Diffusion-weighted MRI-based Virtual Elastography for the Assessment of Liver Fibrosis
Abstract
Background Diffusion-weighted (DW) MRI-based elastography has recently been proposed for noninvasive liver fibrosis staging but requires evaluation in a larger number of patients. Purpose To compare DW MRI and MR elastography for the assessment of liver fibrosis. Materials and Methods In this retrospective study, patients underwent MR elastography and DW MRI between November 2017 and April 2018. Shear modulus measured by MR elastography (μ MRE ) was obtained in each patient from regions of interest placed on liver stiffness maps by two independent readers. Shifted apparent diffusion coefficient (ADC) was calculated from DW MRI ( b = 200 and 1500 sec/mm 2 ) and converted to DW MRI-based virtual shear modulus (μ Diff ). MRI-based liver fibrosis stages were estimated from μ MRE and μ Diff values (F0-F4) and serum fibrosis markers were assessed. Statistical analyses included Bland-Altman plots, Bayesian prediction, and receiver operating characteristic analyses. Results Seventy-four patients (mean age, 68 years ± 9 [standard deviation]; 45 men) were evaluated. Interreader coefficient of reproducibility was 0.86 kPa for DW MRI and 1.2 kPa for MR elastography. Strong correlation between shifted ADC and μ MRE was observed ( r 2 = 0.81; P MRE and μ Diff values (mean difference, -0.02 kPa ± 0.88; P Diff showed better performance in discriminating fibrosis stages F0-F2 from F3-F4 (AUC, 0.79; 95% confidence interval: 0.69, 0.90), whereas serum markers showed slightly better results for…
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This approach was first evaluated and validated for liver-fibrosis staging.
“This approach was first evaluated and validated for liver-fibrosis staging (Kromrey et al., 2020; Le Bihan et al., 2017).”
From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Kromrey et al., 2020
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Sterling, R. K., Lissen, E., Clumeck, N., Sola, R., Correa, M. C., Montaner, J., S. Sulkowski, M., Torriani, F. J., Dieterich, D. T., Thomas, D. L., et al. (2006) · Hepatology · doi:10.1002/hep.21178 · Cited by 5,021 · see citing works
Clinical evidence for the regression of liver fibrosis
Ellis, E. L., & Mann, D. A. (2012) · Journal of Hepatology · doi:10.1016/j.jhep.2011.09.024 · Cited by 411 · see citing works
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Le Bihan, D. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1858655 · Cited by 1 · see citing works
40 Years of diffusion MRI in the brain: From history to emerging frontiers
Le Bihan, D. (2026) · Imaging Neuroscience · doi:10.1162/imag.a.1365
“This approach was first evaluated and validated for liver-fibrosis staging ( Kromrey et al., 2020; Le Bihan et al., 2017).”
Self-citation
- Authors
- Kromrey, M.-L., Le Bihan, D., Ichikawa, S., & Motosugi, U.
- Affiliations
- Kyoto University (JP)
- Venue
- Radiology
- Published
- 2020-04
- Volume
- 295
- Issue
- 1
- Pages
- 127-135
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W3005574293
- Cited by
- 90
- References
- 2
- Citations by year
- 2026: 11 · 2025: 22 · 2024: 26 · 2023: 11 · 2022: 9 · 2021: 8 · 2020: 3
- FWCI
- 3.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Radiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Ultrasound Imaging and Elastography
- Health Sciences › Medicine › Epidemiology › Liver Disease Diagnosis and Treatment
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- diffusion-weighted imaging, liver fibrosis, magnetic resonance elastography, shear modulus, apparent diffusion coefficient, liver stiffness, noninvasive fibrosis staging, serum fibrosis markers, Bayesian forecasting, receiver operating characteristic, liver cirrhosis, non-alcoholic fatty liver disease, chronic hepatitis C, chronic hepatitis B
- MeSH terms
- Aged, Female, Humans, Liver Cirrhosis, Male, Middle Aged, Retrospective Studies, Diffusion Magnetic Resonance Imaging, Elasticity Imaging Techniques, Multimodal Imaging
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