LI-RADS version 2018 ancillary features at MRI

Milena Cerny, Victoria Chernyak, Damien Olivié, Jean Sébastien Billiard, Jessica Murphy-Lavallée, Ania Z. Kielar, Khaled M. Elsayes, Laurence Bourque, Jonathan C. Hooker, Claude B. Sirlin, An Tang

Research output: Contribution to journalArticlepeer-review

77 Scopus citations


The Liver Imaging Reporting and Data System (LI-RADS) standardizes performance of liver imaging in patients at risk for hepatocellular carcinoma (HCC) as well as interpretation and reporting of the results. Developed by experts in liver imaging and supported by the American College of Radiology, LI-RADS assigns to observations categories that reflect the relative probability of benignity, HCC, or other malignancy.While category assignment is based mainly on major imaging features, ancillary features may be applied to improve detection and characterization, increase confidence, or adjust LI-RADS categories. Ancillary features are classified as favoring malignancy in general, HCC in particular, or benignity. Those favoring malignancy in general or HCC in particular may be used to upgrade by a maximum of one category up to LR-4; those favoring benignity may be used to downgrade by a maximum of one category. If there are conflicting ancillary features (ie, one or more favoring malignancy and one or more favoring benignity), the category should not be adjusted. Ancillary features may be seen at diagnostic CT, MRI performed with extracellular agents, or MRI performed with hepatobiliary agents, with the exception of one ancillary feature assessed at US. This article focuses on LI-RADS version 2018 ancillary features seen at MRI. Specific topics include rules for ancillary feature application; definitions, rationale, and illustrations with clinical MRI examples; summary of evidence and diagnostic performance; pitfalls; and future directions.

Original languageEnglish (US)
Pages (from-to)1973-2001
Number of pages29
Issue number7
StatePublished - Nov 1 2018

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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