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Eur Radiol ; 29(7): 3564-3573, 2019 Jul.
Article in English | MEDLINE | ID: mdl-30899974

ABSTRACT

OBJECTIVE: To systematically review studies about the diagnostic accuracy of magnetic resonance imaging proton density fat fraction (MRI-PDFF) in the classification of hepatic steatosis grade in patients with non-alcoholic fatty liver disease (NAFLD). METHODS: Areas under the summary receiver operating characteristic curves (AUROC), sensitivity, specificity, overall diagnostic odds ratio (DOR), diagnostic score, positive likelihood ratio (+LR), and negative likelihood ratio (-LR) for MRI-PDFF in classification of steatosis grades 0 vs. 1-3, 0-1 vs. 2-3, and 0-2 vs. 3 were compared and analyzed. RESULTS: A total of 6 studies were included in this meta-analysis (n = 635). The summary AUROC values of MRI-PDFF for classifying steatosis grades 0 vs. 1-3, 0-1 vs. 2-3, and 0-2 vs. 3 were 0.98, 0.91, and 0.90, respectively. Pooled sensitivity and specificity of MRI-PDFF for classifying steatosis grades 0 vs. 1-3, 0-1 vs. 2-3, and 0-2 vs. 3 were 0.93 and 0.94, 0.74 and 0.90, and 0.74 and 0.87, respectively. Summary +LR and -LR of MRI-PDFF for classifying steatosis grades 0 vs. 1-3, 0-1 vs. 2-3, and 0-2 vs. 3 were 16.21 (95%CI, 4.72-55.67) and 0.08 (95%CI, 0.04-0.15), 7.19 (95%CI, 5.04-10.26) and 0.29 (95%CI, 0.22-0.38), and 5.89 (95%CI, 4.27-8.13) and 0.29 (95%CI, 0.21-0.41), respectively. CONCLUSIONS: Our meta-analysis suggests that MRI-PDFF has excellent diagnostic value for assessment of hepatic fat content and classification of histologic steatosis in patients with NAFLD. KEY POINTS: • MRI-PDFF has significant diagnostic value for hepatic steatosis in patients with NAFLD. • MRI-PDFF may be used to classify grade of hepatic steatosis with high sensitivity and specificity.


Subject(s)
Adipose Tissue/diagnostic imaging , Fatty Liver/diagnosis , Liver/diagnostic imaging , Magnetic Resonance Imaging/methods , Non-alcoholic Fatty Liver Disease/diagnosis , Fatty Liver/complications , Humans , Non-alcoholic Fatty Liver Disease/complications , ROC Curve
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