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Ozkaya E, Kennedy P, Chen J, Bane O, Dillman JR, Jhaveri KS, Ohliger MA, Rossman PJ, Tkach JA, Doucette JT, Venkatesh SK, Ehman RL, Taouli B. Precision and Test-Retest Repeatability of Stiffness Measurement with MR Elastography: A Multicenter Phantom Study. Radiology 2024; 311:e233136. [PMID: 38742971 PMCID: PMC11140535 DOI: 10.1148/radiol.233136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 03/14/2024] [Accepted: 03/26/2024] [Indexed: 05/16/2024]
Abstract
Background MR elastography (MRE) has been shown to have excellent performance for noninvasive liver fibrosis staging. However, there is limited knowledge regarding the precision and test-retest repeatability of stiffness measurement with MRE in the multicenter setting. Purpose To determine the precision and test-retest repeatability of stiffness measurement with MRE across multiple centers using the same phantoms. Materials and Methods In this study, three cylindrical phantoms made of polyvinyl chloride gel mimicking different degrees of liver stiffness in humans (phantoms 1-3: soft, medium, and hard stiffness, respectively) were evaluated. Between January 2021 and January 2022, phantoms were circulated between five different centers and scanned with 10 MRE-equipped clinical 1.5-T and 3-T systems from three major vendors, using two-dimensional (2D) gradient-recalled echo (GRE) imaging and/or 2D spin-echo (SE) echo-planar imaging (EPI). Similar MRE acquisition parameters, hardware, and reconstruction algorithms were used at each center. Mean stiffness was measured by a single observer for each phantom and acquisition on a single section. Stiffness measurement precision and same-session test-retest repeatability were assessed using the coefficient of variation (CV) and the repeatability coefficient (RC), respectively. Results The mean precision represented by the CV was 5.8% (95% CI: 3.8, 7.7) for all phantoms and both sequences combined. For all phantoms, 2D GRE achieved a CV of 4.5% (95% CI: 3.3, 5.7) whereas 2D SE EPI achieved a CV of 7.8% (95% CI: 3.1, 12.6). The mean RC of stiffness measurement was 5.8% (95% CI: 3.7, 7.8) for all phantoms and both sequences combined, 4.9% (95% CI: 2.7, 7.0) for 2D GRE, and 7.0% (95% CI: 2.9, 11.2) for 2D SE EPI (all phantoms). Conclusion MRE had excellent in vitro precision and same-session test-retest repeatability in the multicenter setting when similar imaging protocols, hardware, and reconstruction algorithms were used. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Tang in this issue.
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Affiliation(s)
| | | | - Jun Chen
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Octavia Bane
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Jonathan R. Dillman
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Kartik S. Jhaveri
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Michael A. Ohliger
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Phillip J. Rossman
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Jean A. Tkach
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - John T. Doucette
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Sudhakar K. Venkatesh
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Richard L. Ehman
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
| | - Bachir Taouli
- From the BioMedical Engineering and Imaging Institute (E.O., P.K.,
O.B., B.T.) and Departments of Diagnostic, Molecular and Interventional
Radiology (E.O., P.K., O.B., B.T.) Environmental Medicine and Public Health
(J.T.D.), Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, New York,
NY 10029; Department of Radiology, Mayo Clinic, Rochester, Minn (J.C., P.J.R.,
S.K.V., R.L.E.); Department of Radiology, Nanjing University Medical School
Affiliated Drum Tower Hospital, Nanjing, China (J.C.); Department of Radiology,
Cincinnati Children’s Hospital Medical Center, University of Cincinnati
College of Medicine, Cincinnati, Ohio (J.R.D., J.A.T.); Joint Department of
Medical Imaging, University Health Network, Mount Sinai Hospital, and
Women’s College Hospital, University of Toronto, Toronto, Canada
(K.S.J.); Department of Radiology and Biomedical Imaging, University of
California, San Francisco, Calif (M.A.O.); and Department of Radiology,
Zuckerberg San Francisco General Hospital, San Francisco, Calif (M.A.O.)
