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Kim W, Hwang JA, Min JH, Lee S, Lee JE, Shin J, Jeong WK. Exploring the impact of excluding intrahepatic segmental vessels on liver stiffness measurement and advanced fibrosis diagnosis using magnetic resonance elastography. Acta Radiol 2024:2841851241263335. [PMID: 39033394 DOI: 10.1177/02841851241263335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
BACKGROUND The impact of excluding intrahepatic segmental vessels from regions of interest (ROIs) on liver stiffness measurement (LSM) via magnetic resonance elastography (MRE) remains uncertain. PURPOSE To determine the effect of excluding intrahepatic segmental vessels from ROIs on LSM obtained from MRE. MATERIAL AND METHODS This retrospective analysis included 95 participants who underwent successful two-dimensional gradient recalled-echo MRE before hepatic tumor resection (n = 49) or living liver donation (n = 46). The conventional LSM was determined by manually drawing ROIs on the elastogram within the 95% confidence region, staying 1 cm within the liver capsule and excluding large hilar vessels, the gallbladder, hepatic lesions, and artifacts. In addition, the modified LSM was determined by excluding intrahepatic segmental vessels. LSMs obtained by the two methods were compared with paired sample signed-rank test. Diagnostic performance for advanced fibrosis was calculated and compared using McNemar's test and Delong's test. The stage of hepatic fibrosis was assessed using surgical specimens by the METAVIR system. RESULTS The modified LSM was larger than the conventional LSM (2.4 kPa vs. 2.2 kPa in reader 1; 2.7 kPa vs. 2.4 kPa in reader 2; P < 0.001). The modified LSM showed superior sensitivity (0.841 vs. 0.659 in reader 1; 0.864 vs. 0.705 in reader 2; P < 0.05) and area under the curve (0.901 vs. 0.820 in reader 1; 0.912 vs. 0.843 in reader 2; P < 0.05) for detecting advanced fibrosis (≥F3) than conventional LSM. CONCLUSION The exclusion of intrahepatic segmental vessels from ROIs in MRE affected the LSM and enhanced diagnostic performance for advanced fibrosis.
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Affiliation(s)
- Wook Kim
- Department of Radiology and Center for Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeong Ah Hwang
- Department of Radiology and Center for Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Ji Hye Min
- Department of Radiology and Center for Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sunyoung Lee
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ji Eun Lee
- Department of Radiology, Soonchunhyang University College of Medicine, Bucheon Hospital, Bucheon, Republic of Korea
| | - Jaeseung Shin
- Department of Radiology and Center for Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Zerunian M, Masci B, Caruso D, Pucciarelli F, Polici M, Nardacci S, De Santis D, Iannicelli E, Laghi A. Liver Magnetic Resonance Elastography: Focus on Methodology, Technique, and Feasibility. Diagnostics (Basel) 2024; 14:379. [PMID: 38396418 PMCID: PMC10887609 DOI: 10.3390/diagnostics14040379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
Magnetic resonance elastography (MRE) is an imaging technique that combines low-frequency mechanical vibrations with magnetic resonance imaging to create visual maps and quantify liver parenchyma stiffness. As in recent years, diffuse liver diseases have become highly prevalent worldwide and could lead to a chronic condition with different stages of fibrosis. There is a strong necessity for a non-invasive, highly accurate, and standardised quantitative assessment to evaluate and manage patients with different stages of fibrosis from diagnosis to follow-up, as the actual reference standard for the diagnosis and staging of liver fibrosis is biopsy, an invasive method with possible peri-procedural complications and sampling errors. MRE could quantitatively evaluate liver stiffness, as it is a rapid and repeatable method with high specificity and sensitivity. MRE is based on the propagation of mechanical shear waves through the liver tissue that are directly proportional to the organ's stiffness, expressed in kilopascals (kPa). To obtain a valid assessment of the real hepatic stiffness values, it is mandatory to obtain a high-quality examination. To understand the pearls and pitfalls of MRE, in this review, we describe our experience after one year of performing MRE from indications and patient preparation to acquisition, quality control, and image analysis.
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Affiliation(s)
- Marta Zerunian
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
- PhD School in Translational Medicine and Oncology, Department of Medical and Surgical Sciences and Translational Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Benedetta Masci
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Damiano Caruso
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Francesco Pucciarelli
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Michela Polici
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
- PhD School in Translational Medicine and Oncology, Department of Medical and Surgical Sciences and Translational Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, 00189 Rome, Italy
| | - Stefano Nardacci
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Domenico De Santis
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Elsa Iannicelli
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
| | - Andrea Laghi
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy; (M.Z.); (B.M.); (M.P.); (S.N.); (D.D.S.); (E.I.); (A.L.)
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Bhuiyan EH, Ozkaya E, Kennedy P, Del Hoyo JL, Achkar BE, Thung S, Lewis S, Bane O, Taouli B. Magnetic resonance elastography for noninvasive detection of liver fibrosis: is there an added value of 3D acquisition? Abdom Radiol (NY) 2023; 48:3420-3429. [PMID: 37700185 DOI: 10.1007/s00261-023-04036-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 08/22/2023] [Accepted: 08/24/2023] [Indexed: 09/14/2023]
Abstract
PURPOSE (1) Assess the diagnostic performance of liver 3D magnetic resonance elastography (MRE) parameters (including stiffness, storage/loss modulus and damping ratio) compared to liver stiffness measured with 2D MRE for noninvasive detection of advanced liver fibrosis (F3-F4) and cirrhosis (F4) in patients with chronic liver disease. (2) Assess the value of serum markers (FIB-4) in detecting advanced liver fibrosis and cirrhosis in the same patients. METHODS This was a single center, prospective IRB-approved cross-sectional study that included 49 patients (M/F: 23/26, mean age 50.8 y) with chronic liver disease and concomitant liver biopsy. MRE was acquired at 1.5T using a spin echo-EPI sequence. The following parameters were measured: liver stiffness using 2D MRE (LS-2D) and 3D MRE parameters (LS-3D, liver storage, loss modulus and damping ratio). The Mann-Whitney U test, ROC curve analysis, Spearman correlation and logistic regression were performed to evaluate diagnostic performance of MRE parameters and FIB-4. RESULTS LS-2D and LS-3D had similar diagnostic performance for diagnosis of F3-F4, with AUCs of 0.87 and 0.88, sensitivity of 0.71 and 0.81, specificity of 0.89 for both. For diagnosis of F4, LS-2D and LS-3D had similar performance with AUCs of 0.81 for both, sensitivity of 0.75 and 0.83, and specificity of 0.84 and 0.73, respectively. Additional 3D parameters (storage modulus, loss modulus, damping ratio) had variable performance, with AUC range of 0.59-0.78 for F3-F4; and 0.52-0.70 for F4. FIB-4 had lower diagnostic performance, with AUCs of 0.66 for F3-F4, and 0.68 for F4. CONCLUSION Our study shows no added value of 3D MRE compared to 2D MRE for detection of advanced fibrosis and cirrhosis, while FIB-4 had lower diagnostic performance.
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Affiliation(s)
- Enamul H Bhuiyan
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Efe Ozkaya
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paul Kennedy
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Juan Lloret Del Hoyo
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Bassam El Achkar
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Swan Thung
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Lewis
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bachir Taouli
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Guglielmo FF, Barr RG, Yokoo T, Ferraioli G, Lee JT, Dillman JR, Horowitz JM, Jhaveri KS, Miller FH, Modi RY, Mojtahed A, Ohliger MA, Pirasteh A, Reeder SB, Shanbhogue K, Silva AC, Smith EN, Surabhi VR, Taouli B, Welle CL, Yeh BM, Venkatesh SK. Liver Fibrosis, Fat, and Iron Evaluation with MRI and Fibrosis and Fat Evaluation with US: A Practical Guide for Radiologists. Radiographics 2023; 43:e220181. [PMID: 37227944 DOI: 10.1148/rg.220181] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Quantitative imaging biomarkers of liver disease measured by using MRI and US are emerging as important clinical tools in the management of patients with chronic liver disease (CLD). Because of their high accuracy and noninvasive nature, in many cases, these techniques have replaced liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. The most commonly evaluated imaging biomarkers are surrogates for liver fibrosis, fat, and iron. MR elastography is now routinely performed to evaluate for liver fibrosis and typically combined with MRI-based liver fat and iron quantification to exclude or grade hepatic steatosis and iron overload, respectively. US elastography is also widely performed to evaluate for liver fibrosis and has the advantage of lower equipment cost and greater availability compared with those of MRI. Emerging US fat quantification methods can be performed along with US elastography. The author group, consisting of members of the Society of Abdominal Radiology (SAR) Liver Fibrosis Disease-Focused Panel (DFP), the SAR Hepatic Iron Overload DFP, and the European Society of Radiology, review the basics of liver fibrosis, fat, and iron quantification with MRI and liver fibrosis and fat quantification with US. The authors cover technical requirements, typical case display, quality control and proper measurement technique and case interpretation guidelines, pitfalls, and confounding factors. The authors aim to provide a practical guide for radiologists interpreting these examinations. © RSNA, 2023 See the invited commentary by Ronot in this issue. Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Flavius F Guglielmo
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Richard G Barr
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Takeshi Yokoo
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Giovanna Ferraioli
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - James T Lee
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Jonathan R Dillman
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Jeanne M Horowitz
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Kartik S Jhaveri
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Frank H Miller
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Roshan Y Modi
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Amirkasra Mojtahed
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Michael A Ohliger
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Ali Pirasteh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Scott B Reeder
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Krishna Shanbhogue
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Alvin C Silva
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Elainea N Smith
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Venkateswar R Surabhi
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Bachir Taouli
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Christopher L Welle
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Benjamin M Yeh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Sudhakar K Venkatesh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
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Mahalingam N, Trout AT, Zhang B, Castro-Rojas C, Miethke AG, Dillman JR. Longitudinal changes in quantitative magnetic resonance imaging metrics in children and young adults with autoimmune liver disease. ABDOMINAL RADIOLOGY (NEW YORK) 2023; 48:1933-1944. [PMID: 36799997 DOI: 10.1007/s00261-022-03733-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/25/2022] [Accepted: 10/26/2022] [Indexed: 02/18/2023]
Abstract
PURPOSE To assess longitudinal changes in quantitative MRI metrics in pediatric and young adult patients with autoimmune liver disease (AILD). METHODS This prospective, IRB-approved study included 20 children and young adults (median age = 15 years) with primary sclerosing cholangitis (PSC)/autoimmune sclerosing cholangitis (ASC) and 19 (median age = 17 years) with autoimmune hepatitis (AIH). At a field strength of 1.5-T, T2*-corrected T1 mapping (cT1), 3D fast spin-echo MRCP, and 2D gradient recalled echo MR elastography (MRE) were performed at baseline, one year, and two years. cT1 and quantitative MRCP were processed using LiverMultiScan and MRCP + , respectively (Perspectum Ltd, Oxford, UK). Linear mixed models were used to assess longitudinal changes in quantitative MRI metrics. Spearman rank-order correlation was used to assess relationships between changes in quantitative MRI metrics. RESULTS Changes in quantitative MRI metrics greater than established repeatability coefficients were measured in six (cT1) and five (MRE) patients with PSC/ASC as well as in six patients (cT1 and MRE) with AIH, although linear mixed models identified no significant changes for the subgroups as a whole. For PSC/ASC, there were positive correlations between change in liver stiffness and changes in bile duct strictures (ρ = 0.68; p = 0.005) and bile duct dilations (ρ = 0.70; p = 0.004) between baseline and Year 2. CONCLUSION On average, there were no significant changes in quantitative MRI metrics over a two-year period in children and young adults with AILD. However, worsening cholangiopathy was associated with increasing liver stiffness by MRE in patients with PSC/ASC.
