ArticleAbdominal imaging2015
Non-invasive detection of liver fibrosis: MR imaging features vs. MR elastography.
Article in Abdominal imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.
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Who cites it
50 citing papers in PubMed, 1 synthesis or guideline pooled it, 103 citations in OpenAlex.
- Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review.Frontiers in physiology · 2021Pooled it
- Advanced liver fibrosis detection using a two-stage deep learning approach on standard T2-weighted MRI.Abdominal radiology (New York) · 2026Article
- Imaging features of porto-sinusoidal vascular disorder in a case-control study: diagnostic value for differentiation from liver cirrhosis.Quantitative imaging in medicine and surgery · 2026Article
- Hepatocyte uptake ratio derived from T1 mapping for quantitative assessment of liver fibrosis.European radiology · 2026Article
- The Liver Cirrhosis Network Cohort Study: Cirrhosis Definition, Study Population, and Endpoints.The American journal of gastroenterology · 2025Article
- Two-Dimensional Shear-Wave Elastography: Accuracy in Liver Fibrosis Staging Using Magnetic Resonance Elastography as the Reference Standard.Diagnostics (Basel, Switzerland) · 2024Article
- Fully automated MRI-based convolutional neural network for noninvasive diagnosis of cirrhosis.Insights into imaging · 2024Article
- The impact of hepatic and splenic volumetric assessment in imaging for chronic liver disease: a narrative review.Insights into imaging · 2024Review
- Noninvasive diagnosis of liver cirrhosis: qualitative and quantitative imaging biomarkers.Abdominal radiology (New York) · 2024Review
- Management of alcohol withdrawal syndrome in patients with alcohol-associated liver disease.Hepatology communications · 2024Article
- Deep Learning for Computed Tomography Assessment of Hepatic Fibrosis and Cirrhosis: A Systematic Review.Mayo Clinic proceedings. Digital health · 2023Review
- Development and validation of the OSASH score to predict overall survival of hepatocellular carcinoma after surgical resection: a dual-institutional study.European radiology · 2023Article
- Ultrasound-Based Hepatic Elastography in Non-Alcoholic Fatty Liver Disease: Focus on Patients with Type 2 Diabetes.Biomedicines · 2022Review
- Missed diagnosis of cirrhosis in the inpatient setting.Journal of hospital medicine · 2022Review
- Noninvasive imaging of hepatic dysfunction: A state-of-the-art review.World journal of gastroenterology · 2022Review
- Intraindividual comparison of MRI-derived liver surface nodularity score at 1.5 T and 3 T.Abdominal radiology (New York) · 2022Article
- 1-year outcomes for lung transplantation recipients with non-alcoholic fatty liver disease.ERJ open research · 2021Article
- Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study.Diagnostics (Basel, Switzerland) · 2021Article
- Magnetic resonance quantitative susceptibility mapping in the evaluation of hepatic fibrosis in chronic liver disease: a feasibility study.Quantitative imaging in medicine and surgery · 2021Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
purposeTo compare accuracy of morphological features of liver on MRI and liver stiffness with MR elastography (MRE) for detection of significant liver fibrosis and cirrhosis. MATERIALS AND
methodsIn this retrospective study, we evaluated 62 patients who underwent liver MRI with MRE and histological confirmation of liver fibrosis within 6 months. Two radiologists, blinded to histology results, independently evaluated liver parenchyma texture, surface nodularity, signs of volumetric changes, and portal hypertension for presence of significant fibrosis and cirrhosis. Two more readers independently calculated mean liver stiffness values with MRE. Interobserver agreement was evaluated with kappa and intra-class correlation coefficient (ICC) analysis. Diagnostic accuracy was assessed with area under receiver operating characteristic (AUROC) analysis. Comparison of AUROCs of MRI and MRE was performed.
resultsLiver fibrosis was present in 37 patients. The interobserver agreement was poor to good (κ = 0.12-0.74) for MRI features and excellent for MRE (ICC 0.97, 95% CI 0.95-0.98). MRI features had 48.5%-87.9% sensitivity, 55.2%-100% specificity, and 71.5%-81.6% accuracy/for detection of significant fibrosis. MRE performed better with 100% sensitivity, 96.5% specificity, and 98.9% accuracy. For the detection of cirrhosis, MRE performed better than MRI features with 88.2% sensitivity (vs. 41.2%-82.3%), 91.1% specificity (vs. 64.4%-95.6%), and 93.5% accuracy (vs. 60.6%-80.5%). Among the MRI features, surface nodularity and overall impression had the best accuracies of 80.3% and 81.6% for detection of significant fibrosis, respectively. For cirrhosis, parenchyma texture and overall impression had the best accuracies of 80.5% and 79.7%, respectively. Overall, MRE had significantly greater AUROC than MRI features for detection of both significant fibrosis (0.98.9 vs 0.71-0.82, P < 0.001) and cirrhosis (0.93.5 vs. 0.61-0.80.5, P < 0.01).
conclusionMRE is superior to MRI for the non-invasive diagnosis of significant liver fibrosis and cirrhosis.
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