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Tang A. Liver Stiffness at MR Elastography: A Surrogate Biomarker for Staging Liver Fibrosis, Predicting Clinical Outcomes, and Selecting Patients. Radiology 2024; 311:e240890. [PMID: 38742968 DOI: 10.1148/radiol.240890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Affiliation(s)
- An Tang
- From the Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, 1058 rue Saint-Denis, Montréal, QC, Canada H2X 3J4; Department of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada; and Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada
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Moura Cunha G, Fan B, Navin PJ, Olivié D, Venkatesh SK, Ehman RL, Sirlin CB, Tang A. Interpretation, Reporting, and Clinical Applications of Liver MR Elastography. Radiology 2024; 310:e231220. [PMID: 38470236 PMCID: PMC10982829 DOI: 10.1148/radiol.231220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 11/21/2023] [Accepted: 11/24/2023] [Indexed: 03/13/2024]
Abstract
Chronic liver disease is highly prevalent and often leads to fibrosis or cirrhosis and complications such as liver failure and hepatocellular carcinoma. The diagnosis and staging of liver fibrosis is crucial to determine management and mitigate complications. Liver biopsy for histologic assessment has limitations such as sampling bias and high interreader variability that reduce precision, which is particularly challenging in longitudinal monitoring. MR elastography (MRE) is considered the most accurate noninvasive technique for diagnosing and staging liver fibrosis. In MRE, low-frequency vibrations are applied to the abdomen, and the propagation of shear waves through the liver is analyzed to measure liver stiffness, a biomarker for the detection and staging of liver fibrosis. As MRE has become more widely used in clinical care and research, different contexts of use have emerged. This review focuses on the latest developments in the use of MRE for the assessment of liver fibrosis; provides guidance for image acquisition and interpretation; summarizes diagnostic performance, along with thresholds for diagnosis and staging of liver fibrosis; discusses current and emerging clinical applications; and describes the latest technical developments.
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Affiliation(s)
- Guilherme Moura Cunha
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Boyan Fan
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Patrick J. Navin
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Damien Olivié
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Sudhakar K. Venkatesh
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Richard L. Ehman
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - Claude B. Sirlin
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
| | - An Tang
- From the Department of Radiology, University of Washington, Seattle,
Wash (G.M.C.); Department of Radiology, Université Laval, Québec,
Québec, Canada (B.F.); Department of Radiology, Mayo Clinic, Rochester,
Minn (P.J.N., S.K.V., R.L.E.); Department of Radiology, Centre Hospitalier de
l'Université de Montréal, 1058 Rue Saint-Denis,
Montréal, QC, Canada H2X 3J4 (D.O., A.T.); and Department of Radiology,
University of California San Diego, San Diego, Calif (C.B.S.)
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Wan Q, Peng H, Liu F, Liu X, Cheng C, Tie C, Deng J, Lyu J, Jia Y, Wang Y, Zheng H, Liang D, Liu X, Zou C. Ability of dynamic gadoxetic acid-enhanced magnetic resonance imaging combined with water-specific T1 mapping to reflect inflammation in a rat model of early-stage nonalcoholic steatohepatitis. Quant Imaging Med Surg 2024; 14:1591-1601. [PMID: 38415124 PMCID: PMC10895110 DOI: 10.21037/qims-23-482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 11/23/2023] [Indexed: 02/29/2024]
Abstract
Background Gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) has shown potential in reflecting the hepatic function alterations in nonalcoholic steatohepatitis (NASH). The purpose of this study was to evaluate whether Gd-EOB-DTPA combined with water-specific T1 (wT1) mapping can be used to detect liver inflammation in the early-stage of NASH in rats. Methods In this study, 54 rats with methionine- and choline-deficient (MCD) diet-induced NASH and 10 normal control rats were examined. A multiecho variable flip angle gradient echo (VFA-GRE) sequence was performed and repeated 40 times after the injection of Gd-EOB-DTPA. The wT1 of the liver and the reduction rate of wT1 (rrT1) were calculated. All rats were histologically evaluated and grouped according to the NASH Clinical Research Network scoring system. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect the expression of Gd-EOB-DTPA transport genes. Analysis of variance and least significant difference tests were used for multiple comparisons of quantitative results between all groups. Multiple regression analysis was applied to identify variables associated with precontrast wT1 (wT1pre), and receiver operating characteristic (ROC) analysis was performed to assess the diagnostic performance. Results The rats were grouped according to inflammatory stage (G0 =4, G1 =15, G2 =12, G3 =23) and fibrosis stage (F0 =26, F1 =19, F2 =9). After the infusion of Gd-EOB-DTPA, the rrT1 showed significant differences between the control and NASH groups (P<0.05) but no difference between the different inflammation and fibrosis groups at any time points. The areas under curve (AUCs) of rrT1 at 10, 20, and 30 minutes were only 0.53, 0.58, and 0.61, respectively, for differentiating between low inflammation grade (G0 + G1) and high inflammation grade (G2 + G3). The MRI findings were verified by qRT-PCR examination, in which the Gd-EOB-DTPA transporter expressions showed no significant differences between any inflammation groups. Conclusions The wT1 mapping quantitative method combined with Gd-EOB-DTPA was not capable of discerning the inflammation grade in a rat model of early-stage NASH.