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Affiliation(s)
- Neeraja Mahalingam
- Department of Radiology, Cincinnati Children's Hospital Medical Center, 250 Albert Sabin Way, Cincinnati, OH, 45229, USA.
| | - Andrew T Trout
- Department of Radiology, Cincinnati Children's Hospital Medical Center, 250 Albert Sabin Way, Cincinnati, OH, 45229, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Bin Zhang
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Cyd Castro-Rojas
- Division of Gastroenterology, Hepatology, and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Alexander G Miethke
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Gastroenterology, Hepatology, and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Jonathan R Dillman
- Department of Radiology, Cincinnati Children's Hospital Medical Center, 250 Albert Sabin Way, Cincinnati, OH, 45229, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Updates on Quantitative MRI of Diffuse Liver Disease: A Narrative Review. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1147111. [PMID: 36619303 PMCID: PMC9812615 DOI: 10.1155/2022/1147111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/10/2022] [Accepted: 12/12/2022] [Indexed: 12/29/2022]
Abstract
Diffuse liver diseases are highly prevalent conditions around the world, including pathological liver changes that occur when hepatocytes are damaged and liver function declines, often leading to a chronic condition. In the last years, Magnetic Resonance Imaging (MRI) is reaching an important role in the study of diffuse liver diseases moving from qualitative to quantitative assessment of liver parenchyma. In fact, this can allow noninvasive accurate and standardized assessment of diffuse liver diseases and can represent a concrete alternative to biopsy which represents the current reference standard. MRI approach already tested for other pathologies include diffusion-weighted imaging (DWI) and radiomics, able to quantify different aspects of diffuse liver disease. New emerging MRI quantitative methods include MR elastography (MRE) for the quantification of the hepatic stiffness in cirrhotic patients, dedicated gradient multiecho sequences for the assessment of hepatic fat storage, and iron overload. Thus, the aim of this review is to give an overview of the technical principles and clinical application of new quantitative MRI techniques for the evaluation of diffuse liver disease.
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Ozturk A, Olson MC, Samir AE, Venkatesh SK. Liver fibrosis assessment: MR and US elastography. Abdom Radiol (NY) 2022; 47:3037-3050. [PMID: 34687329 PMCID: PMC9033887 DOI: 10.1007/s00261-021-03269-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 08/31/2021] [Accepted: 09/01/2021] [Indexed: 01/18/2023]
Abstract
Elastography has emerged as a preferred non-invasive imaging technique for the clinical assessment of liver fibrosis. Elastography methods provide liver stiffness measurement (LSM) as a surrogate quantitative biomarker for fibrosis burden in chronic liver disease (CLD). Elastography can be performed either with ultrasound or MRI. Currently available ultrasound-based methods include strain elastography, two-dimensional shear wave elastography (2D-SWE), point shear wave elastography (pSWE), and vibration-controlled transient elastography (VCTE). MR Elastography (MRE) is widely available as two-dimensional gradient echo MRE (2D-GRE-MRE) technique. US-based methods provide estimated Young's modulus (eYM) and MRE provides magnitude of the complex shear modulus. MRE and ultrasound methods have proven to be accurate methods for detection of advanced liver fibrosis and cirrhosis. Other clinical applications of elastography include liver decompensation prediction, and differentiation of non-alcoholic steatohepatitis (NASH) from simple steatosis (SS). In this review, we briefly describe the different elastography methods, discuss current clinical applications, and provide an overview of advances in the field of liver elastography.
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Affiliation(s)
- Arinc Ozturk
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Michael C Olson
- Division of Abdominal Imaging, Radiology, Mayo Clinic Rochester, 200, First Street SW, Rochester, MN, 55905, USA
| | - Anthony E Samir
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Sudhakar K Venkatesh
- Division of Abdominal Imaging, Radiology, Mayo Clinic Rochester, 200, First Street SW, Rochester, MN, 55905, USA.
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Welle CL, Olson MC, Reeder SB, Venkatesh SK. Magnetic Resonance Imaging of Liver Fibrosis, Fat, and Iron. Radiol Clin North Am 2022; 60:705-716. [DOI: 10.1016/j.rcl.2022.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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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] [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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Eaton JE, Welle CL, Monahan H, Tahboub Amawi AD, Idilman I, Harmsen WS, Dzyubak B, Beiermann EW, Bakhshi Z, Gores GJ, LaRusso NF, Gossard AA, Lazaridis KN, Venkatesh SK. Comparative Performance of Quantitative and Qualitative Magnetic Resonance Imaging Metrics in Primary Sclerosing Cholangitis. GASTRO HEP ADVANCES 2022; 1:287-295. [PMID: 39131684 PMCID: PMC11307538 DOI: 10.1016/j.gastha.2022.01.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 01/05/2022] [Indexed: 08/13/2024]
Abstract
Background and Aims Several quantitative and qualitative magnetic resonance imaging (MRI) metrics have been reported to predict outcomes among those with primary sclerosing cholangitis (PSC). We aimed to compare the reproducibility and prognostic performances of MRI biomarkers and examine if combining these measurements adds value. Methods We performed a retrospective review of 388 patients with PSC who underwent a magnetic resonance elastography and magnetic resonance cholangiopancreatography. Liver stiffness (LS) was determined by validated automated software, whereas spleen volume was calculated by semiautomated software, and radiologists manually determined the ANALI scores. The primary endpoint was hepatic decompensation. Results LS and spleen volume values had perfect and near-perfect agreement (intraclass correlation coefficient of 1.00 and 0.9996, respectively), whereas ANALI with and without gadolinium had a moderate inter-rater agreement between 3 radiologists (kappa = 0.42-0.54 and 0.46-0.57, respectively). As a continuous variable, LS alone was the best predictor of hepatic decompensation (concordance score = 0.90; 95% confidence interval, 0.87-0.93). A quantitative-only MRI model [LS (>4.70 kPa = 2 or ≤4.70 kPa = 0) + spleen volume (>600 mm3 = 1 or ≤600 mm3 = 0)] had the optimal reproducibility and performance (concordance score = 0.85; 95% confidence interval = 0.80-0.89) and enabled patient risk stratification by estimating the 5-year incidence of hepatic decompensation: 7.49%, 44.50%, 70.00%, and 91.30% (score 0-3). Conclusion Quantitative MRI markers of fibrosis and portal hypertension generated by automated and semiautomated software are highly reproducible. LS is the single best imaging predictor of hepatic decompensation. However, a quantitative MRI score using LS and spleen volume is well suited to risk stratify those with PSC.
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Affiliation(s)
- John E. Eaton
- Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota
| | | | - Hannah Monahan
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | - Ilkay Idilman
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - William S. Harmsen
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Bogdan Dzyubak
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | - Zeinab Bakhshi
- Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota
| | - Gregory J. Gores
- Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota
| | - Nicholas F. LaRusso
- Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota
| | - Andrea A. Gossard
- Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota
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Intra-patient comparison of 3D and 2D magnetic resonance elastography techniques for assessment of liver stiffness. Abdom Radiol (NY) 2022; 47:998-1008. [PMID: 34982182 DOI: 10.1007/s00261-021-03355-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 11/15/2021] [Accepted: 11/16/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To evaluate performance of 3D magnetic resonance elastography (MRE) using spin-echo echo-planar imaging (seEPI) for assessment of hepatic stiffness compared with 2D gradient-recalled echo (GRE) and 2D seEPI sequences. METHODS Fifty-seven liver MRE examinations including 2D GRE, 2D seEPI, and 3D seEPI sequences were retrospectively evaluated. Elastograms were analyzed by 2 radiologists and polygonal regions of interests (ROIs) were drawn in 2 different fashions: "curated" ROI (avoiding liver edge, major vessels, and areas of wave interferences) and "non-curated" ROI (including largest cross section of liver, to assess the contribution of artifacts). Liver stiffness measurement (LSM) was calculated as the arithmetic mean of individual stiffness values for each technique. For 3D MRE, LSMs were also calculated based on 4 slices ("abbreviated LSM"). Intra-patient variations in LSMs and different methods of ROI placement were assessed by univariate tests. A p-value of < 0.05 was set as a statistically significant difference. RESULTS Mean surface areas of the ROIs were 50,723 mm2, 12,669 mm2, 5814 mm2, and 10,642 mm2 for 3D MRE, abbreviated 3D MRE, 2D GRE, and 2D seEPI, respectively. 3D LSMs based on curated and non-curated ROIs showed no clinically significant difference, with a mean difference less than 0.1 kPa. Abbreviated 3D LSMs had excellent correlation with 3D LSMs based on all slices (r = 0.9; p < 0.001) and were not significantly different (p = 0.927). CONCLUSION 3D MRE allows more reproducible measurements due to its lower susceptibility to artifacts and provides larger areas of parenchyma, enabling a more comprehensive evaluation of the liver.
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12
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Automated CNN-Based Analysis Versus Manual Analysis for MR Elastography in Nonalcoholic Fatty Liver Disease: Inter-method Agreement and Fibrosis Stage Discriminative Performance. AJR Am J Roentgenol 2022; 219:224-232. [PMID: 35107306 DOI: 10.2214/ajr.21.27135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background: Histological fibrosis stage is the most important prognostic factor in chronic liver disease. MR elastography (MRE) is the most accurate noninvasive method for detecting and staging liver fibrosis. Although accurate, manual ROI-based MRE analysis is complex, time consuming, requires specialized readers, and prone to methodologic variability and suboptimal inter-reader agreement. Objectives: To develop an automated convolutional neural network (CNN)-based method for liver MRE analysis, evaluate its agreement with manual ROI-based analysis, and assess its discriminative performance for dichotomized fibrosis stages using histology as reference standard. Methods: In this retrospective cross-sectional study, 675 participants who underwent MRE using different MRI systems and field strengths at 28 imaging sites from five multicenter international clinical trials of nonalcoholic steatohepatitis were included for algorithm development and internal testing of agreement between automated CNN- and manual ROI-based analyses. Eighty-one patients (52 women, 29 men; mean age, 54 years) who underwent MRE using a single 3-Tesla system and liver biopsy for clinical purposes at a single institution were included for external testing of agreement and assessment of fibrosis stage discriminative performance. Agreement was evaluated using intra-class correlation coefficients (ICC). 95% CIs were computed using bootstrapping. Discriminative performance of each method for dichotomized histologic fibrosis stage was evaluated by AUC and compared using bootstrapping. Results: Mean CNN- and manual ROI-based stiffness measurements ranged from 3.21 to 3.34 kPa in trial participants and from 3.30 to 3.45 kPa in clinical patients. ICC for CNN- and manual ROI-based measurements was 0.98 (95% CI, 0.978-0.98) in trial participants and 0.99 (95% CI: 0.98-0.99) in clinical patients. AUC for classification of dichotomized fibrosis stage ranged from 0.89-0.93 for CNN- and 0.87-0.93 for manual ROI-based analyses (p=.23-.75). Conclusion: Stiffness measurements using the automated CNN-based method agreed strongly with manual ROIbased analysis across MRI systems and field strengths, with excellent discriminative performance for histology-determined dichotomized fibrosis stages in external testing. Clinical Impact: Given the high incidence of chronic liver disease worldwide, it is important that noninvasive tools to assess fibrosis are applied reliably across different settings. CNN-based analysis is feasible and may reduce reliance on expert image analysts.
