Hepatocellular carcinoma (HCC) versus non-HCC: accuracy and reliability of Liver Imaging Reporting and Data System v2018

肝细胞癌 (HCC) 与非肝细胞癌:肝脏影像报告和数据系统 v2018 的准确性和可靠性

阅读:1

Abstract

PURPOSE: The Liver Imaging Reporting and Data System (LI-RADS) was created to standardize the diagnostic criteria for hepatocellular carcinoma (HCC) and has undergone multiple revisions including a recent update in 2018 (v2018). The primary aim of this study was to determine the diagnostic performance and interrater reliability (IRR) of LI-RADS v2018 for distinguishing HCC from non-HCC primary hepatic malignancy in patients 'at-risk' for HCC. A secondary aim was to assess the impact of changes introduced in the v2018 diagnostic algorithm. METHODS: This retrospective study combined a 10-year experience of pathologically proven primary liver malignancies from two large liver transplant centers. Two blinded readers independently evaluated each lesion and assigned a LI-RADS diagnostic category, additionally scoring all relevant imaging features. Changes in category based on the reader-provided features and the new v2018 criteria were assessed by a study coordinator. RESULTS: The final study cohort comprised 105 HCCs and 73 non-HCC primarily liver malignancies. LI-RADS had a high specificity for distinguishing HCC from non-HCC (89% and 90% for reader 1 and reader 2, respectively), and IRR was moderate to substantial for final LI-RADS category and most features. Revision of the LI-RADS v2018 diagnostic algorithm resulted in very few changes [5 (2.8%) and 3 (1.7%) for reader 1 and reader 2, respectively] in overall lesion classification. CONCLUSION: LI-RADS diagnostic categories and features had moderate to substantial IRR and high specificity for distinguishing HCC from non-HCC primary liver malignancy. Revision of LI-RADS v2018 diagnostic algorithm resulted in reclassification of very few lesions.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。