB. Cross-sectional and longitudinal evaluation of liver volume and total liver fat burden in adults with nonalcoholic steatohepatitis. ACTA ACUST UNITED AC 2015; 40:26-37. [PMID: 25015398 DOI: 10.1007/s00261-014-0175-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
PURPOSE To explore the cross-sectional and longitudinal relationships between fractional liver fat content, liver volume, and total liver fat burden. METHODS In 43 adults with non-alcoholic steatohepatitis participating in a clinical trial, liver volume was estimated by segmentation of magnitude-based low-flip-angle multiecho GRE images. The liver mean proton density fat fraction (PDFF) was calculated. The total liver fat index (TLFI) was estimated as the product of liver mean PDFF and liver volume. Linear regression analyses were performed. RESULTS Cross-sectional analyses revealed statistically significant relationships between TLFI and liver mean PDFF (R 2 = 0.740 baseline/0.791 follow-up, P < 0.001 baseline/P < 0.001 follow-up), and between TLFI and liver volume (R 2 = 0.352/0.452, P < 0.001/< 0.001). Longitudinal analyses revealed statistically significant relationships between liver volume change and liver mean PDFF change (R 2 = 0.556, P < 0.001), between TLFI change and liver mean PDFF change (R 2 = 0.920, P < 0.001), and between TLFI change and liver volume change (R 2 = 0.735, P < 0.001). CONCLUSION Liver segmentation in combination with MRI-based PDFF estimation may be used to monitor liver volume, liver mean PDFF, and TLFI in a clinical trial.
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Heba ER, Desai A, Zand KA, Hamilton G, Wolfson T, Schlein AN, Gamst A, Loomba R, Sirlin CB, Middleton MS. Accuracy and the effect of possible subject-based confounders of magnitude-based MRI for estimating hepatic proton density fat fraction in adults, using MR spectroscopy as reference. J Magn Reson Imaging 2015. [PMID: 26201284 DOI: 10.1002/jmri.25006] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To determine the accuracy and the effect of possible subject-based confounders of magnitude-based magnetic resonance imaging (MRI) for estimating hepatic proton density fat fraction (PDFF) for different numbers of echoes in adults with known or suspected nonalcoholic fatty liver disease, using MR spectroscopy (MRS) as a reference. MATERIALS AND METHODS In this retrospective analysis of 506 adults, hepatic PDFF was estimated by unenhanced 3.0T MRI, using right-lobe MRS as reference. Regions of interest placed on source images and on six-echo parametric PDFF maps were colocalized to MRS voxel location. Accuracy using different numbers of echoes was assessed by regression and Bland-Altman analysis; slope, intercept, average bias, and R2 were calculated. The effect of age, sex, and body mass index (BMI) on hepatic PDFF accuracy was investigated using multivariate linear regression analyses. RESULTS MRI closely agreed with MRS for all tested methods. For three- to six-echo methods, slope, regression intercept, average bias, and R2 were 1.01-0.99, 0.11-0.62%, 0.24-0.56%, and 0.981-0.982, respectively. Slope was closest to unity for the five-echo method. The two-echo method was least accurate, underestimating PDFF by an average of 2.93%, compared to an average of 0.23-0.69% for the other methods. Statistically significant but clinically nonmeaningful effects on PDFF error were found for subject BMI (P range: 0.0016 to 0.0783), male sex (P range: 0.015 to 0.037), and no statistically significant effect was found for subject age (P range: 0.18-0.24). CONCLUSION Hepatic magnitude-based MRI PDFF estimates using three, four, five, and six echoes, and six-echo parametric maps are accurate compared to reference MRS values, and that accuracy is not meaningfully confounded by age, sex, or BMI.
