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CC BY 4.0 · Journal of Gastrointestinal and Abdominal Radiology 2023; 06(03): 185-201
DOI: 10.1055/s-0043-1764401
Review Article

The Gray Zone: LR3, LR-M, and LR-TIV

Karthik Ganesan 
1   Department of Radiology, Sir H. N. Reliance Foundation Hospital and Research Center, Mumbai, Maharashtra, India
,
Shivsamb Jalkote
1   Department of Radiology, Sir H. N. Reliance Foundation Hospital and Research Center, Mumbai, Maharashtra, India
,
Swarup Nellore
1   Department of Radiology, Sir H. N. Reliance Foundation Hospital and Research Center, Mumbai, Maharashtra, India
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Abstract

The goal of Liver Imaging Reporting and Data System (LI-RADS) is to standardize the lexicon, imaging techniques, interpretation, and reporting of observations in patients with a potential risk for developing hepatocellular carcinoma (HCC), and, consequently, improve communication between radiologists and physicians. LI-RADS diagnostic algorithms are applied to a population “at risk,” follow a stepwise algorithmic approach which categorize and stratify individual observations as HCC, and also assess the likelihood of non-HCC malignancies and tumor in vein. Risk factors for developing HCC have geographical variations, which significantly impact diagnostic and management strategies; however, these variations are not considered in the LIRADS v2018 version. Further, the diagnostic algorithm includes several major and ancillary features, and, tie-breaking rules, which result in numerous probable combinations by which a plausible observation could be assigned a particular category, inherently increasing its complexity. Heterogeneity of the diagnostic algorithm results in certain imaging pitfalls and poses challenges in the precise characterization of observations, complicating its use in routine clinical practice. This article reviews the gray zones which may be encountered in the evaluation of LR-3, LR-M, and LR-TIV observations during routine clinical imaging with contrast-enhanced computed tomography and magnetic resonance imaging.

Keywords

CT - LI-RADS v2018 - LR-3 - LR-M - LR-TIV - MRI


Publication History

Article published online:
21 April 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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