Role of US LI-RADS in the LI-RADS algorithm

Shuchi K. Rodgers, David T. Fetzer, Helena Gabriel, James H. Seow, Hailey H. Choi, Katherine E. Maturen, Ashish P. Wasnik, Tara A. Morgan, Nirvikar Dahiya, Mary K. O’boyle, Yuko Kono, Claude B. Sirlin, Aya Kamaya

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

The US Liver Imaging Reporting and Data System (LI-RADS) was released in 2017 and is the newest of the four American College of Radiology (ACR) LI-RADS algorithms. US LI-RADS provides standardized terminology, technical recommendations, and a reporting framework for US examinations performed for screening or surveillance in patients at risk for developing hepatocellular carcinoma (HCC). The appropriate patient population for screening and surveillance includes individuals who are at risk for developing HCC but do not have known or suspected cancer. This includes patients with cirrhosis from any cause and subsets of patients with chronic hepatitis B virus infection in the absence of cirrhosis. In an HCC screening or surveillance study, US LI-RADS recommends assigning two scores that apply to the entire study: the US category, which determines follow-up, and a visualization score, which communicates the expected level of sensitivity of the examination but does not affect management. Three US categories are possible: US-1 negative, a study with no evidence of HCC; US-2 subthreshold, a study in which an observation less than 10 mm is depicted that is not definitely benign; and US-3 positive, a study in which an observation greater than or equal to 10 mm or a new thrombus in vein is identified, for which diagnostic contrast-material–enhanced imaging is recommended. Three visualization scores are possible: A (no or minimal limitations), B (moderate limitations), and C (severe limitations).

Original languageEnglish (US)
Pages (from-to)690-708
Number of pages19
JournalRadiographics
Volume39
Issue number3
DOIs
StatePublished - May 1 2019

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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    Rodgers, S. K., Fetzer, D. T., Gabriel, H., Seow, J. H., Choi, H. H., Maturen, K. E., Wasnik, A. P., Morgan, T. A., Dahiya, N., O’boyle, M. K., Kono, Y., Sirlin, C. B., & Kamaya, A. (2019). Role of US LI-RADS in the LI-RADS algorithm. Radiographics, 39(3), 690-708. https://doi.org/10.1148/rg.2019180158