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Tang H, Li J, Zinker B, Boehm S, Mauer A, Rex-Rabe S, Glaser KJ, Fronheiser M, Bradstreet T, Nakao Y, Petrone T, Pena A, Villano M, Chow P, Malhi H, Charles ED, Hayes W, Ehman RL, Du S, Yin M. Evaluation of a PEGylated Fibroblast Growth Factor 21 Variant Using Novel Preclinical Magnetic Resonance Imaging and Magnetic Resonance Elastography in a Mouse Model of Nonalcoholic Steatohepatitis. J Magn Reson Imaging 2022; 56:712-724. [PMID: 35092323 PMCID: PMC9533307 DOI: 10.1002/jmri.28077] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 01/10/2022] [Accepted: 01/11/2022] [Indexed: 01/07/2023] Open
Abstract
Background Treatments for nonalcoholic steatohepatitis (NASH) are urgently needed. Hepatic fat fraction and shear stiffness quantified by magnetic resonance imaging (MRI‐HFF) and magnetic resonance elastography (MRE‐SS), respectively, are biomarkers for hepatic steatosis and fibrosis. Purpose This study assessed the longitudinal effects of fibroblast growth factor 21 variant (polyethylene glycol [PEG]‐FGF21v) on MRI‐HFF and MRE‐SS in a NASH mouse model. Study Type Preclinical. Animal Model This study included a choline‐deficient, amino acid‐defined, high‐fat diet (CDAHFD) model and 6‐week‐old, male C57BL/6J mice (N = 78). Field Strength/Sequence This study was performed using: 3T: gradient‐echo two‐point Dixon and spin‐echo (SE) echo‐planar imaging elastography (200 Hz) and 7T: SE two‐point Dixon and SE elastography (200 Hz). Assessment MRI and MRE were performed before control diet (CD) or CDAHFD (BD), before PEG‐FGF21v dosing (baseline), and after PEG‐FGF21v treatment (WK4/8). Regions of interest for MRI‐HFF and MRE‐SS were delineated by J.L. and H.T. (>5 years of experience each). Fibrosis and steatosis were measured histologically after picrosirius red and H&E staining. Alkaline phosphatase, alanine transaminase, bile acids, and triglycerides (TGs) were measured. Statistical Tests Two‐tailed Dunnett's tests were used for statistical analysis; untreated CDAHFD or baseline was used for comparisons. Imaging and histology/biochemistry data were determined using Spearman correlations. Bayesian posterior distributions for MRE‐SS at WK8, posterior means, and 95% credible intervals were presented. Results CDAHFD significantly increased baseline MRI‐HFF (3T: 21.97% ± 0.29%; 7T: 40.12% ± 0.35%) and MRE‐SS (3T: 1.25 ± 0.02; 7T: 1.78 ± 0.06 kPa) vs. CD (3T: 3.45% ± 0.7%; 7T: 12.06% ± 1.4% and 3T: 1.01 ± 0.02; 7T: 0.89 ± 0.06 kPa). At 7T, PEG‐FGF21v significantly decreased MRI‐HFF (WK4: 28.97% ± 1.22%; WK8: 20.93% ± 1.15%) and MRE‐SS (WK4: 1.57 ± 0.04; WK8: 1.36 ± 0.05 kPa) vs. untreated (WK4: 36.36% ± 0.62%; WK8: 30.58% ± 0.81% and WK4: 2.03 ± 0.06; WK8: 2.01 ± 0.04 kPa); 3T trends were similar. WK8 SS posterior mean percent attenuation ratios (RDI) were −68% (−90%, −44%; 3T) and −64% (−78%, −52%; 7T). MRI‐HFF was significantly correlated with H&E (3T, r = 0.93; 7T, r = 0.94) and TGs (both, r = 0.92). Data Conclusions MRI‐HFF and MRE‐SS showed PEG‐FGF21v effects on hepatic steatosis and fibrosis across 3 and 7T, consistent with histological and biochemical data. Level of Evidence 1 Technical Efficacy Stage 2
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Affiliation(s)
- Haiying Tang
- Bristol Myers Squibb, Princeton, New Jersey, USA
| | - Jiahui Li
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Amy Mauer
- Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Kevin J Glaser
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Yasuhiko Nakao
- Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | | | - Patrick Chow
- Bristol Myers Squibb, Princeton, New Jersey, USA
| | - Harmeet Malhi
- Department of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Wendy Hayes
- Bristol Myers Squibb, Princeton, New Jersey, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Shuyan Du
- Bristol Myers Squibb, Princeton, New Jersey, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
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Associations Between Quantitative MRI Metrics and Clinical Risk Scores in Children and Young Adults With Autoimmune Liver Disease. AJR Am J Roentgenol 2022; 219:142-150. [PMID: 35080454 DOI: 10.2214/ajr.21.27204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background: The Mayo risk score and SCOPE (Sclerosing Cholangitis Outcomes in Pediatrics) Index are clinical risk scores for monitoring progression of primary sclerosing cholangitis (PSC) and predict clinically important endpoints. Objective: To evaluate relationships of quantitative MRI measures of liver disease with clinical risk scores in children and young adults with autoimmune liver disease (AILD). Methods: This prospective study included 58 patients (35 male, 23 female; mean age, 15 years; range, 6-24 years) with AILD [PSC (n=16), autoimmune hepatitis (n=30), autoimmune sclerosing cholangitis (n=12)] who underwent research liver MRI examinations including: MR elastography (MRE), T2*-corrected T1 (cT1), and quantitative MRCP measurements. Associations between quantitative MRI metrics and clinical risk scores were evaluated using Spearman rank-order correlation coefficients and multivariable regression analyses. Results: Mean Mayo risk score was -1.1±0.9 (range: -2.9-1.1); mean SCOPE Index was 2.7±2.2 (range: 0-9). Mean liver stiffness was 2.8±1.1 kPa, mean whole-liver mean cT1 was 875±78 ms, and mean cT1 interquartile range (IQR) was 151±56 ms. Mayo risk score was significantly correlated with liver stiffness (r=0.56; p<.001), cT1 IQR (r=0.58; p<.001), whole-liver mean cT1 (r=0.31; p=.02), and multiple quantitative MRCP measures (r=0.36-0.45, p<.001). SCOPE Index was significantly correlated with liver stiffness (r=0.68; p<.001), cT1 IQR (r=0.51; p<.001), and multiple quantitative MRCP measures (r=0.47-0.49, p<.001). Multivariable linear regression analyses identified liver stiffness, cT1 IQR, and left hepatic duct maximum diameter as significant independent predictors of Mayo risk score (adjusted R2=0.45), and liver stiffness, cT1 IQR, common bile duct maximum (CBD) diameter, and CBD median diameter as significant independent predictors of SCOPE Index (adjusted R2=0.69). On logistic regression analysis, greater than low risk by SCOPE Index was best predicted by liver stiffness [odds ratio (OR)=49.6; 95% CI: 3.1-793.6) and CBD maximum diameter (OR=2.5; 95% CI: 1.3-4.7). Conclusion: Increased liver stiffness, increased cT1 IQR, and larger bile duct diameters are independently associated with higher (worse) Mayo risk score and SCOPE Index in children and young adults with AILD and may be surrogate markers of clinically meaningful endpoints. Clinical Impact: Multiparametric liver MRI incorporating quantitative metrics may serve as a noninvasive diagnostic and prognostic tool in pediatric AILD.
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Magnetic resonance elastography of the liver: everything you need to know to get started. Abdom Radiol (NY) 2022; 47:94-114. [PMID: 34725719 DOI: 10.1007/s00261-021-03324-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/17/2021] [Accepted: 10/18/2021] [Indexed: 12/17/2022]
Abstract
Magnetic resonance elastography (MRE) of the liver has emerged as the non-invasive standard for the evaluation of liver fibrosis in chronic liver diseases (CLDs). The utility of MRE in the evaluation of different CLD in both adults and children has been demonstrated in several studies, and MRE has been recommended by several clinical societies. Consequently, the clinical indications for evaluation of CLD with MRE have increased, and MRE is currently used as an add-on test during routine liver MRI studies or as a standalone test. To meet the increasing clinical demand, MRE is being installed in many academic and private practice imaging centers. There is a need for a comprehensive practical guide to help these practices to deliver high-quality liver MRE studies as well as troubleshoot the common issues with MRE to ensure smooth running of the service. This comprehensive clinical practice review summarizes the indications and provides an overview on why to use MRE, technical requirements, system set-up, patient preparation, acquiring the data, and interpretation.
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Chen J, Allen AM, Therneau TM, Chen J, Li J, Hoodeshenas S, Chen J, Lu X, Zhu Z, Venkatesh SK, Song B, Ehman RL, Yin M. Liver stiffness measurement by magnetic resonance elastography is not affected by hepatic steatosis. Eur Radiol 2021; 32:950-958. [PMID: 34432123 DOI: 10.1007/s00330-021-08225-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 07/15/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To evaluate the relationship between biopsy-assessed hepatic steatosis, magnetic resonance imaging (MRI)-assessed proton density fat fraction (PDFF), and magnetic resonance elastography (MRE)-assessed liver stiffness measurement (LSM), in patients with or at risk for nonalcoholic fatty liver disease (NAFLD). METHODS A retrospective study was performed, encompassing 256 patients who had a liver biopsy and MRI/MRE examination performed within 1 year. Clinical and laboratory data were retrieved from the electronic medical record. Hepatic steatosis and fibrosis were assessed by histopathological grading/staging. First, we analyzed the diagnostic performance of PDFF for distinguishing hepatic steatosis with the receiver operating characteristic analyses. Second, variables influencing LSM were screened with univariant analyses, then identified with multivariable linear regression. Finally, the potential relationship between PDFF and LSM was assessed with linear regression after adjustment for other influencing factors, in patients with diagnosed steatosis (PDFF ≥ 5%). RESULTS The diagnostic accuracy of PDFF in distinguishing steatosis grades (S0-3) was above 0.82. No significant difference in LSM was found between patients with S1, S2, and S3 steatosis and between all steatosis grades after patients were grouped according to fibrosis stage. No statistically significant relationship was found between the LSM and PDFF (estimate = - 0.02, p = 0.065) after adjustment for fibrosis stage and age in patients with diagnosed steatosis (PDFF ≥ 5%). CONCLUSIONS In patients with NAFLD, the severity of hepatic steatosis has no significant influence on the liver stiffness measurement with magnetic resonance elastography. KEY POINTS • The MRI-based proton density fat fraction provides a quantitative assessment of hepatic steatosis with high accuracy. • No significant effect of hepatic steatosis on MRE-based liver stiffness measurement was found in patients with S1, S2, and S3 steatosis and between all steatosis grades after patients were grouped according to fibrosis stage. • After adjusting for fibrosis stage and age, there was no statistically significant relationship between liver stiffness and proton density fat fraction in patients with hepatic steatosis (p = 0.065).