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Affiliation(s)
- Qian Wan
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Hao Peng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Feng Liu
- Peking University People’s Hospital, Peking University Hepatology Institute, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Diseases, Beijing International Cooperation Base for Science and Technology on NAFLD Diagnosis, Beijing, China
| | - Xiaoyi Liu
- Departments of Radiology, Peking University People’s Hospital, Beijing, China
| | - Chuanli Cheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Changjun Tie
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jie Deng
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Jianxun Lyu
- Department of Radiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Yizhen Jia
- Departments of Research Services, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - Yi Wang
- Departments of Radiology, Peking University People’s Hospital, Beijing, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Dong Liang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xin Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Chao Zou
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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Lo CM, Hung PH. Predictive stroke risk model with vision transformer-based Doppler features. Med Phys 2024; 51:126-138. [PMID: 38043124 DOI: 10.1002/mp.16861] [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: 04/08/2023] [Revised: 11/17/2023] [Accepted: 11/17/2023] [Indexed: 12/05/2023] Open
Abstract
BACKGROUND Acute stroke is the leading cause of death and disability globally, with an estimated 16 million cases each year. The progression of carotid stenosis reduces blood flow to the intracranial vasculature, causing stroke. Early recognition of ischemic stroke is crucial for disease treatment and management. PURPOSE A computer-aided diagnosis (CAD) system was proposed in this study to rapidly evaluate ischemic stroke in carotid color Doppler (CCD). METHODS Based on the ground truth from the clinical examination report, the vision transformer (ViT) features extracted from all CCD images (513 stroke and 458 normal images) were combined in machine learning classifiers to generate the likelihood of ischemic stroke for each image. The pretrained weights from ImageNet reduced the time-consuming training process. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve were calculated to evaluate the stroke prediction model. The chi-square test, DeLong test, and Bonferroni correction for multiple comparisons were applied to deal with the type-I error. Only p values equal to or less than 0.00125 were considered to be statistically significant. RESULTS The proposed CAD system achieved an accuracy of 89%, a sensitivity of 94%, a specificity of 84%, and an area under the receiver operating characteristic curve of 0.95, outperforming the convolutional neural networks AlexNet (82%, p < 0.001), Inception-v3 (78%, p < 0.001), ResNet101 (84%, p < 0.001), and DenseNet201 (85%, p < 0.01). The computational time in model training was only 30 s, which would be efficient and practical in clinical use. CONCLUSIONS The experiment shows the promising use of CCD images in stroke estimation. Using the pretrained ViT architecture, the image features can be automatically and efficiently generated without human intervention. The proposed CAD system provides a rapid and reliable suggestion for diagnosing ischemic stroke.