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Affiliation(s)
- Elhamy R Heba
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Ajinkya Desai
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Kevin A Zand
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California, San Diego, San Diego, California, USA
| | - Alexandra N Schlein
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Anthony Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California, San Diego, San Diego, California, USA
| | - Rohit Loomba
- Department of Medicine (Division of Gastroenterology and Hepatology), University of California, San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
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Hamilton G, Middleton MS, Hooker JC, Haufe WM, Forbang NI, Allison MA, Loomba R, Sirlin CB. In vivo breath-hold (1) H MRS simultaneous estimation of liver proton density fat fraction, and T1 and T2 of water and fat, with a multi-TR, multi-TE sequence. J Magn Reson Imaging 2015; 42:1538-43. [PMID: 26114603 DOI: 10.1002/jmri.24946] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 04/24/2015] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To examine the intra-examination repeatability of proton density fat fraction (PDFF) and T1 and T2 of liver water and fat as estimated by a novel multi-repetition time (TR)-echo time (TE) (1) H magnetic resonance spectroscopy (MRS)-stimulated echo acquisition mode (STEAM) sequence that acquires 32 spectra for a range of TRs and TEs in single breath-hold. MATERIALS AND METHODS Sixty-seven subjects undergoing liver MRI examinations at 3T had three multi-TR-TE sequences acquired consecutively in a single session. This sequence was designed to allow accurate estimation of T1 and T2 of both water and fat, as well as PDFF, in a single breath-hold. A standard long-TR, multi-TE sequence was also acquired to allow comparison of estimated PDFF. Regression and interclass correlation (ICC) analyses were performed. RESULTS There was strong agreement between PDFF estimated by the multi-TR-TE and long-TR, multi-TE sequences (slope 0.997; intercept -0.03; R = 0.997). The multi-TR-TE sequence had high repeatability for estimating PDFF (ICC = 0.999), water T2 (ICC = 0.920), water T1 (ICC = 0.845), and fat T2 (ICC = 0.760), and moderate repeatability for estimating fat T1 (ICC = 0.556). CONCLUSION A novel multi-TR-TE sequence can estimate PDFF and water and fat T1 and T2 in a single breath-hold. Refinement may be needed to improve repeatability for fat T1 estimation.
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Affiliation(s)
- Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - William M Haufe
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Nketi I Forbang
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA
| | - Matthew A Allison
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA
| | - Rohit Loomba
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.,NAFLD Translational Research Unit, Division of Gastroenterology, Department of Medicine, University of California, San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
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Schwimmer JB, Middleton MS, Behling C, Newton KP, Awai HI, Paiz MN, Lam J, Hooker JC, Hamilton G, Fontanesi J, Sirlin CB. Magnetic resonance imaging and liver histology as biomarkers of hepatic steatosis in children with nonalcoholic fatty liver disease. Hepatology 2015; 61:1887-95. [PMID: 25529941 PMCID: PMC4670559 DOI: 10.1002/hep.27666] [Citation(s) in RCA: 121] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2014] [Accepted: 12/13/2014] [Indexed: 12/12/2022]
Abstract
UNLABELLED Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children. In order to advance the field of NAFLD, noninvasive imaging methods for measuring liver fat are needed. Advanced magnetic resonance imaging (MRI) has shown great promise for the quantitative assessment of hepatic steatosis but has not been validated in children. Therefore, this study was designed to evaluate the correlation and diagnostic accuracy of MRI-estimated liver proton density fat fraction (PDFF), a biomarker for hepatic steatosis, compared to histologic steatosis grade in children. The study included 174 children with a mean age of 14.0 years. Liver PDFF estimated by MRI was significantly (P < 0.01) correlated (0.725) with steatosis grade. The correlation of MRI-estimated liver PDFF and steatosis grade was influenced by both sex and fibrosis stage. The correlation was significantly (P < 0.01) stronger in girls (0.86) than in boys (0.70). The correlation was significantly (P < 0.01) weaker in children with stage 2-4 fibrosis (0.61) than children with no fibrosis (0.76) or stage 1 fibrosis (0.78). The diagnostic accuracy of commonly used threshold values to distinguish between no steatosis and mild steatosis ranged from 0.69 to 0.82. The overall accuracy of predicting the histologic steatosis grade from MRI-estimated liver PDFF was 56%. No single threshold had sufficient sensitivity and specificity to be considered diagnostic for an individual child. CONCLUSIONS Advanced magnitude-based MRI can be used to estimate liver PDFF in children, and those PDFF values correlate well with steatosis grade by liver histology. Thus, magnitude-based MRI has the potential for clinical utility in the evaluation of NAFLD, but at this time no single threshold value has sufficient accuracy to be considered diagnostic for an individual child.
