Diagnostic Performance of CT/MRI Liver Imaging Reporting and Data System v2017 for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Abstract

Background & aims: The liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing liver imaging in patients at high risk for hepatocellular carcinoma (HCC). We performed a meta-analysis to determine the diagnostic performance of the LR-5 category for HCC and the pooled proportions of HCCs in each LI-RADS category using CT/MRI LI-RADS v2017.

Methods: We searched multiple databases for original studies reporting on the diagnostic accuracy of CT/MRI LI-RADS v2017. Random-effects models were used to determine the summary estimates of the diagnostic performance of the LR-5 category and the pooled proportions of HCCs for each LI-RADS category. Risk of bias and concerns regarding applicability were evaluated with the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

Results: Fourteen studies (3 prospective studies and 11 retrospective studies) were included in the final analysis, consisting of 2056 patients, 2589 observations, and 1693 HCCs. The pooled per-observation sensitivity was 67% (95% confidence interval [CI], 62%-72%) with specificity of 92% (95% CI, 88%-95%) in the LR-5 category of CT/MRI LI-RADS v2017 for diagnosing HCC. The pooled proportions of HCCs were 0% (95% CI, 0%-0%) for LR-1, 4% (95% CI, 0%-8%) for LR-2, 34% (95% CI, 23%-44%) for LR-3, 67% (95% CI, 53%-81%) for LR-4, and 92% (95% CI, 87%-96%) for LR-5. The proportions of HCCs were significantly different among LI-RADS categories 1-5 (P = .034).

Conclusions: The LR-5 category of CT/MRI LI-RADS v2017 shows moderate sensitivity and high specificity for diagnosing HCC. Higher LI-RADS categories contained higher proportions of HCCs.