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Affiliation(s)
- Jie Chen
- Department of Radiology, West China Hospital, Sichuan University, No.37 Guoxue Alley, Chengdu, 610041, China.,Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Alina M Allen
- Division of Gastroenterology and Hepatology, Mayo Clinic, 200 First Street SW, MN, 55905, Rochester, USA
| | - Terry M Therneau
- Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, MN, 55905, Rochester, USA
| | - Jun Chen
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jiahui Li
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Safa Hoodeshenas
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jingbiao Chen
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Xin Lu
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Zheng Zhu
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Sudhakar K Venkatesh
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, No.37 Guoxue Alley, Chengdu, 610041, China
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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Gandhi DB, Pednekar A, Braimah AB, Dudley J, Tkach JA, Trout AT, Miethke AG, Franck MD, Heilman JA, Dzyubak B, Lake DS, Dillman JR. Assessment of agreement between manual and automated processing of liver MR elastography for shear stiffness estimation in children and young adults with autoimmune liver disease. Abdom Radiol (NY) 2021; 46:3927-3934. [PMID: 33811261 DOI: 10.1007/s00261-021-03073-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 03/17/2021] [Accepted: 03/21/2021] [Indexed: 12/30/2022]
Abstract
PURPOSE To compare automated versus standard of care manual processing of 2D gradient recalled echo (GRE) liver MR Elastography (MRE) in children and young adults. MATERIALS AND METHODS 2D GRE liver MRE data from research liver MRI examinations performed as part of an autoimmune liver disease registry between March 2017 and March 2020 were analyzed retrospectively. All liver MRE data were acquired at 1.5 T with 60 Hz mechanical vibration frequency. For manual processing, two independent readers (R1, R2) traced regions of interest on scanner generated shear stiffness maps. Automated processing was performed using MREplus+ (Resoundant Inc.) using 90% (A90) and 95% (A95) confidence masks. Agreement was evaluated using intra-class correlation coefficients (ICC) and Bland-Altman analyses. Classification performance was evaluated using receiver operating characteristic curve (ROC) analyses. RESULTS In 65 patients with mean age of 15.5 ± 3.8 years (range 8-23 years; 35 males) median liver shear stiffness was 2.99 kPa (mean 3.55 ± 1.69 kPa). Inter-reader agreement for manual processing was very strong (ICC = 0.99, mean bias = 0.01 kPa [95% limits of agreement (LoA): - 0.41 to 0.44 kPa]). Correlation between manual and A95 automated processing was very strong (R1: ICC = 0.988, mean bias = 0.13 kPa [95% LoA: - 0.40 to 0.68 kPa]; R2: ICC = 0.987, mean bias = 0.13 kPa [95% LoA: - 0.44 to 0.69 kPa]). Automated measurements were perfectly replicable (ICC = 1.0; mean bias = 0 kPa). CONCLUSION Liver shear stiffness values obtained using automated processing showed excellent agreement with manual processing. Automated processing of liver MRE was perfectly replicable.
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Affiliation(s)
- Deep B Gandhi
- Department of Radiology, Imaging Research Center (IRC), Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA
| | - Amol Pednekar
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
- Imaging Research Center, 3333 Burnet Avenue, Suite S1.533, Cincinnati, OH, 45229, USA.
| | - Adebayo B Braimah
- Department of Radiology, Imaging Research Center (IRC), Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA
| | - Jonathan Dudley
- Department of Radiology, Imaging Research Center (IRC), Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA
| | - Jean A Tkach
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Andrew T Trout
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Alexander G Miethke
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Hepatology, Gastroenterology and Nutrition, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA
| | - Marnix D Franck
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Radboud University, Nijmegen, The Netherlands
| | | | - Bogdan Dzyubak
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - David S Lake
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Jonathan R Dillman
- Department of Radiology, Imaging Research Center (IRC), Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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18
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Agreement Between Automated and Clinically Reported Manual ROI-Based MR Elastography Liver Stiffness Measurements in Children and Young Adults. AJR Am J Roentgenol 2021; 218:163-164. [PMID: 34286591 DOI: 10.2214/ajr.21.26423] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
MR elastography (MRE) typically requires manual ROI placement to generate liver shear stiffness measurements. Among 419 patients (primarily children and young adults), a computer-based automated MRE processing tool and clinically reported manual ROI-based measurements generated similar results (mean bias = 0.13 kPa). The intraclass correlation coefficient was 0.94 and was at least 0.90 across common indications in male and female patients and in patients with and without elevated liver fat fraction. Automated analysis may promote postprocessing standardization and decrease reporting variability.
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19
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Comparison of the diagnostic performance of 2D and 3D MR elastography in staging liver fibrosis. Eur Radiol 2021; 31:9468-9478. [PMID: 34023968 DOI: 10.1007/s00330-021-08053-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 04/16/2021] [Accepted: 05/06/2021] [Indexed: 12/12/2022]
Abstract
OBJECTIVES To compare the diagnostic performance and image quality of state-of-the-art 2D MR elastography (MRE) and 3D MRE in the basic application of liver fibrosis staging. METHODS This retrospective study assessed data from 293 patients who underwent 2D and 3D MRE examinations. MRE image quality was assessed with a qualitative 2-point grading system by evaluating artifacts. Two experienced analysts independently measured mean liver stiffness values. The interobserver agreement of liver stiffness measurement was assessed by the intraclass correlation coefficient (ICC). The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of 2D and 3D MRE and blood-based markers for fibrosis staging using the pathology-proven liver fibrosis stage as the gold standard. RESULTS The image quality provided by 3D MRE was graded as significantly higher than that obtained with the 2D MRE method (p < 0.01). Interobserver agreement in liver stiffness measurements was higher for 3D MRE (ICC: 3D 0.979 vs 2D 0.955). The AUC values for discriminating ≥ F1, ≥ F2, ≥ F3, and F4 fibrosis for 3D MRE (0.89, 0.92, 0.95, and 0.93) were similar to those for 2D MRE (0.89, 0.91, 0.94, and 0.92). Both the 2D and 3D MRE methods provided superior accuracy to the blood-based biomarkers, including APRI, FIB-4, and Forns index, especially for ≥ F2, ≥ F3, and F4 fibrosis stages (all p < 0.01). CONCLUSIONS While 3D MRE offers certain advantages and opportunities for new applications of MRE, current widely deployed 2D MRE technology has comparable performance in the basic application of detecting and staging liver fibrosis. KEY POINTS • 2D MRE and 3D MRE have comparable diagnostic performance in detecting and staging liver fibrosis. • 3D MRE has superior image quality and interobserver agreement compared to 2D MRE.
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20
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Moura Cunha G, Navin PJ, Fowler KJ, Venkatesh SK, Ehman RL, Sirlin CB. Quantitative magnetic resonance imaging for chronic liver disease. Br J Radiol 2021; 94:20201377. [PMID: 33635729 DOI: 10.1259/bjr.20201377] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Chronic liver disease (CLD) has rapidly increased in prevalence over the past two decades, resulting in significant morbidity and mortality worldwide. Historically, the clinical gold standard for diagnosis, assessment of severity, and longitudinal monitoring of CLD has been liver biopsy with histological analysis, but this approach has limitations that may make it suboptimal for clinical and research settings. Magnetic resonance (MR)-based biomarkers can overcome the limitations by allowing accurate, precise, and quantitative assessment of key components of CLD without the risk of invasive procedures. This review briefly describes the limitations associated with liver biopsy and the need for non-invasive biomarkers. It then discusses the current state-of-the-art for MRI-based biomarkers of liver iron, fat, and fibrosis, and inflammation.
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Affiliation(s)
- Guilherme Moura Cunha
- Department of Radiology, Liver Imaging Group, University of California San Diego, San Diego, CA, USA
| | | | - Kathryn J Fowler
- Department of Radiology, Liver Imaging Group, University of California San Diego, San Diego, CA, USA
| | | | | | - Claude B Sirlin
- Department of Radiology, Liver Imaging Group, University of California San Diego, San Diego, CA, USA
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21
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Dzyubak B, Li J, Chen J, Mara KC, Therneau TM, Venkatesh SK, Ehman RL, Allen AM, Yin M. Automated Analysis of Multiparametric Magnetic Resonance Imaging/Magnetic Resonance Elastography Exams for Prediction of Nonalcoholic Steatohepatitis. J Magn Reson Imaging 2021; 54:122-131. [PMID: 33586159 DOI: 10.1002/jmri.27549] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 01/18/2021] [Accepted: 01/21/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Nonalcoholic fatty liver disease (NAFLD) affects 25% of the global population. The standard of diagnosis, biopsy, is invasive and affected by sampling error and inter-reader variability. We hypothesized that widely available rapid MRI techniques could be used to predict nonalcoholic steatohepatitis (NASH) noninvasively by measuring liver stiffness, with magnetic resonance elastography (MRE), and liver fat, with chemical shift-encoded (CSE) MRI. Besides, we validate an automated image analysis technique to maximize the utility of these methods. PURPOSE To implement and test an automated system for analyzing CSE-MRI and MRE data coupled with model-based prediction of NASH. STUDY TYPE Prospective. SUBJECTS Eighty-three patients with suspected NAFLD. FIELD STRENGTH/SEQUENCE A 1.5 T using a flow-compensated motion-encoded gradient echo MRE sequence and a multiecho CSE-MRI sequence. ASSESSMENTS The MRE and CSE-MRI data were analyzed by two readers (5+ and 1 years of experience) and an automated algorithm. A logistic regression model to predict pathology-diagnosed NASH was trained based on stiffness and proton density fat fraction, and the area under the receiver operating characteristic curve (AUROC) was calculated using 10-fold cross validation for models based on both automated and manual measurements. A separate model was trained to predict the NASH severity score (NAS). STATISTICAL TESTS Pearson's correlation, Bland-Altman, AUROC, C-statistic. RESULTS The agreement between automated measurements and the more experienced reader (R2 = 0.87 for stiffness and R2 = 0.99 for proton density fat fraction [PDFF]) was slightly better than the agreement between readers (R2 = 0.85 and 0.98). The model for predicting biopsy-diagnosed NASH had an AUROC of 0.87. The NAS-prediction model had a C-statistic of 0.85. DATA CONCLUSION We demonstrated a workflow that used a limited MRI acquisition protocol and fully automated analysis to predict NASH with high accuracy. These methods show promise to provide a reliable noninvasive alternative to biopsy for NASH-screening in populations with NAFLD. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
| | - Jiahui Li
- Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jie Chen
- Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | | | | | - Alina M Allen
- GI and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Meng Yin
- Radiology, Mayo Clinic, Rochester, Minnesota, USA
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22
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MR Elastography. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00058-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Abstract
Application of MRE for noninvasive evaluation of renal fibrosis has great potential for noninvasive assessment in patients with chronic kidney disease (CKD). CKD leads to severe complications, which require dialysis or kidney transplant and could even result in death. CKD in native kidneys and interstitial fibrosis in allograft kidneys are the two major kidney fibrotic pathologies where MRE may be clinically useful. Both these conditions can lead to extensive morbidity, mortality, and high health care costs. Currently, biopsy is the standard method for renal fibrosis staging. This method of diagnosis is painful, invasive, limited by sampling bias, exhibits inter- and intraobserver variability, requires prolonged hospitalization, poses risk of complications and significant bleeding, and could even lead to death. MRE based methods can potentially be useful to noninvasively detect, stage, and monitor renal fibrosis, reducing the need for renal biopsy. In this chapter, we describe experimental procedure and step by step instructions to run MRE along with some illustrative applications. We also includes sections on how to perform data quality check and analysis methods.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers.
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Affiliation(s)
- Suraj D Serai
- Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA.
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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24
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Plaikner M, Kremser C, Viveiros A, Zoller H, Henninger B. [Magnetic resonance elastography of the liver : Worth knowing for clinical routine]. Radiologe 2020; 60:966-978. [PMID: 32399783 DOI: 10.1007/s00117-020-00690-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND Magnetic resonance elastography (MRE) is a noninvasive, quantitative, MRI-based method to evaluate liver stiffness. Beside biopsy and ultrasound elastography, this imaging method plays in many places a significant role in the detection and additive characterization of chronic liver disease. OBJECTIVES, MATERIALS AND METHODS Based on the literature, a brief review of the underlying method and the commercially available products is given. Furthermore, the practical procedure, the analysis, and the interpretation of clinically relevant questions are illustrated and a comparison with ultrasound elastography is provided. RESULTS This relative "young" MRI method allows extensive evaluation of mechanical properties of the liver and is an important diagnostic tool especially in follow-up examinations. The MRE of the liver is with a maximum technical failure rate of 5.8% a robust technique with high accuracy and an excellent re-test reliability as well as intra- and interobserver reproducibility. There is a high diagnostic certainty within the framework of most important clinical indications, the quantification of fibrosis, and with a very good correlation with the "gold standard" biopsy. CONCLUSION Based on its rising clinical relevance and the broad usage, MRE of the liver is increasingly used in many centers and in routine liver protocols. Therefore, basic knowledge of this method is essential for every radiologist.