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Affiliation(s)
- Chung-Ming Lo
- Graduate Institute of Library, Information and Archival Studies, National Chengchi University, Taipei, Taiwan
| | - Peng-Hsiang Hung
- Department of Radiology, Mackay Memorial Hospital, Taipei, Taiwan
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Gunes A, Schmitt C, Bilodeau L, Huet C, Belblidia A, Baldwin C, Giard JM, Biertho L, Lafortune A, Couture CY, Cheung A, Nguyen BN, Galun E, Bémeur C, Bilodeau M, Laplante M, Tang A, Faraj M, Estall JL. IL-6 Trans-Signaling Is Increased in Diabetes, Impacted by Glucolipotoxicity, and Associated With Liver Stiffness and Fibrosis in Fatty Liver Disease. Diabetes 2023; 72:1820-1834. [PMID: 37757741 PMCID: PMC10658070 DOI: 10.2337/db23-0171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023]
Abstract
Many people living with diabetes also have nonalcoholic fatty liver disease (NAFLD). Interleukin-6 (IL-6) is involved in both diseases, interacting with both membrane-bound (classical) and circulating (trans-signaling) soluble receptors. We investigated whether secretion of IL-6 trans-signaling coreceptors are altered in NAFLD by diabetes and whether this might associate with the severity of fatty liver disease. Secretion patterns were investigated with use of human hepatocyte, stellate, and monocyte cell lines. Associations with liver pathology were investigated in two patient cohorts: 1) biopsy-confirmed steatohepatitis and 2) class 3 obesity. We found that exposure of stellate cells to high glucose and palmitate increased IL-6 and soluble gp130 (sgp130) secretion. In line with this, plasma sgp130 in both patient cohorts positively correlated with HbA1c, and subjects with diabetes had higher circulating levels of IL-6 and trans-signaling coreceptors. Plasma sgp130 strongly correlated with liver stiffness and was significantly increased in subjects with F4 fibrosis stage. Monocyte activation was associated with reduced sIL-6R secretion. These data suggest that hyperglycemia and hyperlipidemia can directly impact IL-6 trans-signaling and that this may be linked to enhanced severity of NAFLD in patients with concomitant diabetes. ARTICLE HIGHLIGHTS IL-6 and its circulating coreceptor sgp130 are increased in people with fatty liver disease and steatohepatitis. High glucose and lipids stimulated IL-6 and sgp130 secretion from hepatic stellate cells. sgp130 levels correlated with HbA1c, and diabetes concurrent with steatohepatitis further increased circulating levels of all IL-6 trans-signaling mediators. Circulating sgp130 positively correlated with liver stiffness and hepatic fibrosis. Metabolic stress to liver associated with fatty liver disease might shift the balance of IL-6 classical versus trans-signaling, promoting liver fibrosis that is accelerated by diabetes.
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Affiliation(s)
- Aysim Gunes
- Institut de recherches cliniques de Montréal (IRCM), Montreal, Quebec, Canada
- Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Montreal Diabetes Research Centre, Montreal, Quebec, Canada
| | - Clémence Schmitt
- Institut de recherches cliniques de Montréal (IRCM), Montreal, Quebec, Canada
- Programmes de biologie moléculaire, Faculté de médecine, Université de Montréal, Montreal, Quebec, Canada
| | - Laurent Bilodeau
- Département de radiologie, Centre hospitalier de l’Université de Montréal (CHUM), Montreal, Quebec, Canada
| | - Catherine Huet
- Département de radiologie, Centre hospitalier de l’Université de Montréal (CHUM), Montreal, Quebec, Canada
| | - Assia Belblidia
- Département de radiologie, Centre hospitalier de l’Université de Montréal (CHUM), Montreal, Quebec, Canada
| | - Cindy Baldwin
- Institut de recherches cliniques de Montréal (IRCM), Montreal, Quebec, Canada
| | - Jeanne-Marie Giard
- Liver Unit, Centre hospitalier de l’Université de Montréal (CHUM), Département de médecine, Université de Montréal, Montreal, Quebec, Canada
| | - Laurent Biertho
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Quebec, Canada
- Département de chirurgie, Faculté de médecine, Université Laval, Quebec City, Quebec, Canada
| | - Annie Lafortune
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Quebec, Canada
