Multiparametric US for Identifying Metabolic Dysfunction-associated Steatohepatitis: A Prospective Multicenter Study.

Background Noninvasive evaluation of metabolic dysfunction-associated fatty liver disease (MAFLD) with multiparametric US is essential, but multicenter studies are lacking. Purpose To evaluate the ability of multiparametric US with attenuation imaging (ATI) and two-dimensional (2D) shear-wave elastography (SWE) for predicting metabolic dysfunction-associated steatohepatitis (MASH) in participants with MAFLD, regardless of hepatitis B virus infection status. Materials and Methods This prospective cross-sectional multicenter study of consecutive adults with MAFLD who underwent multiparametric US with ATI and 2D SWE, as well as liver biopsy, from September 2020 to June 2022 was conducted in 12 tertiary hospitals in China. Multivariable logistic regression was performed to assess risk factors associated with MASH. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate diagnostic performance in predicting MASH in training and validation groups (6:4 ratio of participants), and for a post hoc subgroup analysis of hepatitis B virus infection and diabetes. Results A total of 424 participants (median age, 47 years; IQR, 34-59 years; 244 male) were evaluated, including 332 participants (78%) with MASH and 92 (22%) without. Attenuation coefficient (AC) (odds ratio [OR], 3.32 [95% CI: 1.94, 5.71]; P < .001), alanine aminotransferase (ALT) level (OR, 4.42 [95% CI: 1.78, 10.94]; P = .001), and international normalized ratio (INR) (OR, 0.59 [95% CI: 0.37, 0.95]; P = .03) were independently associated with MASH. A combined model (AC, ALT, and INR) had AUCs of 0.85 (95% CI: 0.79, 0.91) and 0.77 (95% CI: 0.69, 0.85) for predicting MASH in the training and validation groups, respectively. AUC values for the subgroups with and without diabetes were 0.83 (95% CI: 0.72, 0.94) and 0.81 (95% CI: 0.75, 0.87) and for the subgroups with and without hepatitis B were 0.82 (95% CI: 0.74, 0.90) and 0.79 (95% CI: 0.71, 0.87), respectively. Conclusion A model combining AC, ALT level, and INR showed good discrimination ability for predicting MASH in participants with MAFLD. Clinical trial registration no. NCT04551716 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Reuter in this issue.