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Affiliation(s)
- Michaela Plaikner
- Radiologie, Medizinische Universität Innsbruck, Anichstraße 35, 6020, Innsbruck, Österreich.
| | - Christian Kremser
- Radiologie, Medizinische Universität Innsbruck, Anichstraße 35, 6020, Innsbruck, Österreich
| | - André Viveiros
- Innere Medizin I, Medizinische Universität Innsbruck, Anichstraße 35, 6020, Innsbruck, Österreich
| | - Heinz Zoller
- Innere Medizin I, Medizinische Universität Innsbruck, Anichstraße 35, 6020, Innsbruck, Österreich
| | - Benjamin Henninger
- Radiologie, Medizinische Universität Innsbruck, Anichstraße 35, 6020, Innsbruck, Österreich
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25
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MR elastography of liver: current status and future perspectives. Abdom Radiol (NY) 2020; 45:3444-3462. [PMID: 32705312 DOI: 10.1007/s00261-020-02656-7] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 07/06/2020] [Accepted: 07/09/2020] [Indexed: 02/08/2023]
Abstract
Non-invasive evaluation of liver fibrosis has evolved over the last couple of decades. Currently, elastography techniques are the most widely used non-invasive methods for clinical evaluation of chronic liver disease (CLD). MR elastography (MRE) of the liver has been used in the clinical practice for nearly a decade and continues to be widely accepted for detection and staging of liver fibrosis. With MRE, one can directly visualize propagating shear waves through the liver and an inversion algorithm in the scanner automatically converts the shear wave properties into an elastogram (stiffness map) on which liver stiffness can be calculated. The commonly used MRE method, two-dimensional gradient recalled echo (2D-GRE) sequence has produced excellent results in the evaluation of liver fibrosis in CLD from various etiologies and newer clinical indications continue to emerge. Advances in MRE technique, including 3D MRE, automated liver elasticity calculation, improvements in shear wave delivery and patient experience, are promising to provide a faster and more reliable MRE of liver. Innovations, including evaluation of mechanical parameters, such as loss modulus, displacement, and volumetric strain, are promising for comprehensive evaluation of CLD as well as understanding pathophysiology, and in differentiating various etiologies of CLD. In this review, the current status of the MRE of liver in CLD are outlined and followed by a brief description of advanced techniques and innovations in MRE of liver.
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Shahryari M, Meyer T, Warmuth C, Herthum H, Bertalan G, Tzschätzsch H, Stencel L, Lukas S, Lilaj L, Braun J, Sack I. Reduction of breathing artifacts in multifrequency magnetic resonance elastography of the abdomen. Magn Reson Med 2020; 85:1962-1973. [PMID: 33104294 DOI: 10.1002/mrm.28558] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 08/21/2020] [Accepted: 09/28/2020] [Indexed: 12/17/2022]
Abstract
PURPOSE With abdominal magnetic resonance elastography (MRE) often suffering from breathing artifacts, it is recommended to perform MRE during breath-hold. However, breath-hold acquisition prohibits extended multifrequency MRE examinations and yields inconsistent results when patients cannot hold their breath. The purpose of this work was to analyze free-breathing strategies in multifrequency MRE of abdominal organs. METHODS Abdominal MRE with 30, 40, 50, and 60 Hz vibration frequencies and single-shot, multislice, full wave-field acquisition was performed four times in 11 healthy volunteers: once with multiple breath-holds and three times during free breathing with ungated, gated, and navigated slice adjustment. Shear wave speed maps were generated by tomoelastography inversion. Image registration was applied for correction of intrascan misregistration of image slices. Sharpness of features was quantified by the variance of the Laplacian. RESULTS Total scan times ranged from 120 seconds for ungated free-breathing MRE to 376 seconds for breath-hold examinations. As expected, free-breathing MRE resulted in larger organ displacements (liver, 4.7 ± 1.5 mm; kidneys, 2.4 ± 2.2 mm; spleen, 3.1 ± 2.4 mm; pancreas, 3.4 ± 1.4 mm) than breath-hold MRE (liver, 0.7 ± 0.2 mm; kidneys, 0.4 ± 0.2 mm; spleen, 0.5 ± 0.2 mm; pancreas, 0.7 ± 0.5 mm). Nonetheless, breathing-related displacement did not affect mean shear wave speed, which was consistent across all protocols (liver, 1.43 ± 0.07 m/s; kidneys, 2.35 ± 0.21 m/s; spleen, 2.02 ± 0.15 m/s; pancreas, 1.39 ± 0.15 m/s). Image registration before inversion improved the quality of free-breathing examinations, yielding no differences in image sharpness to uncorrected breath-hold MRE in most organs (P > .05). CONCLUSION Overall, multifrequency MRE is robust to breathing when considering whole-organ values. Respiration-related blurring can readily be corrected using image registration. Consequently, ungated free-breathing MRE combined with image registration is recommended for multifrequency MRE of abdominal organs.
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Affiliation(s)
- Mehrgan Shahryari
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Tom Meyer
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Carsten Warmuth
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Helge Herthum
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Gergely Bertalan
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Heiko Tzschätzsch
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Lisa Stencel
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Steffen Lukas
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ledia Lilaj
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jürgen Braun
- Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ingolf Sack
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Abstract
There are >1.5 billion people with chronic liver disease worldwide, causing liver diseases to be a significant global health issue. Diffuse parenchymal liver diseases, including hepatic steatosis, fibrosis, metabolic diseases, and hepatitis cause chronic liver injury and may progress to fibrosis and eventually hepatocellular carcinoma. As early diagnosis and treatment of these diseases impact the progression and outcome, the need for assessment of the liver parenchyma has increased. While the current gold standard for evaluation of the hepatic parenchymal tissue, biopsy has disadvantages and limitations. Consequently, noninvasive methods have been developed based on serum biomarkers and imaging techniques. Conventional imaging modalities such as ultrasound, computed tomography scan, and magnetic resonance imaging provide noninvasive options for assessment of liver tissue. However, several recent advances in liver imaging techniques have been introduced. This review article focuses on the current status of imaging methods for diffuse parenchymal liver diseases assessment including their diagnostic accuracy, advantages and disadvantages, and comparison between different techniques.
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28
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Li J, Venkatesh SK, Yin M. Advances in Magnetic Resonance Elastography of Liver. Magn Reson Imaging Clin N Am 2020; 28:331-340. [PMID: 32624152 DOI: 10.1016/j.mric.2020.03.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
Magnetic resonance elastography (MRE) is the most accurate noninvasive technique in diagnosing fibrosis and cirrhosis in patients with chronic liver disease (CLD). The accuracy of hepatic MRE in distinguishing the severity of disease has been validated in studies of patients with various CLDs. Advanced hepatic MRE is a reliable, comfortable, and inexpensive alternative to liver biopsy for disease diagnosing, progression monitoring, and clinical decision making in patients with CLDs. This article summarizes current knowledge of the technical advances and innovations in hepatic MRE, and the clinical applications in various hepatic diseases.
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Affiliation(s)
- Jiahui Li
- Department of Radiology, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA
| | | | - Meng Yin
- Department of Radiology, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA.
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Idilman IS, Low HM, Bakhshi Z, Eaton J, Venkatesh SK. Comparison of liver stiffness measurement with MRE and liver and spleen volumetry for prediction of disease severity and hepatic decompensation in patients with primary sclerosing cholangitis. Abdom Radiol (NY) 2020; 45:701-709. [PMID: 31894383 DOI: 10.1007/s00261-019-02387-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
PURPOSE To compare liver stiffness measurement (LSM) with magnetic resonance elastography (MRE) and liver and spleen volumetry for prediction of disease severity and hepatic decompensation in primary sclerosing cholangitis (PSC). METHODS This retrospective study was approved by the institutional review board. Magnetic resonance imaging (MRI) and MRE studies were reviewed, and mean LSM of entire liver, right lobe and left lobe, total liver, right lobe, left lobe, caudate lobe, and spleen volumes were calculated. Qualitative evaluation of lobar atrophy or hypertrophy and presence of macronodular regeneration (MNR) was recorded. Statistical analysis was performed to evaluate correlations between LSM, volumetry measurements, and Mayo risk score. Univariate and multivariate analyses were performed to predict hepatic decompensation. RESULTS A total of 266 patients with PSC were included in the study. Lobar stiffness measures were higher in the presence of relative lobe atrophy. Mean LSM was higher in the presence of MNR. Significant correlations were observed between mean LSM and volumetry measurements with a fair correlation between LSM and spleen volume (rs = 0.526, p < 0.0001). Among the measurements, the best correlation was observed between mean LSM and Mayo risk score (rs = 0.646, p < 0.0001). In the multivariate analyses, mean LSM and Mayo risk score were significantly associated with liver decompensation (hazard ratio, 1.18; 95%CI 1.02-1.36 and hazard ratio, 1.65; 95%CI 1.08-2.53, respectively). CONCLUSION LSM with MRE performs significantly better than liver and spleen volumes for prediction of both disease severity and hepatic decompensation.
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Affiliation(s)
- Ilkay S Idilman
- Department of Radiology, School of Medicine, Hacettepe University, Ankara, Turkey
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Hsien Min Low
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, Tan Tock Seng Hospital, Singapore, Singapore
| | - Zeinab Bakhshi
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - John Eaton
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
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Hoodeshenas S, Welle CL, Navin PJ, Dzyubak B, Eaton JE, Ehman RL, Venkatesh SK. Magnetic Resonance Elastography in Primary Sclerosing Cholangitis: Interobserver Agreement for Liver Stiffness Measurement with Manual and Automated Methods. Acad Radiol 2019; 26:1625-1632. [PMID: 30878345 DOI: 10.1016/j.acra.2019.02.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Revised: 02/04/2019] [Accepted: 02/05/2019] [Indexed: 02/07/2023]
Abstract
RATIONALE AND OBJECTIVE Primary sclerosing cholangitis, a chronic liver disease causes heterogeneous parenchymal changes and fibrosis. Liver stiffness measurement (LSM) with magnetic resonance Elastography (MRE) may be affected by this heterogeneous distribution. We evaluated interobserver agreement of LSM in primary sclerosing cholangitis (PSC) with manual and automated methods to study the influence of heterogeneous changes. MATERIALS AND METHODS A total of 79 consecutive patients with PSC who had a liver MRI and MRE formed the study group. Three readers with 1-3 years' experience in MRE and a MRE expert (11 years' experience) independently performed LSM. Each reader manually drew free hand (fROI) and average (aROI) on stiffness maps. Automatic liver elasticity calculation (ALEC) was used to generate automated LSM. The expert fROI was the reference standard. Correlation analysis and absolute intra-class correlation coefficient (ICC) analysis was performed. RESULTS LSM data of 79 livers and 315 sections were evaluated. There was excellent ICC between expert and reader fROIs (0.989, 95% confidence interval, and 0.985-0.993) and aROIs (0.971, 95% confidence interval, and 0.953-0.983) and ALEC (0.972, 0.957-0.982) with fROI performing better. The areas measured with fROIs and ALEC had moderate ICC with Expert fROI (0.64 and 0.56, respectively) whereas aROI area had a poor ICC of 0.12. Comparison of multiple methods showed significant differences in LSM between expert fROI and aROI of two readers and no significant differences for fROIs of all three readers. CONCLUSION LSM with MRE in PSC patients shows excellent interobserver agreement with both fROI and aROI methods with better performance with fROI. fROI may therefore be preferred for LSM measurements in PSC.