- Département de chirurgie, Faculté de médecine, Université Laval, Quebec City, Quebec, Canada
| | - Christian Yves Couture
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Quebec, Canada
- Département de biologie moléculaire, biochimie médicale et pathologie, Université Laval, Quebec City, Quebec, Canada
| | - Angela Cheung
- Gastroenterology and Hepatology, Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Bich N. Nguyen
- Département de pathologie et biologie cellulaire, Université de Montréal, Montreal, Quebec, Canada
| | - Eithan Galun
- Goldyne Savad Institute of Gene Therapy, Hadassah Hebrew University Hospital, Jerusalem, Israel
| | - Chantal Bémeur
- Département de nutrition, Université de Montréal, Montreal, Quebec, Canada
- Labo HépatoNeuro, Centre de recherche du CHUM, Montreal, Quebec, Canada
| | - Marc Bilodeau
- Liver Unit, Centre hospitalier de l’Université de Montréal (CHUM), Département de médecine, Université de Montréal, Montreal, Quebec, Canada
| | - Mathieu Laplante
- Montreal Diabetes Research Centre, Montreal, Quebec, Canada
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Quebec City, Quebec, Canada
| | - An Tang
- Département de radiologie, Centre hospitalier de l’Université de Montréal (CHUM), Montreal, Quebec, Canada
| | - May Faraj
- Institut de recherches cliniques de Montréal (IRCM), Montreal, Quebec, Canada
- Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Montreal Diabetes Research Centre, Montreal, Quebec, Canada
- Département de nutrition, Université de Montréal, Montreal, Quebec, Canada
| | - Jennifer L. Estall
- Institut de recherches cliniques de Montréal (IRCM), Montreal, Quebec, Canada
- Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Montreal Diabetes Research Centre, Montreal, Quebec, Canada
- Programmes de biologie moléculaire, Faculté de médecine, Université de Montréal, Montreal, Quebec, Canada
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Yazdani L, Rafati I, Gesnik M, Nicolet F, Chayer B, Gilbert G, Volniansky A, Olivié D, Giard JM, Sebastiani G, Nguyen BN, Tang A, Cloutier G. Ultrasound Shear Wave Attenuation Imaging for Grading Liver Steatosis in Volunteers and Patients With Non-alcoholic Fatty Liver Disease: A Pilot Study. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:2264-2272. [PMID: 37482477 DOI: 10.1016/j.ultrasmedbio.2023.06.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/26/2023] [Accepted: 06/27/2023] [Indexed: 07/25/2023]
Abstract
OBJECTIVE The aims of the work described here were to assess shear wave attenuation (SWA) in volunteers and patients with non-alcoholic fatty liver disease (NAFLD) and compare its diagnostic performance with that of shear wave dispersion (SWD), magnetic resonance imaging (MRI) proton density fat fraction (PDFF) and biopsy. METHODS Forty-nine participants (13 volunteers and 36 NAFLD patients) were enrolled. Ultrasound and MRI examinations were performed in all participants. Biopsy was also performed in patients. SWA was used to assess histopathology grades as potential confounders. The areas under curves (AUCs) of SWA, SWD and MRI-PDFF were assessed in different steatosis grades by biopsy. Youden's thresholds of SWA were obtained for steatosis grading while using biopsy or MRI-PDFF as the reference standard. RESULTS Spearman's correlations of SWA with histopathology (steatosis, inflammation, ballooning and fibrosis) were 0.89, 0.73, 0.62 and 0.31, respectively. Multiple linear regressions of SWA confirmed the correlation with steatosis grades (adjusted R2 = 0.77, p < 0.001). The AUCs of MRI-PDFF, SWA and SWD were respectively 0.97, 0.99 and 0.94 for S0 versus ≥S1 (p > 0.05); 0.94, 0.98 and 0.78 for ≤S1 versus ≥S2 (both MRI-PDFF and SWA were higher than SWD, p < 0.05); and 0.90, 0.93 and 0.68 for ≤S2 versus S3 (both SWA and MRI-PDFF were higher than SWD, p < 0.05). SWA's Youden thresholds (Np/m/Hz) (sensitivity, specificity) for S0 versus ≥S1, ≤S1 versus ≥S2 and ≤S2 versus S3 were 1.05 (1.00, 0.92), 1.37 (0.96, 0.96) and 1.51 (0.83, 0.87), respectively. These values were 1.16 (1.00, 0.81), 1.49 (0.91, 0.82) and 1.67 (0.87, 0.92) when considering MRI-PDFF as the reference standard. CONCLUSION In this pilot study, SWA increased with increasing steatosis grades, and its diagnostic performance was higher than that of SWD but equivalent to that of MRI-PDFF.
