Repeatability of MRI Biomarkers in Nonalcoholic Fatty Liver Disease: The NIMBLE Consortium.

Background There is a need for reliable noninvasive methods for diagnosing and monitoring nonalcoholic fatty liver disease (NAFLD). Thus, the multidisciplinary Non-invasive Biomarkers of Metabolic Liver disease (NIMBLE) consortium was formed to identify and advance the regulatory qualification of NAFLD imaging biomarkers. Purpose To determine the different-day same-scanner repeatability coefficient of liver MRI biomarkers in patients with NAFLD at risk for steatohepatitis. Materials and Methods NIMBLE 1.2 is a prospective, observational, single-center short-term cross-sectional study (October 2021 to June 2022) in adults with NAFLD across a spectrum of low, intermediate, and high likelihood of advanced fibrosis as determined according to the fibrosis based on four factors (FIB-4) index. Participants underwent up to seven MRI examinations across two visits less than or equal to 7 days apart. Standardized imaging protocols were implemented with six MRI scanners from three vendors at both 1.5 T and 3 T, with central analysis of the data performed by an independent reading center (University of California, San Diego). Trained analysts, who were blinded to clinical data, measured the MRI proton density fat fraction (PDFF), liver stiffness at MR elastography (MRE), and visceral adipose tissue (VAT) for each participant. Point estimates and CIs were calculated using χ2 distribution and statistical modeling for pooled repeatability measures. Results A total of 17 participants (mean age, 58 years ± 8.5 [SD]; 10 female) were included, of which seven (41.2%), six (35.3%), and four (23.5%) participants had a low, intermediate, or high likelihood of advanced fibrosis, respectively. The different-day same-scanner mean measurements were 13%-14% for PDFF, 6.6 L for VAT, and 3.15 kPa for two-dimensional MRE stiffness. The different-day same-scanner repeatability coefficients were 0.22 L (95% CI: 0.17, 0.29) for VAT, 0.75 kPa (95% CI: 0.6, 0.99) for MRE stiffness, 1.19% (95% CI: 0.96, 1.61) for MRI PDFF using magnitude reconstruction, 1.56% (95% CI: 1.26, 2.07) for MRI PDFF using complex reconstruction, and 19.7% (95% CI: 15.8, 26.2) for three-dimensional MRE shear modulus. Conclusion This preliminary study suggests that thresholds of 1.2%-1.6%, 0.22 L, and 0.75 kPa for MRI PDFF, VAT, and MRE, respectively, should be used to discern measurement error from real change in patients with NAFLD. ClinicalTrials.gov registration no. NCT05081427 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kozaka and Matsui in this issue.

Automated CNN-Based Analysis Versus Manual Analysis for MR Elastography in Nonalcoholic Fatty Liver Disease: Intermethod Agreement and Fibrosis Stage Discriminative Performance.

BACKGROUND. Histologic fibrosis stage is the most important prognostic factor in chronic liver disease. MR elastography (MRE) is the most accurate noninvasive method for detecting and staging liver fibrosis. Although accurate, manual ROI-based MRE analysis is complex, time-consuming, requires specialized readers, and is prone to methodologic variability and suboptimal interreader agreement. OBJECTIVE. The purpose of this study was to develop an automated convolutional neural network (CNN)-based method for liver MRE analysis, evaluate its agreement with manual ROI-based analysis, and assess its performance for classifying dichotomized fibrosis stages using histology as the reference standard. METHODS. In this retrospective cross-sectional study, 675 participants who underwent MRE using different MRI systems and field strengths at 28 imaging sites from five multicenter international clinical trials of nonalcoholic steatohepatitis were included for algorithm development and internal testing of agreement between automated CNN-based and manual ROI-based analyses. Eighty-one patients (52 women, 29 men; mean age, 54 years) who underwent MRE using a single 3-T system and liver biopsy for clinical purposes at a single institution were included for external testing of agreement between the two analysis methods and assessment of fibrosis stage discriminative performance. Agreement was evaluated using intraclass correlation coefficients (ICCs). Bootstrapping was used to compute 95% CIs. Discriminative performance of each method for dichotomized histologic fibrosis stage was evaluated by AUC and compared using bootstrapping. RESULTS. Mean CNN- and manual ROI-based stiffness measurements ranged from 3.21 to 3.34 kPa in trial participants and from 3.21 to 3.30 kPa in clinical patients. ICC for CNN- and manual ROI-based measurements was 0.98 (95% CI, 0.97-0.98) in trial participants and 0.99 (95% CI, 0.98-0.99) in clinical patients. AUCs for classification of dichotomized fibrosis stage ranged from 0.89 to 0.93 for CNN-based analysis and 0.87 to 0.93 for manual ROI-based analysis (p = .23-.75). CONCLUSION. Stiffness measurements using the automated CNN-based method agreed strongly with manual ROI-based analysis across MRI systems and field strengths, with excellent discriminative performance for histology-determined dichotomized fibrosis stages in external testing. CLINICAL IMPACT. Given the high incidence of chronic liver disease worldwide, it is important that noninvasive tools to assess fibrosis are applied reliably across different settings. CNN-based analysis is feasible and may reduce reliance on expert image analysts.

