Magnetic resonance elastography-based prediction model for hepatic decompensation in NAFLD: A multicenter cohort study.

BACKGROUND AND AIMS: Magnetic resonance elastography (MRE) is an accurate, continuous biomarker of liver fibrosis; however, the optimal combination with clinical factors to predict the risk of incident hepatic decompensation is unknown. Therefore, we aimed to develop and validate an MRE-based prediction model for hepatic decompensation for patients with NAFLD. APPROACH AND RESULTS: This international multicenter cohort study included participants with NAFLD undergoing MRE from 6 hospitals. A total of 1254 participants were randomly assigned as training (n = 627) and validation (n = 627) cohorts. The primary end point was hepatic decompensation, defined as the first occurrence of variceal hemorrhage, ascites, or HE. Covariates associated with hepatic decompensation on Cox-regression were combined with MRE to construct a risk prediction model in the training cohort and then tested in the validation cohort. The median (IQR) age and MRE values were 61 (18) years and 3.5 (2.5) kPa in the training cohort and 60 (20) years and 3.4 (2.5) kPa in the validation cohort, respectively. The MRE-based multivariable model that included age, MRE, albumin, aspartate aminotransferase, and platelets had excellent discrimination for the 3- and 5-year risk of hepatic decompensation (c-statistic 0.912 and 0.891, respectively) in the training cohort. The diagnostic accuracy remained consistent in the validation cohort with a c-statistic of 0.871 and 0.876 for hepatic decompensation at 3 and 5 years, respectively, and was superior to Fibrosis-4 in both cohorts ( p < 0.05). CONCLUSIONS: An MRE-based prediction model allows for accurate prediction of hepatic decompensation and assists in the risk stratification of patients with NAFLD.

Direct Comparison of Quantitative US versus Controlled Attenuation Parameter for Liver Fat Assessment Using MRI Proton Density Fat Fraction as the Reference Standard in Patients Suspected of Having NAFLD.

Background MRI-derived proton density fat fraction (PDFF) is an accurate, reliable, and safe biologic marker for use in the noninvasive diagnosis of hepatic steatosis in patients with nonalcoholic fatty liver disease (NAFLD). Because of the cost and limited availability of MRI, it is necessary to develop an accurate method to diagnose NAFLD with potential point-of-care access. Purpose To compare the diagnostic accuracy of the quantitative US (QUS) fat fraction (FF) estimator with that of the controlled attenuation parameter (CAP) in the diagnosis of NAFLD using contemporaneous MRI-derived PDFF as the reference standard. Materials and Methods Participants with or suspected of having NAFLD were prospectively recruited at the NAFLD Research Center between July 2015 and July 2019. All participants underwent MRI-derived PDFF measurement, transient elastography with CAP measurement, and QUS. QUS FF was derived using computed QUS parameters from the acquired radiofrequency US data using a calibrated reference phantom. The area under the receiver operating characteristic curve (AUC) was calculated to assess the accuracy of QUS FF and CAP in the diagnosis of hepatic steatosis (defined as MRI-derived PDFF ≥ 5%). AUCs were compared using the DeLong test. Results A total of 123 participants were included (mean age, 52 years ± 13 [SD]; 67 [54%] women). Of these participants, 100 (81%) had MRI-derived PDFF of 5% or more. QUS FF had a significantly higher AUC for diagnosis of NAFLD than did CAP (0.92 [95% CI: 0.87, 0.98] vs 0.79 [95% CI: 0.67, 0.90], P = .03). QUS FF had a sensitivity of 98% (98 of 100) and a specificity of 48% (11 of 23). CAP had a sensitivity of 87% (87 of 100) and a specificity of 57% (13 of 23). Conclusion The quantitative US fat fraction estimator is more accurate than the controlled attenuation parameter in the diagnosis of hepatic steatosis in patients with or suspected of having nonalcoholic fatty liver disease. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Ito in this issue.

Clinical utility of 30% relative decline in MRI-PDFF in predicting fibrosis regression in non-alcoholic fatty liver disease.

