Assessment of Hepatic Fibrosis Through Radiomics Models Utilizing Diffusion-Based Virtual Magnetic Resonance Elastography.

Abstract

Objective: To investigate the potential of the radiomic features derived from the diffusion magnetic resonance imaging (MRI)-based elastography in identifying patients with different liver fibrosis stages.

Methods: Data from 151 patients with liver fibrosis, collected between January 2018 and August 2021, were included. Liver fibrosis staging was determined using histopathology from surgical resection specimens, assessed by the METAVIR scoring system, with significant fibrosis defined as ≥F2 and advanced fibrosis as ≥F3. Shifted apparent diffusion coefficient (sADC) and virtual MR elastography (vMRE) were calculated from the diffusion-weighted imaging (DWI) technique with b values of 200 and 1500 s/mm 2 . A total of 3222 radiomic features were extracted. A support vector machine was applied to build a classification model with radiomic features. We compared the results of models constructed by the mean values of MRE, radiomic features of sADC, vMRE, and sADC + vMRE in identifying significant and advanced liver fibrosis. The corresponding radiomics scores were also applied in each subject for comparison.

Results: sADC and vMRE data without clinical data provided better classification performance than that of combined features of imaging and clinical data. As compared with MRE, the radiomics model derived from sADC + vMRE yielded higher AUCs of 0.90 and 0.91 in identifying significant and advanced liver fibrosis stages, respectively. Radiomics scores achieved a comparable AUC of 0.91. The radiomics scores of sADC + vMRE were significantly correlated with the pathologic fibrosis stage.

Conclusions: The application of radiomics in sADC and vMRE performed well to identify different stages of liver fibrosis. Radiomics applied to sADC and vMRE may provide complementary information that is associated with histopathologic changes.