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Affiliation(s)
- Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California,Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Cynthia Behling
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Pathology, Sharp Medical Center, San Diego, California
| | - Kimberly P. Newton
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Hannah I. Awai
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California,Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Melissa N. Paiz
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Jessica Lam
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California,School of Medicine, Loma Linda University, Loma Linda, California
| | - Jonathan C. Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - John Fontanesi
- Center for Management Science in Health, Division of General Internal Medicine, Department of Medicine, University of California, San Diego School of Medicine, La Jolla, California,Department of Family and Preventive Medicine, University of California, San Diego School of Medicine, La Jolla, California,Department of Pediatrics, University of California, San Diego School of Medicine, La Jolla, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
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Costa EAC, Cunha GM, Smorodinsky E, Cruite I, Tang A, Marks RM, Clark L, Wolfson T, Gamst A, Sicklick JK, Hemming A, Peterson MR, Middleton MS, Sirlin CB. Diagnostic Accuracy of Preoperative Gadoxetic Acid-enhanced 3-T MR Imaging for Malignant Liver Lesions by Using Ex Vivo MR Imaging-matched Pathologic Findings as the Reference Standard. Radiology 2015; 276:775-86. [PMID: 25875972 DOI: 10.1148/radiol.2015142069] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
PURPOSE To determine per-lesion sensitivity and positive predictive value (PPV) of gadoxetic acid-enhanced 3-T magnetic resonance (MR) imaging for the diagnosis of malignant lesions by using matched (spatially correlated) hepatectomy pathologic findings as the reference standard. Materials and METHODS In this prospective, institutional review board-approved, HIPAA-compliant study, 20 patients (nine men, 11 women; mean age, 59 years) with malignant liver lesions who gave written informed consent underwent preoperative gadoxetic acid-enhanced 3-T MR imaging for surgical planning. Two image sets were independently analyzed by three readers to detect liver lesions (set 1 without and set 2 with hepatobiliary phase [HBP] images). Hepatectomy specimen ex vivo MR imaging assisted in matching gadoxetic acid-enhanced 3-T MR imaging findings with pathologic findings. Interreader agreement was assessed by using the Cohen κ coefficient. Per-lesion sensitivity and PPV were calculated. RESULTS Cohen κ values were 0.64-0.76 and 0.57-0.84, and overall per-lesion sensitivity was 45% (42 of 94 lesions) to 56% (53 of 94 lesions) and 58% (55 of 94 lesions) to 64% (60 of 94 lesions) for sets 1 and 2, respectively. The addition of HBP imaging did not affect interreader agreement but significantly improved overall sensitivity for one reader (P < .05) and almost for another (P = .05). Sensitivity for 0.2-0.5-cm lesions was 0% (0 of 26 lesions) to 8% (two of 26 lesions) for set 1 and 4% (one of 26 lesions) to 12% (three of 26 lesions) for set 2. Sensitivity for 0.6-1.0-cm lesions was 28% (nine of 32 lesions) to 59% (19 of 32 lesions) for set 1 and 66% (21 of 32 lesions) to 69% (22 of 32 lesions) for set 2. Sensitivity for lesions at least 1.0 cm in diameter was at least 81% (13 of 16 lesions) for set 1 and was not improved for set 2. PPV was 98% (56 of 57 lesions) to 100% (60 of 60 lesions) for all readers without differences between image sets or lesion size. CONCLUSION Gadoxetic acid-enhanced 3-T MR imaging provides high per-lesion sensitivity and PPV for preoperative malignant liver lesion detection overall, although sensitivity for 0.2-0.5-cm malignant lesions is poor.
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Affiliation(s)
- Eduardo A C Costa
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Guilherme M Cunha
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Emmanuil Smorodinsky
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Irene Cruite
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - An Tang
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Robert M Marks
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Lisa Clark
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Tanya Wolfson
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Anthony Gamst
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Jason K Sicklick
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Alan Hemming
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Michael R Peterson
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Michael S Middleton
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
| | - Claude B Sirlin
- From the Liver Imaging Group, Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226 (E.A.C.C., G.M.C., E.S., I.C., A.T., R.M.M., L.C., M.S.M., C.B.S.); Department of Radiology, Naval Medical Center San Diego, San Diego, Calif (R.M.M.); Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California-San Diego, San Diego, Calif (T.W., A.G.); Department of Surgery and Moores Cancer Center, University of California-San Diego, San Diego, Calif (J.K.S., A.H.); and Western Washington Pathology and Multicare Health System, Tacoma, Wash (M.R.P.)
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Zand KA, Shah A, Heba E, Wolfson T, Hamilton G, Lam J, Chen J, Hooker JC, Gamst AC, Middleton MS, Schwimmer JB, Sirlin CB. Accuracy of multiecho magnitude-based MRI (M-MRI) for estimation of hepatic proton density fat fraction (PDFF) in children. J Magn Reson Imaging 2015; 42:1223-32. [PMID: 25847512 DOI: 10.1002/jmri.24888] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Accepted: 03/02/2015] [Indexed: 01/28/2023] Open
Abstract
PURPOSE To assess accuracy of magnitude-based magnetic resonance imaging (M-MRI) in children to estimate hepatic proton density fat fraction (PDFF) using two to six echoes, with magnetic resonance spectroscopy (MRS) -measured PDFF as a reference standard. METHODS This was an IRB-approved, HIPAA-compliant, single-center, cross-sectional, retrospective analysis of data collected prospectively between 2008 and 2013 in children with known or suspected nonalcoholic fatty liver disease (NAFLD). Two hundred eighty-six children (8-20 [mean 14.2 ± 2.5] years; 182 boys) underwent same-day MRS and M-MRI. Unenhanced two-dimensional axial spoiled gradient-recalled-echo images at six echo times were obtained at 3T after a single low-flip-angle (10°) excitation with ≥ 120-ms recovery time. Hepatic PDFF was estimated using the first two, three, four, five, and all six echoes. For each number of echoes, accuracy of M-MRI to estimate PDFF was assessed by linear regression with MRS-PDFF as reference standard. Accuracy metrics were regression intercept, slope, average bias, and R(2) . RESULTS MRS-PDFF ranged from 0.2-40.4% (mean 13.1 ± 9.8%). Using three to six echoes, regression intercept, slope, and average bias were 0.46-0.96%, 0.99-1.01, and 0.57-0.89%, respectively. Using two echoes, these values were 2.98%, 0.97, and 2.72%, respectively. R(2) ranged 0.98-0.99 for all methods. CONCLUSION Using three to six echoes, M-MRI has high accuracy for hepatic PDFF estimation in children.