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Affiliation(s)
- Safa Hoodeshenas
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Christopher L Welle
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Patrick J Navin
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Bogdan Dzyubak
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - John E Eaton
- Division of Gastroenterology and Hepatology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
| | - Sudhakar K Venkatesh
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905.
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Rezvani Habibabadi R, Khoshpouri P, Ghadimi M, Shaghaghi M, Ameli S, Hazhirkarzar B, Pandey P, Aliyari Ghasabeh M, Pandey A, Kamel IR. Comparison between ROI-based and volumetric measurements in quantifying heterogeneity of liver stiffness using MR elastography. Eur Radiol 2019; 30:1609-1615. [DOI: 10.1007/s00330-019-06478-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 09/01/2019] [Accepted: 09/27/2019] [Indexed: 12/15/2022]
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Guglielmo FF, Venkatesh SK, Mitchell DG. Liver MR Elastography Technique and Image Interpretation: Pearls and Pitfalls. Radiographics 2019; 39:1983-2002. [DOI: 10.1148/rg.2019190034] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Flavius F. Guglielmo
- From the Department of Radiology, Thomas Jefferson University Hospital, 132 S 10th St, Philadelphia, PA 19107 (F.F.G., D.G.M.); and Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V.)
| | - Sudhakar K. Venkatesh
- From the Department of Radiology, Thomas Jefferson University Hospital, 132 S 10th St, Philadelphia, PA 19107 (F.F.G., D.G.M.); and Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V.)
| | - Donald G. Mitchell
- From the Department of Radiology, Thomas Jefferson University Hospital, 132 S 10th St, Philadelphia, PA 19107 (F.F.G., D.G.M.); and Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V.)
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Kim DW, Kim SY, Yoon HM, Kim KW, Byun JH. Comparison of technical failure of MR elastography for measuring liver stiffness between gradient‐recalled echo and spin‐echo echo‐planar imaging: A systematic review and meta‐analysis. J Magn Reson Imaging 2019; 51:1086-1102. [DOI: 10.1002/jmri.26918] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 08/14/2019] [Indexed: 12/14/2022] Open
Affiliation(s)
- Dong Wook Kim
- The Department of Radiology and Research Institute of RadiologyUniversity of Ulsan College of Medicine, Asan Medical Center Seoul Republic of Korea
| | - So Yeon Kim
- The Department of Radiology and Research Institute of RadiologyUniversity of Ulsan College of Medicine, Asan Medical Center Seoul Republic of Korea
| | - Hee Mang Yoon
- The Department of Radiology and Research Institute of RadiologyUniversity of Ulsan College of Medicine, Asan Medical Center Seoul Republic of Korea
| | - Kyung Won Kim
- The Department of Radiology and Research Institute of RadiologyUniversity of Ulsan College of Medicine, Asan Medical Center Seoul Republic of Korea
| | - Jae Ho Byun
- The Department of Radiology and Research Institute of RadiologyUniversity of Ulsan College of Medicine, Asan Medical Center Seoul Republic of Korea
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El-Meteini M, Sakr M, Eldorry A, Mohran Z, Abdelkader NA, Dabbous H, Montasser I, Refaie R, Salah M, Aly M. Non-Invasive Assessment of Graft Fibrosis After Living Donor Liver Transplantation: Is There Still a Role for Liver Biopsy? Transplant Proc 2019; 51:2451-2456. [PMID: 31358454 DOI: 10.1016/j.transproceed.2019.01.197] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 01/03/2019] [Indexed: 12/13/2022]
Abstract
Non-invasive methods have evolved as a surrogate for liver biopsy such as indirect markers (aspartate transaminase to platelet ratio index, fibro-α score), transient elastography (TE), and magnetic resonance elastography (MRE). The aim of this study is to prospectively compare the value of MRE, TE, and indirect markers in detecting and staging allograft fibrosis compared to liver biopsies in patients who have undergone living donor liver transplantation for complications related to hepatitis C virus. A total of 31 living donor liver transplantation recipients with hepatitis C virus recurrence underwent a liver biopsy, TE, and MRE within 3 months of a liver biopsy. Fibrosis was assessed according to the biopsy and staged according to Metavir criteria. There was a significant correlation between both MRE and fibro-α scores, as well as histologic classification by liver biopsy (P = .02, .002). The diagnostic accuracy of MRE and fibro-α scores in diagnosing significant fibrosis (F ≥ 3) was measured as the area under the curve (.708 and .833, respectively). Both methods showed good diagnostic performance. TE and aspartate transaminase to platelet ratio index were insignificantly correlated with the degree of fibrosis in liver biopsy (P value of .134, .535). At a cutoff value of 5.5 kPa, MRE predicted graft fibrosis (Metavir stage ≥ 3) with 71.43% sensitivity, 75% specificity, 45.5% positive predictive value, and 90% negative predictive value; at a cutoff value > 1.47, fibro-α scores predicted significant graft fibrosis (Metavir stage ≥ 3) with 85.7% sensitivity and 70.83% specificity, with a positive predictive value of 46.2% and a negative predictive value of 94.4%. These data suggest that non-invasive methods could be considered a reliable tool in assessing significant graft fibrosis post-living donor liver transplantation.
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Affiliation(s)
- M El-Meteini
- Department of Hepatobiliary Surgery & Liver Transplantation, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - M Sakr
- Tropical Medicine Department, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - A Eldorry
- Interventional Radiology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - Z Mohran
- Tropical Medicine Department, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - N A Abdelkader
- Tropical Medicine Department, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - H Dabbous
- Tropical Medicine Department, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - I Montasser
- Tropical Medicine Department, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - R Refaie
- Internal Medicine Department, Faculty of Medicine, Helwan University, Cairo, Egypt
| | - M Salah
- Tropical Medicine Department, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt.
| | - M Aly
- Tropical Medicine Department, Ain Shams Center for Organ Transplantation (ASCOT), Faculty of Medicine, Ain Shams University, Cairo, Egypt
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Abstract
The first clinical application of magnetic resonance elastography (MRE) was in the evaluation of chronic liver disease (CLD) for detection and staging of liver fibrosis. In the past 10 years, MRE has been incorporated seamlessly into a standard magnetic resonance imaging (MRI) liver protocol worldwide. Liver MRE is a robust technique for evaluation of liver stiffness and is currently the most accurate noninvasive imaging technology for evaluation of liver fibrosis. Newer MRE sequences including spin-echo MRE and 3 dimensional MRE have helped in reducing the technical limitations of clinical liver MRE that is performed with 2D gradient recalled echo (GRE) MRE. Advances in MRE technology have led to understanding of newer mechanical parameters such as dispersion, attenuation, and viscoelasticity that may be useful in evaluating pathological processes in CLD and may prove useful in their management.This review article will describe the changes in CLD that cause an increase in stiffness followed by principle and technique of liver MRE. In the later part of the review, we will briefly discuss the advances in liver MRE.
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Allen AM, Shah VH, Therneau TM, Venkatesh SK, Mounajjed T, Larson JJ, Mara KC, Schulte PJ, Kellogg TA, Kendrick ML, McKenzie TJ, Greiner SM, Li J, Glaser KJ, Wells ML, Chen J, Ehman RL, Yin M. The Role of Three-Dimensional Magnetic Resonance Elastography in the Diagnosis of Nonalcoholic Steatohepatitis in Obese Patients Undergoing Bariatric Surgery. Hepatology 2018; 71:510-521. [PMID: 30582669 PMCID: PMC6591099 DOI: 10.1002/hep.30483] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 10/29/2018] [Indexed: 12/17/2022]
Abstract
The lack of reliable, noninvasive methods to diagnose early nonalcoholic steatohepatitis (NASH) is a major unmet need. We aimed to determine the diagnostic accuracy of three-dimensional magnetic resonance elastography (3D-MRE), with shear stiffness measured at 60 Hz, damping ratio at 40 Hz, and magnetic resonance imaging proton density fat fraction (MRI-PDFF) in the detection of NASH in individuals undergoing bariatric surgery. Obese adults at risk for NASH were enrolled between 2015 and 2017 (prospective cohort, n = 88) and 2010 and 2013 (retrospective cohort, n = 87). The imaging protocol consisted of multifrequency 3D-MRE (mf3D-MRE) with shear waves delivered at different frequencies to explore parameters that best correlated with histologic NASH, and MRI-PDFF to estimate steatosis. The prospective cohort was used to establish the optimal mf3D-MRE technical parameters for NASH detection. The two cohorts were then combined to derive predictive models of NASH and disease activity by nonalcoholic fatty liver disease activity score (NAS) using the three imaging parameters that correlated with NASH. A total of 175 patients (median age 45, 81% women, and 81 [46%] with histologic NASH) were used for model derivation. From the complex shear modulus output generated by mf3D-MRE, the damping ratio at 40 Hz and shear stiffness at 60 Hz best correlated with NASH. The fat fraction obtained from MRI-PDFF correlated with steatosis (P < 0.05 for all). These three parameters were fit into a logistic regression model that predicted NASH with cross-validated area under the receiver operating characteristic curve (AUROC) = 0.73, sensitivity = 0.67, specificity = 0.80, positive predictive value = 0.73 and negative predictive value = 0.74, and disease activity by NAS with cross-validated AUROC = 0.82. Conclusion: The mf3D-MRE allows identification of imaging parameters that predict early NASH and disease activity. This imaging biomarker represents a promising alternative to liver biopsy for NASH diagnosis and monitoring. The results provide motivation for further studies in nonbariatric cohorts.
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Affiliation(s)
- Alina M. Allen
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Vijay H. Shah
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Terry M. Therneau
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | | | | | - Joseph J. Larson
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Kristin C. Mara
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Phillip J. Schulte
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Jiahui Li
- Department of Radiology, Mayo Clinic, Rochester, MN
| | | | | | - Jun Chen
- Department of Radiology, Mayo Clinic, Rochester, MN
| | | | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN
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Wang CK, Fang YHD, Lin LC, Lin CF, Kuo LC, Chiu FM, Chen CH. Magnetic Resonance Elastography in the Assessment of Acute Effects of Kinesio Taping on Lumbar Paraspinal Muscles. J Magn Reson Imaging 2018; 49:1039-1045. [PMID: 30284358 DOI: 10.1002/jmri.26281] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 07/18/2018] [Accepted: 07/19/2018] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Kinesio tape (KT) is an elastic therapeutic tape used for treating sports-related injuries and a number of other disorders. To date, the objective evidence to link pathophysiological effects and actual reactions triggered by KT is limited. PURPOSE To explore the effect of KT on the lumbar paraspinal muscles by magnetic resonance (MR) elastography. STUDY TYPE Prospective observational study. POPULATION Sixty-six asymptomatic volunteers with 31 women and 35 men. FIELD STRENGTH/SEQUENCE 3.0T MRI and elastography with vibration frequency of 120 Hz. ASSESSMENT The 5-cm-width KT with full tension was placed on a single side of the lumbar paraspinal muscle. The taping side and adhering direction were randomly decided. Two rectangular regions of interest (ROIs) of 5- and 2.5-cm-width were positioned at the bilateral paraspinal regions from the L2 to L4 level on the confidence map of MR elastography before and after KT taping. The mean shear stiffness values of the ROIs at the superficial, middle, and deep depths were recorded; then the differences between the taping and reference sides were calculated. STATISTICAL TESTS Paired t-test and Pearson correlations were used to evaluate the stiffness changes after KT application and intraoperator errors of the stiffness measures on the reference side, respectively. RESULTS A significant decrease in the muscle stiffness value between taping and reference sides (-0.71 kPa ± 0.60 with KT and -0.25 kPa ± 0.78 without KT, P < 0.0001 for 5-cm ROI; -0.67 kPa ± 1.12 with KT and -0.16 kPa ± 1.17 without KT, P = 0.0004 for 2.5-cm ROI) was found in the superficial depth, but no significant differences in the middle and deep depths (P = 0.25 and P = 0.79 for 5-cm ROI; P = 0.09 and P = 0.67 for 2.5-cm ROI, respectively). There were no significant differences of muscle stiffness differences between gender (P = 0.11 for superficial, P = 0.37 for middle, P = 0.78 for deep) and taping direction (P = 0.18 for superficial, P = 0.13 for middle, P = 0.15 for deep). DATA CONCLUSION Our results demonstrate that KT can reduce the MR elastography-derived shear stiffness in the superficial depth of paraspinal muscles. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1039-1045.