OBJECTIVE: Emerging data suggest that a 30% relative decline in liver fat, as assessed by MRI-proton density fat fraction (MRI-PDFF), may be associated with Non-Alcoholic Fatty Liver Disease Activity Score improvement, but the association between decline in MRI-PDFF and fibrosis regression is not known. Therefore, we aimed to examine the association between ≥30% relative decline in MRI-PDFF and fibrosis regression in non-alcoholic fatty liver disease (NAFLD). DESIGN: This prospective study included 100 well-characterised patients with biopsy-proven NAFLD with paired contemporaneous MRI-PDFF assessment at two time points. MRI-PDFF response was defined as ≥30% relative decline in MRI-PDFF. The primary outcome was ≥1 stage histological fibrosis regression. RESULTS: The median (IQR) age was 54 (43-62) years and body mass index was 31.9 (29-36) kg/m2. In multivariable-adjusted logistic regression analysis (adjusted for age, gender, diabetes status, race/ethnicity, interval between biopsies, gamma-glutamyl transferase, liver stiffness by magnetic resonance elastography and change in platelet counts), MRI-PDFF response was an independent predictor of fibrosis regression with an adjusted OR of 6.46 (95% CI 1.1 to 37.0, p=0.04). The proportion of patients with MRI-PDFF response with fibrosis regression, no change in fibrosis and fibrosis progression was 40.0%, 24.6% and 13.0%, respectively, and the proportion of patients with MRI-PDFF response increased with fibrosis regression (p=0.03). CONCLUSION: ≥30% reduction in MRI-PDFF in early phase trials can provide a useful estimate of odds of ≥1 stage improvement in fibrosis. These data may be helpful in sample size estimation in non-alcoholic steatohepatitis trials.

MRE combined with FIB-4 (MEFIB) index in detection of candidates for pharmacological treatment of NASH-related fibrosis.

OBJECTIVE: Patients with non-alcoholic fatty liver disease (NAFLD) with ≥stage 2 fibrosis are at increased risk for liver-related mortality and are candidates for pharmacological therapies for treatment of NAFLD. The aim of this prospective cohort study is to examine the diagnostic accuracy of MR elastography (MRE) combined with fibrosis-4 (FIB-4) in diagnosing ≥stage 2 fibrosis (candidates for pharmacological therapies). DESIGN: This is a cross-sectional analysis of a prospective cohort (University of California at San Diego (UCSD)-NAFLD) including 238 consecutive patients with contemporaneous MRE and biopsy-proven NAFLD. Non-alcoholic steatohepatitis-Clinical Research Network-Histologic Scoring System was used to assess histology. The radiologist and pathologist were blinded to clinical, pathological and imaging data, respectively. Receiver operating characteristics (ROCs) were determined to examine the diagnostic accuracy of MRE and FIB-4 for diagnosis of ≥stage 2 fibrosis in NAFLD. We then validated these findings in an independent validation cohort derived from Yokohama City University in Japan (Japan-NAFLD Cohort; N=222 patients). RESULTS: In the UCSD-NAFLD (training) Cohort, MRE demonstrated a clinically significant diagnostic accuracy for the detection of ≥stage 2 fibrosis with an area under the ROC curve (AUROC) of 0.93 (95% CI 0.90 to 0.97) vs FIB-4 with an AUROC of 0.78 (95% CI 0.71 to 0.85), which was both clinically and statistically significant (p<0.0001). We then combined MRE with FIB-4 (MRE ≥3.3 kPa and FIB-4 ≥1.6) to develop a clinical prediction rule to rule in ≥stage 2 fibrosis patients which had positive predictive value (PPV) of 97.1% (p<0.02) in the UCSD-NAFLD cohort (AUROC of 0.90 (95% CI 0.85 to 0.95)) which remained significant at PPV of 91.0% (p<0.003) in the Japan-NAFLD Cohort (AUROC of 0.84 (95% CI 0.78 to 0.89)). CONCLUSION: MRE combined with FIB-4 (MEFIB) index may be used for non-invasive identification of candidates for (≥stage 2 fibrosis) pharmacological therapy among patients with NAFLD with a high PPV.