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Affiliation(s)
- Ladan Yazdani
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada
| | - Iman Rafati
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada
| | - Marc Gesnik
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Frank Nicolet
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Boris Chayer
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Guillaume Gilbert
- MR Clinical Science, Philips Healthcare Canada, Markham, ON, Canada; Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada
| | - Anton Volniansky
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada
| | - Damien Olivié
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada
| | | | - Giada Sebastiani
- Division of Gastroenterology and Hepatology, McGill University Health Centre, Montreal, QC, Canada
| | - Bich N Nguyen
- Service of Pathology, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, QC, Canada
| | - An Tang
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada; Laboratory of Clinical Image Processing, CRCHUM, Montréal, QC, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada; Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada.
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Zheng S, He K, Zhang L, Li M, Zhang H, Gao P. Conventional and artificial intelligence-based computed tomography and magnetic resonance imaging quantitative techniques for non-invasive liver fibrosis staging. Eur J Radiol 2023; 165:110912. [PMID: 37290363 DOI: 10.1016/j.ejrad.2023.110912] [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: 03/13/2023] [Revised: 05/25/2023] [Accepted: 05/30/2023] [Indexed: 06/10/2023]
Abstract
Chronic liver disease (CLD) ultimately develops into liver fibrosis and cirrhosis and is a major public health problem globally. The assessment of liver fibrosis is important for patients with CLD for prognostication, treatment decisions, and surveillance. Liver biopsies are traditionally performed to determine the stage of liver fibrosis. However, the risks of complications and technical limitations restrict their application to screening and sequential monitoring in clinical practice. CT and MRI are essential for evaluating cirrhosis-associated complications in patients with CLD, and several non-invasive methods based on them have been proposed. Artificial intelligence (AI) techniques have also been applied to stage liver fibrosis. This review aimed to explore the values of conventional and AI-based CT and MRI quantitative techniques for non-invasive liver fibrosis staging and summarized their diagnostic performance, advantages, and limitations.
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Affiliation(s)
- Shuang Zheng
- Department of Radiology, the First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, Jilin, China.
| | - Kan He
- Department of Radiology, the First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, Jilin, China.
| | - Lei Zhang
- Department of Radiology, the First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, Jilin, China.
| | - Mingyang Li
- Department of Radiology, the First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, Jilin, China.
| | - Huimao Zhang
- Department of Radiology, the First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, Jilin, China.
| | - Pujun Gao
- Department of Hepatology, the First Hospital of Jilin University, No. 71 Xinmin Street, Changchun, Jilin, China.
