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Published on: October 20, 2023
Fat-Corrected Non-Gaussian Diffusion MRI for Liver Fibrosis Assessment in Metabolic Dysfunction-Associated Steatotic
Omaïma Saïd1, Sabrina Doblas1, Valérie Paradis1,2
1Center for Research on Inflammation, Inserm U1149 Université Paris Cité, Paris, France.
Background:
In patients with metabolic dysfunction-associated steatotic liver disease (MASLD), non-Gaussian diffusion-weighted imaging (DWI) has been proposed for the diagnosis of liver fibrosis, but its measurement is partially confounded by steatosis. We therefore asked whether a fat-corrected approach could improve fibrosis assessment.
Purpose:
To evaluate the diagnostic performance of non-Gaussian diffusion coefficients for the assessment of fibrosis in MASLD patients with a method accounting for intravoxel fat.
Study Type:
Prospective single-center cross-sectional study.
Population:
A total of 289 participants with Type 2 diabetes, hepatic steatosis, and elevated aminotransferases were enrolled from October 2018 to June 2021. Among them, 222 participants (mean age 59 ± 10 years; 149 men) underwent liver biopsy and MRI and were included in the final analysis.
Field Strength/Sequence:
3 T, DWI using spin-echo echo-planar imaging, MR elastography (MRE) using gradient echo sequence and fat fraction imaging using a multiple gradient echoes sequence.
Assessment:
Diffusion coefficients were estimated using two non-Gaussian models: a shifted apparent diffusion coefficient (sADC) and a non-linear least squares fit (ngADC), both computed without and with intravoxel fat correction (corr) using fat fraction on PDFF. Fibrosis was staged histologically. Quantitative parameters were compared across fibrosis stages. Diagnostic performance for F0 versus ≥ F1 was evaluated and compared to liver stiffness on MRE.
Statistical Tests:
Group comparisons used Kruskal-Wallis tests (α = 0.05), and diagnostic performance was assessed via receiver operating characteristic (ROC) curve analysis with 95% confidence intervals, with p < 0.05 considered statistically significant.
Results:
ngADCcorr was significantly different between fibrosis stages (Kruskal-Wallis p < 0.05). ROC curve analysis indicated comparable performance in discriminating fibrosis stages F0 versus F1-F4 for ngADCcorr and stiffness (AUC = 0.66, 95% CI: [0.59, 0.7], p < 0.05 and 0.68 [0.62, 0.74], p < 0.05, respectively).
Data Conclusion:
Fit-based non-Gaussian DWI with fat correction could potentially be used with similar diagnostic accuracy as MRE for detecting fibrosis in patients with MASLD.
Evidence Level:
3.
Technical Efficacy:
Stage 2.