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Affiliation(s)
- Kevin A Zand
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Amol Shah
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Elhamy Heba
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, Division of Biostatistics and Informatics, University of California, San Diego, California, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Jessica Lam
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Joshua Chen
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory, Division of Biostatistics and Informatics, University of California, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Jeffrey B Schwimmer
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA.,Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego, California, USA.,Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
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Tang A, Desai A, Hamilton G, Wolfson T, Gamst A, Lam J, Clark L, Hooker J, Chavez T, Ang BD, Middleton MS, Peterson M, Loomba R, Sirlin CB. Accuracy of MR imaging-estimated proton density fat fraction for classification of dichotomized histologic steatosis grades in nonalcoholic fatty liver disease. Radiology 2014; 274:416-25. [PMID: 25247408 DOI: 10.1148/radiol.14140754] [Citation(s) in RCA: 207] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
PURPOSE To evaluate the diagnostic performance of previously proposed high-specificity magnetic resonance (MR) imaging-estimated proton density fat fraction (PDFF) thresholds for diagnosis of steatosis grade 1 or higher (PDFF threshold of 6.4%), grade 2 or higher (PDFF threshold of 17.4%), and grade 3 (PDFF threshold of 22.1%) by using histologic findings as a reference in an independent cohort of adults known to have or suspected of having nonalcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS This prospective, cross-sectional, institutional review board-approved, HIPAA-compliant single-center study was conducted in an independent cohort of 89 adults known to have or suspected of having NAFLD who underwent contemporaneous liver biopsy. MR imaging PDFF was estimated at 3 T by using magnitude-based low-flip-angle multiecho gradient-recalled-echo imaging with T2* correction and multipeak modeling. Steatosis was graded histologically (grades 0, 1, 2, and 3, according to the Nonalcoholic Steatohepatitis Clinical Research Network scoring system). Sensitivity, specificity, and binomial confidence intervals were calculated for the proposed MR imaging PDFF thresholds. RESULTS The proposed MR imaging PDFF threshold of 6.4% to diagnose grade 1 or higher steatosis had 86% sensitivity (71 of 83 patients; 95% confidence interval [CI]: 76, 92) and 83% specificity (five of six patients; 95% CI: 36, 100). The threshold of 17.4% to diagnose grade 2 or higher steatosis had 64% sensitivity (28 of 44 patients; 95% CI: 48, 78) and 96% specificity (43 of 45 patients; 95% CI: 85, 100). The threshold of 22.1% to diagnose grade 3 steatosis had 71% sensitivity (10 of 14 patients; 95% CI: 42, 92) and 92% specificity (69 of 75 patients; 95% CI: 83, 97). CONCLUSION In an independent cohort of adults known to have or suspected of having NAFLD, the previously proposed MR imaging PDFF thresholds provided moderate to high sensitivity and high specificity for diagnosis of grade 1 or higher, grade 2 or higher, and grade 3 steatosis. Prospective multicenter studies are now needed to further validate these high-specificity thresholds.
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Affiliation(s)
- An Tang
- From the Liver Imaging Group, Department of Radiology (A.T., A.D., G.H., J.L., L.C., J.H., T.C., M.S.M., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.G.), Department of Pathology (M.P.), and Department of Medicine, Division of Gastroenterology (B.D.A., R.L.), University of California San Diego, 408 Dickinson St, San Diego, CA 92103-8226
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Abstract
This article describes the rationale and indications for breast implant-related magnetic resonance (MR) imaging, alone or in combination with breast cancer-related MR imaging. Basic silicone chemistry, implant styles, and normal appearances of breast implants are described. The various presentations of breast implant rupture are described, and a 4-point staging scheme for intracapsular rupture is reviewed. Finally, a discussion of what the reviewing physician needs to know is presented, both before breast implant MR examinations are requested and afterward, when results are reported.
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Affiliation(s)
- Michael S Middleton
- Department of Radiology, UCSD School of Medicine, 410 West Dickinson Street, San Diego, CA 92103-8749, USA.
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