Association of Hepatic Steatosis with Adipose and Muscle Mass and Distribution in Children.

Background: Pediatric studies have shown associations between hepatic steatosis and total body fat, visceral fat, and lean mass. However, these associations have not been assessed simultaneously, leaving their relative importance unknown. Objective: To evaluate associations between hepatic steatosis and total-body adiposity, visceral adiposity, and lean mass in children. Method: In children at risk for fatty liver, hepatic steatosis, adipose, and lean mass were estimated with magnetic resonance imaging and dual-energy X-ray absorptiometry. Results: Two hundred twenty-seven children with mean age 12.1 years had mean percent body fat of 38.9% and mean liver fat of 8.4%. Liver fat was positively associated with total-body adiposity, visceral adiposity, and lean mass (P < 0.001), and negatively associated with lean mass percentage (P < 0.001). After weight adjustment, liver fat was only positively associated with measures of central adiposity (P < 0.001). Visceral adiposity also had the strongest association with liver fat (P < 0.001). Conclusions: In children, hepatic steatosis is more strongly associated with visceral adiposity than total adiposity, and the association of lean mass is not independent of weight or fat mass. These relationships may help guide the choice of future interventions to target hepatic steatosis.

Repeatability and accuracy of various region-of-interest sampling strategies for hepatic MRI proton density fat fraction quantification.

PURPOSE: To evaluate repeatability of ROI-sampling strategies for quantifying hepatic proton density fat fraction (PDFF) and to assess error relative to the 9-ROI PDFF. METHODS: This was a secondary analysis in subjects with known or suspected nonalcoholic fatty liver disease who underwent MRI for magnitude-based hepatic PDFF quantification. Each subject underwent three exams, each including three acquisitions (nine acquisitions total). An ROI was placed in each hepatic segment on the first acquisition of the first exam and propagated to other acquisitions. PDFF was calculated for each of 511 sampling strategies using every combination of 1, 2, …, all 9 ROIs. Intra- and inter-exam intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs) were estimated for each sampling strategy. Mean absolute error (MAE) was estimated relative to the 9-ROI PDFF. Strategies that sampled both lobes evenly ("balanced") were compared with those that did not ("unbalanced") using two-sample t tests. RESULTS: The 29 enrolled subjects (23 male, mean age 24 years) had mean 9-ROI PDFF 11.8% (1.1-36.3%). With more ROIs, ICCs increased, RCs decreased, and MAE decreased. Of the 60 balanced strategies with 4 ROIs, all (100%) achieved inter- and intra-exam ICCs > 0.998, 55 (92%) achieved intra-exam RC < 1%, 50 (83%) achieved inter-exam RC < 1%, and all (100%) achieved MAE < 1%. Balanced sampling strategies had higher ICCs and lower RCs, and lower MAEs than unbalanced strategies in aggregate (p < 0.001 for comparisons between balanced vs. unbalanced strategies). CONCLUSION: Repeatability improves and error diminishes with more ROIs. Balanced 4-ROI strategies provide high repeatability and low error.