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Affiliation(s)
- Chien-Kuo Wang
- Department of Radiology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Yu-Hua Dean Fang
- Department of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan
| | - Liang-Ching Lin
- Department of Statistics, National Cheng Kung University, Tainan, Taiwan
| | - Cheng-Feng Lin
- Department of Physical Therapy, National Cheng Kung University, Tainan, Taiwan
| | - Li-Chieh Kuo
- Department of Occupational Therapy, National Cheng Kung University, Tainan, Taiwan
| | | | - Chia-Hui Chen
- College of Photonics, National Chiao Tung University, Tainan, Taiwan.,Department of Medical Imaging and Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan
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Garteiser P, Doblas S, Van Beers BE. Magnetic resonance elastography of liver and spleen: Methods and applications. NMR IN BIOMEDICINE 2018; 31:e3891. [PMID: 29369503 DOI: 10.1002/nbm.3891] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 11/16/2017] [Accepted: 12/04/2017] [Indexed: 05/06/2023]
Abstract
The viscoelastic properties of the liver and spleen can be assessed with magnetic resonance elastography (MRE). Several actuators, MRI acquisition sequences and reconstruction algorithms have been proposed for this purpose. Reproducible results are obtained, especially when the examination is performed in standard conditions with the patient fasting. Accurate staging of liver fibrosis can be obtained by measuring liver stiffness or elasticity with MRE. Moreover, emerging evidence shows that assessing the tissue viscous parameters with MRE is useful for characterizing liver inflammation, non-alcoholic steatohepatitis, hepatic congestion, portal hypertension, and hepatic tumors. Further advances such as multifrequency acquisitions and compression-sensitive MRE may provide novel quantitative markers of hepatic and splenic mechanical properties that may improve the diagnosis of hepatic and splenic diseases.
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Affiliation(s)
- Philippe Garteiser
- Laboratory of Imaging Biomarkers, Center of Research on Inflammation, UMR 1149 INSERM-University Paris Diderot, Paris, France
| | - Sabrina Doblas
- Laboratory of Imaging Biomarkers, Center of Research on Inflammation, UMR 1149 INSERM-University Paris Diderot, Paris, France
| | - Bernard E Van Beers
- Laboratory of Imaging Biomarkers, Center of Research on Inflammation, UMR 1149 INSERM-University Paris Diderot, Paris, France
- Department of Radiology, Beaujon University Hospital Paris Nord, Clichy, France
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Abstract
Liver fibrosis is a hallmark of chronic liver disease characterized by the excessive accumulation of extracellular matrix proteins. Although liver biopsy is the reference standard for diagnosis and staging of liver fibrosis, it has some limitations, including potential pain, sampling variability, and low patient acceptance. Hence, there has been an effort to develop noninvasive imaging techniques for diagnosis, staging, and monitoring of liver fibrosis. Many quantitative techniques have been implemented on magnetic resonance imaging (MRI) for this indication. The most widely validated technique is magnetic resonance elastography, which aims to measure viscoelastic properties of the liver and relate them to fibrosis stage. Several additional MRI methods have been developed or adapted to liver fibrosis quantification. Diffusion-weighted imaging measures the Brownian motion of water molecules which is restricted by collagen fibers. Texture analysis assesses the changes in the texture of liver parenchyma associated with fibrosis. Perfusion imaging relies on signal intensity and pharmacokinetic models to extract quantitative perfusion parameters. Hepatocellular function, which decreases with increasing fibrosis stage, can be estimated by the uptake of hepatobiliary contrast agents. Strain imaging measures liver deformation in response to physiological motion such as cardiac contraction. T1ρ quantification is an investigational technique, which measures the spin-lattice relaxation time in the rotating frame. This article will review the MRI techniques used in liver fibrosis staging, their advantages and limitations, and diagnostic performance. We will briefly discuss future directions, such as longitudinal monitoring of disease, prediction of portal hypertension, and risk stratification of hepatocellular carcinoma.
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Abstract
Liver stiffness is now a well-established noninvasive biomarker for assessing fibrosis in chronic liver disease. MRI-based and ultrasound-based dynamic elastography techniques have been introduced for assessment of liver stiffness and useful in clinical staging of hepatic fibrosis. Several different elastography techniques are now available with each method having inherent strengths and limitations. The published literature generally indicates that MR elastography has a higher diagnostic performance and fewer technical failures than ultrasound-based elastography techniques in assessing hepatic fibrosis. There is also significant potential to further develop elastography techniques to implement multiparametric methods that have promise for distinguishing between processes such as inflammation, fibrosis, venous congestion, and portal hypertension that can result in increased liver stiffness. In this commentary, we compare MR and ultrasound elastography methods and their utility in clinical practice.
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Miller R, Kolipaka A, Nash MP, Young AA. Estimation of transversely isotropic material properties from magnetic resonance elastography using the optimised virtual fields method. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2018; 34. [PMID: 29528568 PMCID: PMC5993646 DOI: 10.1002/cnm.2979] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Magnetic resonance elastography (MRE) has been used to estimate isotropic myocardial stiffness. However, anisotropic stiffness estimates may give insight into structural changes that occur in the myocardium as a result of pathologies such as diastolic heart failure. The virtual fields method (VFM) has been proposed for estimating material stiffness from image data. This study applied the optimised VFM to identify transversely isotropic material properties from both simulated harmonic displacements in a left ventricular (LV) model with a fibre field measured from histology as well as isotropic phantom MRE data. Two material model formulations were implemented, estimating either 3 or 5 material properties. The 3-parameter formulation writes the transversely isotropic constitutive relation in a way that dissociates the bulk modulus from other parameters. Accurate identification of transversely isotropic material properties in the LV model was shown to be dependent on the loading condition applied, amount of Gaussian noise in the signal, and frequency of excitation. Parameter sensitivity values showed that shear moduli are less sensitive to noise than the other parameters. This preliminary investigation showed the feasibility and limitations of using the VFM to identify transversely isotropic material properties from MRE images of a phantom as well as simulated harmonic displacements in an LV geometry.
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Affiliation(s)
- Renee Miller
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Arunark Kolipaka
- Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Martyn P. Nash
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Alistair A. Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
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Serai SD, Obuchowski NA, Venkatesh SK, Sirlin CB, Miller FH, Ashton E, Cole PE, Ehman RL. Repeatability of MR Elastography of Liver: A Meta-Analysis. Radiology 2017; 285:92-100. [PMID: 28530847 DOI: 10.1148/radiol.2017161398] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Purpose To perform a meta-analysis to generate an estimate of the repeatability coefficient (RC) for magnetic resonance (MR) elastography of the liver. Materials and Methods A systematic search of databases was performed for publications on MR elastography during the 10-year period between 2006 and 2015. The identified studies were screened independently and were verified reciprocally by all authors. Two reviewers independently determined the percentage RC and effective sample size from each article. A forest plot was constructed of the percentage RC estimates from the 12 studies. Bootstrap 95% confidence intervals (CIs) were constructed for the summary percentage RCs. Results Twelve studies comprising 274 patients met the eligibility criteria and were included for analysis. A flow diagram of studies included according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was prepared for the inclusion and exclusion criteria. All studies included in the meta-analysis fulfilled four or more of the seven categories of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2. The estimated summary RC was 22% (95% CI: 16.1%, 28.2%). The three main sources for this heterogeneity were the trained versus untrained operator drawing contours to choose regions of interest, the time between two replicate examinations, and, finally, the field strength of the MR imaging unit. The RC estimates tended to be higher for studies that did not use a well-trained operator, those with 1.5-T field strength imaging units, and those with longer time intervals between examinations. Conclusion The meta-analysis results provide the basis for the following draft longitudinal Quantitative Imaging Biomarkers Alliance MR elastography claim: A measured change in hepatic stiffness of 22% or greater, at the same site and with use of the same equipment and acquisition sequence, indicates that a true change in stiffness has occurred with 95% confidence. © RSNA, 2017.
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Affiliation(s)
- Suraj D Serai
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
| | - Nancy A Obuchowski
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
| | - Sudhakar K Venkatesh
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
| | - Claude B Sirlin
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
| | - Frank H Miller
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
| | - Edward Ashton
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
| | - Patricia E Cole
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
| | - Richard L Ehman
- From the Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 5031, Cincinnati, OH 45229 (S.D.S.); Department of Quantitative Health Sciences, the Cleveland Clinic Foundation, Cleveland, Ohio (N.A.O.); Department of Radiology, Mayo Clinic, Rochester, Minn (S.K.V., R.L.E.); Department of Radiology, UCSD Liver Imaging Group, San Diego, Calif (C.B.S.); Department of Radiology, Northwestern Memorial Hospital, Chicago, Ill (F.H.M.); Virtualscopics, Rochester, NY (E.A.); and Clinical and Translational Science-Imaging, Takeda Pharmaceuticals, Deerfield, Ill (P.E.C.)
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Dzyubak B, Glaser KJ, Manduca A, Ehman RL. Automated Liver Elasticity Calculation for 3D MRE. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2017; 10134. [PMID: 29033488 DOI: 10.1117/12.2254476] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Magnetic Resonance Elastography (MRE) is a phase-contrast MRI technique which calculates quantitative stiffness images, called elastograms, by imaging the propagation of acoustic waves in tissues. It is used clinically to diagnose liver fibrosis. Automated analysis of MRE is difficult as the corresponding MRI magnitude images (which contain anatomical information) are affected by intensity inhomogeneity, motion artifact, and poor tissue- and edge-contrast. Additionally, areas with low wave amplitude must be excluded. An automated algorithm has already been successfully developed and validated for clinical 2D MRE. 3D MRE acquires substantially more data and, due to accelerated acquisition, has exacerbated image artifacts. Also, the current 3D MRE processing does not yield a confidence map to indicate MRE wave quality and guide ROI selection, as is the case in 2D. In this study, extension of the 2D automated method, with a simple wave-amplitude metric, was developed and validated against an expert reader in a set of 57 patient exams with both 2D and 3D MRE. The stiffness discrepancy with the expert for 3D MRE was -0.8% ± 9.45% and was better than discrepancy with the same reader for 2D MRE (-3.2% ± 10.43%), and better than the inter-reader discrepancy observed in previous studies. There were no automated processing failures in this dataset. Thus, the automated liver elasticity calculation (ALEC) algorithm is able to calculate stiffness from 3D MRE data with minimal bias and good precision, while enabling stiffness measurements to be fully reproducible and to be easily performed on the large 3D MRE datasets.