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Liver stiffness assessed by magnetic resonance elastography predicts clinical outcomes in patients with heart failure and without chronic liver disease. Eur Radiol 2023; 33:2062-2074. [PMID: 36326882 DOI: 10.1007/s00330-022-09209-0] [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: 06/22/2022] [Revised: 09/25/2022] [Accepted: 09/30/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVES Evaluation of liver stiffness (LS) by magnetic resonance elastography (MRE) is useful for estimating right atrial pressure (RAP) in patients with heart failure (HF). However, its prognostic implications are unclear. We sought to investigate whether LS measured by MRE (LS-MRE) could predict clinical outcomes in patients with HF. METHODS We prospectively examined 207 consecutive HF patients between April 2018 and May 2021 after excluding those with organic liver disease. All patients underwent 3.0-T MRE. The primary outcome of interest was the composite of all-cause death and hospitalisation for HF. RESULTS During a median follow-up period of 720 (interquartile range [IQR] 434-1013) days, the primary outcome occurred in 44 patients (21%), including 15 (7%) all-cause deaths and 29 (14%) hospitalisations for HF. The patients were divided into two groups according to median LS-MRE of 2.54 (IQR 2.34-2.82) kPa. Patients with higher LS-MRE showed a higher incidence of the primary outcome compared to those with lower LS-MRE (p < 0.001). Multivariable Cox regression analyses revealed that LS-MRE value was independently associated with the risk of adverse events (hazard ratio 2.49, 95% confidence interval 1.46-4.24). In multivariable linear regression, RAP showed a stronger correlation with LS-MRE (β coefficient = 0.31, p < 0.001) compared to markers related to liver fibrosis. CONCLUSIONS In patients without chronic liver disease and presenting with HF, elevated LS-MRE was independently associated with worse clinical outcomes. Elevated LS-MRE may be useful for risk stratification in patients with HF and without chronic liver disease. KEY POINTS • Magnetic resonance elastography (MRE) is an emerging non-invasive imaging technique for evaluating liver stiffness (LS) which can estimate right atrial pressure. • Elevated LS-MRE, which mainly reflects liver congestion, was independently associated with worse clinical outcomes in patients with heart failure. • The assessment of LS-MRE would be useful for stratifying the risk of adverse events in heart failure patients without chronic liver disease.
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10
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Fotaki A, Velasco C, Prieto C, Botnar RM. Quantitative MRI in cardiometabolic disease: From conventional cardiac and liver tissue mapping techniques to multi-parametric approaches. Front Cardiovasc Med 2023; 9:991383. [PMID: 36756640 PMCID: PMC9899858 DOI: 10.3389/fcvm.2022.991383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 12/29/2022] [Indexed: 01/24/2023] Open
Abstract
Cardiometabolic disease refers to the spectrum of chronic conditions that include diabetes, hypertension, atheromatosis, non-alcoholic fatty liver disease, and their long-term impact on cardiovascular health. Histological studies have confirmed several modifications at the tissue level in cardiometabolic disease. Recently, quantitative MR methods have enabled non-invasive myocardial and liver tissue characterization. MR relaxation mapping techniques such as T1, T1ρ, T2 and T2* provide a pixel-by-pixel representation of the corresponding tissue specific relaxation times, which have been shown to correlate with fibrosis, altered tissue perfusion, oedema and iron levels. Proton density fat fraction mapping approaches allow measurement of lipid tissue in the organ of interest. Several studies have demonstrated their utility as early diagnostic biomarkers and their potential to bear prognostic implications. Conventionally, the quantification of these parameters by MRI relies on the acquisition of sequential scans, encoding and mapping only one parameter per scan. However, this methodology is time inefficient and suffers from the confounding effects of the relaxation parameters in each single map, limiting wider clinical and research applications. To address these limitations, several novel approaches have been proposed that encode multiple tissue parameters simultaneously, providing co-registered multiparametric information of the tissues of interest. This review aims to describe the multi-faceted myocardial and hepatic tissue alterations in cardiometabolic disease and to motivate the application of relaxometry and proton-density cardiac and liver tissue mapping techniques. Current approaches in myocardial and liver tissue characterization as well as latest technical developments in multiparametric quantitative MRI are included. Limitations and challenges of these novel approaches, and recommendations to facilitate clinical validation are also discussed.
