Liver Fat Quantification and Steatosis Grading in Fatty Liver Disease by Magnetic Resonance Imaging: Systematic Review and Meta-Analysis

磁共振成像对脂肪肝疾病中肝脏脂肪含量进行定量和脂肪变性分级:系统评价和荟萃分析

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Abstract

AIM: Magnetic resonance imaging (MRI) surrogate biomarkers are widely utilized to diagnose and monitor metabolic dysfunction-associated steatotic liver disease (MASLD). This meta-analysis assesses their effectiveness in quantifying liver fat and grading steatosis. METHODS AND RESULTS: Scopus, Web of Science, and MEDLINE (PubMed) were systematically searched up to February 20, 2024. Eligible studies included original research in English, focusing on MRI-based assessments of hepatic steatosis in humans with no comorbidities, with magnetic resonance spectroscopy (MRS) or pathology as the reference standard. Fat fraction and steatosis grade were evaluated using correlation, mean difference, and diagnostic accuracy metrics. This review was registered with PROSPERO with registration number CRD42024524991. Out of 9852 unique studies, 18 were included. Selective saturation fat fraction demonstrated the strongest Fisher's Z-transformed correlation with the reference standard (0.93), followed by proton density fat fraction (PDFF) (0.9). PDFF exhibited the highest Fisher's Z-transformed correlation with hepatic steatosis grading of the reference standard (0.67) and the highest AUROC for diagnosing hepatic steatosis (0.99). Magnetic resonance elastography (MRE) and MRI-PDFF multiparametric MRI showed the greatest sensitivity (0.97) for hepatic steatosis diagnosis, while multiecho gradient echo (MEGE) demonstrated the highest specificity (0.99). CONCLUSIONS: The analysis revealed moderate to strong correlations between MRI and reference standard FF, with MRI-PDFF demonstrating the highest diagnostic accuracy. There was significant variability in results across studies due to differences in techniques, field strength, and study design. The findings underscore the need for standardized performance metrics and reporting practices to enhance comparability, optimize clinical utility, and improve diagnostic uniformity for hepatic steatosis.

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