Suhail Najm Alareer Hayder, Arian Arvin, Fotouhi Maryam, Taher Hayder Jasim, Dinar Abdullah Ayoob
Department of Radiology, College of Health and Medical Technology, Al-Ayen University, Thi-Qar, 64001, Iraq.
Cancer Institute ADIR, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
J Biomed Phys Eng. 2024 Feb 1;14(1):5-20. doi: 10.31661/jbpe.v0i0.2211-1562. eCollection 2024 Feb.
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.
This study aimed to assess the diagnostic value of LI-RADS in high-risk patients with HCC.
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 I index to calculate heterogeneity among studies, and Funnel plots and Egger tests were used for evaluating publication bias.
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) (I: 80.6%, of chi 2 test for heterogeneity <0.001 and T: 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) (I: 81.7%, of chi 2 test for heterogeneity <0.001 and T: 0.001).
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.
根据肝脏影像报告和数据系统(LI-RADS)指南,可使用影像标准对有肝细胞癌(HCC)风险的患者进行HCC诊断。
本研究旨在评估LI-RADS在高危HCC患者中的诊断价值。
对国际数据库进行系统评价,包括谷歌学术、科学网、PubMed、Embase、PROQUEST和考克兰图书馆,使用适当的关键词。使用二项分布公式计算每项研究的方差,并使用STATA 16版对所有数据进行分析。采用随机效应荟萃分析方法确定合并敏感性和特异性。此外,我们使用卡方检验和I指数计算研究间的异质性,使用漏斗图和Egger检验评估发表偏倚。
合并敏感性估计为0.80(95%CI 0.76-0.84)。根据不同类型的肝脏影像报告和数据系统(LI-RADS),合并敏感性最高的是2018版(0.83(95%CI 0.79-0.87)(I:80.6%,异质性卡方检验P<0.001,T:0.001)。合并特异性估计为0.89(95%CI 0.87-0.92)。根据不同类型的LI-RADS,合并特异性最高的是2014版(93.0(95%CI 89.0-96.0)(I:81.7%,异质性卡方检验P<0.001,T:0.001)。
LI-RADS可帮助放射科医生在疑似HCC的高危患者中达到所需的敏感性和特异性。因此,该策略可作为识别HCC的合适工具。