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Updated: Jul 19, 2025

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
Published on: July 21, 2023
Three-dimensional magnetic resonance elastography combining proton-density fat fraction precisely identifies
Huimin Lin1, Suhao Qiu2, Yanzhao Yang1
1Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Purpose:
Patients with metabolic dysfunction-associated steatohepatitis (MASH) and significant fibrosis (fibrosis stage≥2), known as Fibro-MASH, are at increased risk of liver-related outcomes and lower rates of spontaneous disease regression. The aim was to investigate three-dimensional MR elastography (3D-MRE) combining proton-density fat fraction (PDFF) as a means of identifying Fibro-MASH.
Methods:
Forty-eight New Zealand rabbits were fed a high-fat/cholesterol or standard diet to obtain different disease activity and fibrosis stages. Shear stiffness (SS) and Damping Ratio (DR) were derived from 3D-MRE, whereas PDFF was from a volumetric 3D imaging sequence. Steatosis grade, metabolic dysfunction-associated steatotic liver disease activity score (MAS), and fibrosis stage were diagnosed histologically. Serum markers of fibrosis and inflammation were also measured. Correlation and comparison analysis, Receiver operating characteristic curves (ROC), Delong test, logistic regression analysis, and Net reclassification improvement (NRI) were performed.
Results:
PDFF correlated with steatosis grade (rho = 0.853). SS increased with developed liver fibrosis (rho = 0.837). DR correlated with MAS grade (rho = 0.678). The areas under the ROC (AUROCs) of SS for fibrosis grading were 0.961 and 0.953 for ≥F2, and ≥ F3, respectively. All the biochemical parameters were considered but excluded from the logistic regression analysis to identify Fibro-MASH. FF, SS, and DR were finally included in the further analysis. The three-parameter model combining PDFF, SS, and DR showed significant improvement in NRI over the model combining SS and PDFF (AUROC 0.973 vs. 0.906, P = 0.081; NRI 0.28, P < 0.05).
Conclusion:
3D-MRE combining PDFF may characterize the state of fat content, disease activity and fibrosis, thus precisely identify Fibro-MASH.