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Affiliation(s)
- Anastasia Fotaki
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom,*Correspondence: Anastasia Fotaki,
| | - Carlos Velasco
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile,Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile,Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile
| | - René M. Botnar
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom,School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile,Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile,Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile
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Gosalia D, Ratziu V, Stanicic F, Vukicevic D, Zah V, Gunn N, Halegoua-DeMarzio D, Tran T. Accuracy of Noninvasive Diagnostic Tests for the Detection of Significant and Advanced Fibrosis Stages in Nonalcoholic Fatty Liver Disease: A Systematic Literature Review of the US Studies. Diagnostics (Basel) 2022; 12:2608. [PMID: 36359453 PMCID: PMC9689671 DOI: 10.3390/diagnostics12112608] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 10/18/2022] [Accepted: 10/24/2022] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND The purpose of this systematic literature review (SLR) was to evaluate the accuracy of noninvasive diagnostic tools in detecting significant or advanced (F2/F3) fibrosis among patients with nonalcoholic fatty liver (NAFL) in the US healthcare context. METHODS The SLR was conducted in PubMed and Web of Science, with an additional hand search of public domains and citations, in line with the PRISMA statement. The study included US-based original research on diagnostic test sensitivity, specificity and accuracy. RESULTS Twenty studies were included in qualitative evidence synthesis. Imaging techniques with the highest diagnostic accuracy in F2/F3 detection and differentiation were magnetic resonance elastography and vibration-controlled transient elastography. The most promising standard blood biomarkers were NAFLD fibrosis score and FIB-4. The novel diagnostic tools showed good overall accuracy, particularly a score composed of body mass index, GGT, 25-OH-vitamin D, and platelet count. The novel approaches in liver fibrosis detection successfully combine imaging techniques and blood biomarkers. CONCLUSIONS While noninvasive techniques could overcome some limitations of liver biopsy, a tool that would provide a sufficiently sensitive and reliable estimate of changes in fibrosis development and regression is still missing.
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Affiliation(s)
- Dhaval Gosalia
- Department of Commercial Strategy and Operations, Glympse Bio, Cambridge, MA 02140, USA
| | - Vlad Ratziu
- Department of Medicine, Medicine Sorbonne University, 75013 Paris, France
| | - Filip Stanicic
- Health Economics and Outcomes Research Department, ZRx Outcomes Research Inc., Mississauga, ON L5A 2X7, Canada
| | - Djurdja Vukicevic
- Health Economics and Outcomes Research Department, ZRx Outcomes Research Inc., Mississauga, ON L5A 2X7, Canada
| | - Vladimir Zah
- Health Economics and Outcomes Research Department, ZRx Outcomes Research Inc., Mississauga, ON L5A 2X7, Canada
| | - Nadege Gunn
- Department of Hepatology, Impact Research Institute, Waco, TX 76710, USA
| | - Dina Halegoua-DeMarzio
- Department of Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Tram Tran
- Department of Medicine, UCLA Santa Monica Medical Center, Santa Monica, CA 90404, USA
- Department of Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA
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Muacevic A, Adler JR. Accuracy of Ultrasonography vs. Elastography in Patients With Non-alcoholic Fatty Liver Disease: A Systematic Review. Cureus 2022; 14:e29967. [PMID: 36381908 PMCID: PMC9637432 DOI: 10.7759/cureus.29967] [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: 08/31/2022] [Accepted: 10/05/2022] [Indexed: 01/25/2023] Open
Abstract
Ultrasonography and elastography are the most widely used imaging modalities for diagnosing non-alcoholic fatty liver disease. This study aimed to assess and compare the diagnostic accuracy in patients with non-alcoholic fatty liver disease/non-alcoholic steatohepatitis. This systematic review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search was done for the past seven years using Pubmed, Pubmed Central, Cochrane, and Google Scholar databases on Jun 29, 2022. Studies were included based on the following predefined criteria: observational studies, randomized controlled trial (RCT), comparative studies, studies using liver biopsy or MRI proton density fat fraction (MRI PDFF) as a reference standard, ultrasonography, and elastography with measures of their diagnostic accuracy like sensitivity (SN), specificity (SP), area under the receiver operating characteristic (AUROC) curve, and English language. The data were extracted on a predefined template. The final twelve eligible studies were assessed using the quality assessment of diagnostic accuracy tool (QUADS-2). Most studies focused on elastography techniques, and the remaining focused on quantitative ultrasonography methods like the controlled attenuation parameter (CAP) and attenuation coefficient (AC). Only one study was available for the evaluation of qualitative ultrasonography. MRI was generally found superior to other diagnostic tests for determining liver stiffness through magnetic resonance elastography (MRE) and steatosis through MRI PDFF. Data assessing the comparative diagnostic accuracy of the two tests were inconclusive.
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