Journal of Biomedical Physics and Engineering (Feb 2024)
Evidence Supporting Diagnostic Value of Liver Imaging Reporting and Data System for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis
Abstract
Background: Based on the Liver Imaging Data and Reporting System (LI-RADS) guidelines, Hepatocellular Carcinoma (HCC) can be diagnosed using imaging criteria in patients at risk of HCC.Objective: This study aimed to assess the diagnostic value of LI-RADS in high-risk patients with HCC.Material and Methods: This systematic review is conducted on international databases, including Google Scholar, Web of Science, PubMed, Embase, PROQUEST, and Cochrane Library, with appropriate keywords. Using the binomial distribution formula, the variance of each study was calculated, and all the data were analyzed using STATA version 16. The pooled sensitivity and specificity were determined using a random-effects meta-analysis approach. Also, we used the chi-squared test and I2 index to calculate heterogeneity among studies, and Funnel plots and Egger tests were used for evaluating publication bias.Results: The pooled sensitivity was estimated at 0.80 (95% CI: 0.76-0.84). According to different types of Liver Imaging Reporting and Data Systems (LI-RADS), the highest pooled sensitivity was in version 2018 (0.83 (95% CI: 0.79-0.87) (I2: 80.6%, P of chi 2 test for heterogeneity: <0.001 and T2: 0.001). The pooled specificity was estimated as 0.89 (95% CI: 0.87-0.92). According to different types of LI-RADS, the highest pooled specificity was in version 2014 (93.0 (95% CI: 89.0-96.0) (I2: 81.7%, P of chi 2 test for heterogeneity: <0.001 and T2: 0.001). Conclusion: LI-RADS can assist radiologists in achieving the required sensitivity and specificity in high-risk patients suspected to have HCC. Therefore, this strategy can serve as an appropriate tool for identifying HCC.
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