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Petitclerc L, Sebastiani G, Gilbert G, Cloutier G, Tang A. Liver fibrosis: Review of current imaging and MRI quantification techniques. J Magn Reson Imaging 2016; 45:1276-1295. [PMID: 27981751 DOI: 10.1002/jmri.25550] [Citation(s) in RCA: 134] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 10/27/2016] [Indexed: 12/13/2022] Open
Abstract
Liver fibrosis is characterized by the accumulation of extracellular matrix proteins such as collagen in the liver interstitial space. All causes of chronic liver disease may lead to fibrosis and cirrhosis. The severity of liver fibrosis influences the decision to treat or the need to monitor hepatic or extrahepatic complications. The traditional reference standard for diagnosis of liver fibrosis is liver biopsy. However, this technique is invasive, associated with a risk of sampling error, and has low patient acceptance. Imaging techniques offer the potential for noninvasive diagnosis, staging, and monitoring of liver fibrosis. Recently, several of these have been implemented on ultrasound (US), computed tomography, or magnetic resonance imaging (MRI). Techniques that assess changes in liver morphology, texture, or perfusion that accompany liver fibrosis have been implemented on all three imaging modalities. Elastography, which measures changes in mechanical properties associated with liver fibrosis-such as strain, stiffness, or viscoelasticity-is available on US and MRI. Some techniques assessing liver shear stiffness have been adopted clinically, whereas others assessing strain or viscoelasticity remain investigational. Further, some techniques are only available on MRI-such as spin-lattice relaxation time in the rotating frame (T1 ρ), diffusion of water molecules, and hepatocellular function based on the uptake of a liver-specific contrast agent-remain investigational in the setting of liver fibrosis staging. In this review, we summarize the key concepts, advantages and limitations, and diagnostic performance of each technique. The use of multiparametric MRI techniques offers the potential for comprehensive assessment of chronic liver disease severity. LEVEL OF EVIDENCE 5 J. MAGN. RESON. IMAGING 2017;45:1276-1295.
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Affiliation(s)
- Léonie Petitclerc
- Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, Quebec, Canada.,Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Giada Sebastiani
- Department of Gastroenterology and Hepatology, McGill University Health Centre, Montreal, Quebec, Canada
| | - Guillaume Gilbert
- Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, Quebec, Canada.,MR Clinical Science, Philips Healthcare Canada, Markham, Ontario, Canada
| | - Guy Cloutier
- Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, Quebec, Canada.,Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada.,Institute of Biomedical Engineering, Université de Montréal, CP 6128, Succursale Centre-ville, Montréal, Québec, Canada.,Laboratory of Biorheology and Medical Ultrasonics, CRCHUM, 900 Saint-Denis, Montréal, Québec, Canada
| | - An Tang
- Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, Quebec, Canada.,Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada.,Institute of Biomedical Engineering, Université de Montréal, CP 6128, Succursale Centre-ville, Montréal, Québec, Canada
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Venkatesh SK, Loomba R. Non-invasive estimation of HVPG by combined structural and hemodynamic evaluation of portal hypertension using quantitative magnetic resonance imaging. J Hepatol 2016; 65:1079-1080. [PMID: 27663418 DOI: 10.1016/j.jhep.2016.09.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Accepted: 09/14/2016] [Indexed: 01/06/2023]
Affiliation(s)
| | - Rohit Loomba
- NAFLD Research Center, University of California, San Diego, La Jolla 92093, United States; Division of Gastroenterology, Department of Medicine, University of California, San Diego, La Jolla 92093, United States
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Srinivasa Babu A, Wells ML, Teytelboym OM, Mackey JE, Miller FH, Yeh BM, Ehman RL, Venkatesh SK. Elastography in Chronic Liver Disease: Modalities, Techniques, Limitations, and Future Directions. Radiographics 2016; 36:1987-2006. [PMID: 27689833 DOI: 10.1148/rg.2016160042] [Citation(s) in RCA: 140] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Chronic liver disease has multiple causes, many of which are increasing in prevalence. The final common pathway of chronic liver disease is tissue destruction and attempted regeneration, a pathway that triggers fibrosis and eventual cirrhosis. Assessment of fibrosis is important not only for diagnosis but also for management, prognostic evaluation, and follow-up of patients with chronic liver disease. Although liver biopsy has traditionally been considered the reference standard for assessment of liver fibrosis, noninvasive techniques are the emerging focus in this field. Ultrasound-based elastography and magnetic resonance (MR) elastography are gaining popularity as the modalities of choice for quantifying hepatic fibrosis. These techniques have been proven superior to conventional cross-sectional imaging for evaluation of fibrosis, especially in the precirrhotic stages. Moreover, elastography has added utility in the follow-up of previously diagnosed fibrosis, the assessment of treatment response, evaluation for the presence of portal hypertension (spleen elastography), and evaluation of patients with unexplained portal hypertension. In this article, a brief overview is provided of chronic liver disease and the tools used for its diagnosis. Ultrasound-based elastography and MR elastography are explored in depth, including a brief glimpse into the evolution of elastography. Elastography is based on the principle of measuring tissue response to a known mechanical stimulus. Specific elastographic techniques used to exploit this principle include MR elastography and ultrasonography-based static or quasistatic strain imaging, one-dimensional transient elastography, point shear-wave elastography, and supersonic shear-wave elastography. The advantages, limitations, and pitfalls of each modality are emphasized. ©RSNA, 2016.
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Affiliation(s)
- Aparna Srinivasa Babu
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
| | - Michael L Wells
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
| | - Oleg M Teytelboym
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
| | - Justin E Mackey
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
| | - Frank H Miller
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
| | - Benjamin M Yeh
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
| | - Richard L Ehman
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
| | - Sudhakar K Venkatesh
- From the Departments of Radiology of Mercy Catholic Medical Center, Darby, Pa (A.S.B., O.M.T., J.E.M.); Mayo Clinic, 200 First St SW, Rochester, MN 55905 (M.L.W., R.L.E., S.K.V.); Northwestern University Feinberg School of Medicine, Chicago, Ill (F.H.M.); and University of California-San Francisco School of Medicine, San Francisco, Calif (B.M.Y.)
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Hoy AM, Fallowfield JA. Editorial: non-invasive assessment of hepatic fibrosis in alpha-1 antitrypsin deficiency using magnetic resonance elastography. Aliment Pharmacol Ther 2016; 44:644-5. [PMID: 27511134 DOI: 10.1111/apt.13729] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- A M Hoy
- MRC Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK
| | - J A Fallowfield
- MRC Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK.
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Mariappan YK, Dzyubak B, Glaser KJ, Venkatesh SK, Sirlin CB, Hooker J, McGee KP, Ehman RL. Application of Modified Spin-Echo-based Sequences for Hepatic MR Elastography: Evaluation, Comparison with the Conventional Gradient-Echo Sequence, and Preliminary Clinical Experience. Radiology 2016; 282:390-398. [PMID: 27509543 DOI: 10.1148/radiol.2016160153] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Purpose To (a) evaluate modified spin-echo (SE) magnetic resonance (MR) elastographic sequences for acquiring MR images with improved signal-to-noise ratio (SNR) in patients in whom the standard gradient-echo (GRE) MR elastographic sequence yields low hepatic signal intensity and (b) compare the stiffness values obtained with these sequences with those obtained with the conventional GRE sequence. Materials and Methods This HIPAA-compliant retrospective study was approved by the institutional review board; the requirement to obtain informed consent was waived. Data obtained with modified SE and SE echo-planar imaging (EPI) MR elastographic pulse sequences with short echo times were compared with those obtained with the conventional GRE MR elastographic sequence in two patient cohorts, one that exhibited adequate liver signal intensity and one that exhibited low liver signal intensity. Shear stiffness values obtained with the three sequences in 130 patients with successful GRE-based examinations were retrospectively tested for statistical equivalence by using a 5% margin. In 47 patients in whom GRE examinations were considered to have failed because of low SNR, the SNR and confidence level with the SE-based sequences were compared with those with the GRE sequence. Results The results of this study helped confirm the equivalence of SE MR elastography and SE-EPI MR elastography to GRE MR elastography (P = .0212 and P = .0001, respectively). The SE and SE-EPI MR elastographic sequences provided substantially improved SNR and stiffness inversion confidence level in 47 patients in whom GRE MR elastography had failed. Conclusion Modified SE-based MR elastographic sequences provide higher SNR MR elastographic data and reliable stiffness measurements; thus, they enable quantification of stiffness in patients in whom the conventional GRE MR elastographic sequence failed owing to low signal intensity. The equivalence of the three sequences indicates that the current diagnostic thresholds are applicable to SE MR elastographic sequences for assessing liver fibrosis. © RSNA, 2016.
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Affiliation(s)
- Yogesh K Mariappan
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
| | - Bogdan Dzyubak
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
| | - Kevin J Glaser
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
| | - Sudhakar K Venkatesh
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
| | - Claude B Sirlin
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
| | - Jonathan Hooker
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
| | - Kiaran P McGee
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
| | - Richard L Ehman
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (Y.K.M., B.D., K.J.G., S.K.V., K.P.M., R.L.E.); and Department of Radiology, University of California, San Diego, Calif (C.B.S., J.H.)
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Ronot M, Vilgrain V. Multiparametric magnetic resonance imaging in patients with chronic liver disease: are we there yet? Liver Int 2016; 36:631-3. [PMID: 27105131 DOI: 10.1111/liv.13089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Affiliation(s)
- Maxime Ronot
- Radiology Department, Beaujon Hospital, University Hospitals Paris Nord Val de Seine, Assistance Publique-Hôpitaux de Paris, APHP, Clichy, France.,University Paris Diderot, Sorbonne Paris Cité, INSERM UMR 1149, Paris, France
| | - Valérie Vilgrain
- Radiology Department, Beaujon Hospital, University Hospitals Paris Nord Val de Seine, Assistance Publique-Hôpitaux de Paris, APHP, Clichy, France.,University Paris Diderot, Sorbonne Paris Cité, INSERM UMR 1149, Paris, France
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Fenstad ER, Dzyubak B, Oh JK, Williamson EE, F Glockner J, Young PM, Anavekar NS, Leise MD, Ehman RL, Araoz PA, Venkatesh SK. Evaluation of liver stiffness with magnetic resonance elastography in patients with constrictive pericarditis: Preliminary findings. J Magn Reson Imaging 2015; 44:81-8. [PMID: 26691749 DOI: 10.1002/jmri.25126] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Accepted: 12/01/2015] [Indexed: 01/26/2023] Open
Abstract
PURPOSE To evaluate with magnetic resonance elastography (MRE) whether patients with constrictive pericarditis (CP) have increased hepatic stiffness. CP results in reduced pericardial compliance, ventricular interdependence, and right heart failure. Patients with untreated CP may develop liver fibrosis and ultimately cirrhosis due to chronic venous congestion. Chronic venous congestion ± fibrosis may lead to increased liver stiffness. MATERIALS AND METHODS Prospectively, patients with suspected CP underwent 2D transthoracic echocardiography, cardiac MRI, and liver MRE. An automated method was used to draw regions of interest (ROIs) on the stiffness maps to calculate the mean liver stiffness in kilopascals (kPa). A t-test with α = 0.05 was performed between stiffness values of patients with positive and negative CP findings based on previously published echocardiography criteria. RESULTS Nineteen patients met inclusion criteria with a mean ± standard deviation (SD) age of 51 ± 16 years. Nine patients (47%) had CP. Mean liver stiffness trended higher in patients with CP compared to those without CP (4.04 kPa vs. 2.46; P = 0.045). Liver stiffness correlated with MRI septal bounce (P = 0.04), inferior vena cava size (P = 0.003), echo abnormal septal motion (P = 0.04), and echo mitral inflow variation >25% (P = 0.02). Only MRI septal bounce predicted CP by echocardiography (P < 0.001). CONCLUSION CP was associated with increased liver stiffness. The increased stiffness is most likely secondary to chronic hepatic venous congestion and/or fibrosis. MRE may be useful for noninvasive liver stiffness assessment in CP. J. Magn. Reson. Imaging 2016;44:81-88.
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Affiliation(s)
- Eric R Fenstad
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | - Bogdan Dzyubak
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jae K Oh
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Phillip M Young
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Nandan S Anavekar
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | - Michael D Leise
- Division of Gastroenterology, Mayo Clinic, Rochester, Minnesota, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Philip A Araoz
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
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