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How to Use LI-RADS to Report Liver CT and MRI Observations

Guilherme Moura Cunha, Kathryn J. Fowler, Alexandra Roudenko, Bachir Taouli, Alice Fung, Khaled M. Elsayes, Robert M. Marks, Irene Cruite, Natally Horvat, Victoria Chernyak, Claude B. Sirlin, An Tang

2021Radiographics39 citationsDOIOpen Access PDF

Abstract

Primary liver cancer is the fourth leading cause of cancer-related deaths worldwide, with hepatocellular carcinoma (HCC) comprising the vast majority of primary liver malignancies. Imaging plays a central role in HCC diagnosis and management. As a result, the content and structure of radiology reports are of utmost importance in guiding clinical management. The Liver Imaging Reporting and Data System (LI-RADS) provides guidance for standardized reporting of liver observations in patients who are at risk for HCC. LI-RADS standardized reporting intends to inform patient treatment and facilitate multidisciplinary communication and decisions, taking into consideration individual clinical factors. Depending on the context, observations may be reported individually, in aggregate, or as a combination of both. LI-RADS provides two templates for reporting liver observations: in a single continuous paragraph or in a structured format with keywords and imaging findings. The authors clarify terminology that is pertinent to reporting, highlight the benefits of structured reports, discuss the applicability of LI-RADS for liver CT and MRI, review the elements of a standardized LI-RADS report, provide guidance on the description of LI-RADS observations exemplified with two case-based reporting templates, illustrate relevant imaging findings and components to be included when reporting specific clinical scenarios, and discuss future directions. An invited commentary by Yano is available online. Online supplemental material is available for this article. Work of the U.S. Government published under an exclusive license with the RSNA.

Topics & Concepts

MedicineContext (archaeology)TerminologyMedical physicsRadiologyPaleontologyLinguisticsBiologyPhilosophyRadiomics and Machine Learning in Medical ImagingRadiology practices and educationHepatocellular Carcinoma Treatment and Prognosis
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