Diagnostic performance of LI-RADS version 2018 in differentiating hepatocellular carcinoma from other hepatic malignancies in patients with hepatitis B virus infection
The diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) in differentiating hepatocellular carcinoma (HCC) from other hepatic malignancies has not been investigated in Chinese patients with chronic liver disease from hepatitis B virus (HBV) infection. The aim of this study was to evaluate the accuracy of the LI-RADS version 2018 in differentiating HCC, intrahepatic cholangiocarcinoma (ICCA), and combined HCC-cholangiocarcinoma (cHCC-CCA) in Chinese patients with HBV infection. Seventy consecutive HBV-infected patients with ICCA (n = 48) or cHCC-CCA (n = 22) who underwent contrast-enhanced magnetic resonance imaging (CE-MRI) between 2006 and 2017 were enrolled along with a comparison cohort of 70 patients with HCC and CE-MRI-matched for tumor size (10–19 mm, 20–30 mm, 31–50 mm, and >50 mm). Imaging feature frequencies for each tumor type were compared using Fisher’s exact test. The classification accuracy of LR-5 and LR-M was estimated for HCC versus non-HCC (ICCA and cHCC-CCA). The interobserver agreement was good for LI-RADS categories of HCC and moderate for non-HCC. After consensus read, 66 of 70 (94%) HCCs were categorized LR-5 (including tumor in vein [TIV] with LR-5), while 42 of 48 (88%) ICCAs and 13 of 22 (59%) cHCC-CCAs were categorized LR-M (including TIV with LR-M) (p < 0.001). Thus, assignment of LR-5 provided 94% sensitivity and 81% specificity for HCC. LR-M provided 79% sensitivity and 97% specificity for non-HCC (ICCA and cHCC-CCA); and the sensitivity and accuracy were lower in differentiating HCC from non-HCC (tumor size <20 mm). LI-RADS v2018 category 5 and M reliably differentiated HBV-related HCC from ICCA. However, a substantial proportion of cHCC-CCAs were categorized LR-5 rather than LR-M. While management is controversial for these combined tumors, accurate prospective differentiation is desired for optimal treatment.
Copyright (c) 2020 Shuo Shao, Yingying Liang, Sichi Kuang, Jingbiao Chen, Qungang Shan, Hao Yang, Yao Zhang, Bin Wang, Kathryn J. Fowler, Jin Wang, Claude B. Sirlin
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