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ROBERTO CANNELLA

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

  • Autori: Ludwig D.R.; Fraum T.J.; Cannella R.; Ballard D.H.; Tsai R.; Naeem M.; LeBlanc M.; Salter A.; Tsung A.; Shetty A.S.; Borhani A.A.; Furlan A.; Fowler K.J.
  • Anno di pubblicazione: 2019
  • Tipologia: Articolo in rivista
  • OA Link: http://hdl.handle.net/10447/588650

Abstract

PurposeThe 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.MethodsThis 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.ResultsThe 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.ConclusionLI-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.