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

• Main Authors: Karthik Ganesan (Author), Shivsamb Jalkote (Author), Swarup Nellore (Author)
• Format: Book
• Published: Thieme Medical and Scientific Publishers Pvt. Ltd., 2023-09-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2581-9178; 10.1055/s-0043-1764401
• Keywords: CT; LI-RADS v2018; LR-3; LR-M; LR-TIV; MRI; Internal medicine; RC31-1245; Diseases of the digestive system. Gastroenterology; RC799-869
• Source: Journal of Gastrointestinal and Abdominal Radiology, Vol 06, Iss 03, Pp 185-201 (2023)

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.