LI-RADS in 2024: recent updates, planned refinements, and future directions

• Published in: Abdominal imaging Vol. 50; no. 7; pp. 2868 - 2880
• Main Authors: Kierans, Andrea Siobhan, Fowler, Kathryn J., Chernyak, Victoria
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.07.2025; Springer Nature B.V
• Subjects: Algorithms; Carcinoma, Hepatocellular - diagnostic imaging; Computed tomography; Contrast Media; Gastroenterology; Hepatocellular carcinoma; Hepatology; Humans; Imaging; Liver; Liver cancer; Liver Neoplasms - diagnostic imaging; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Malignancy; Medical imaging; Medicine; Medicine & Public Health; Radiation; Radiology; Radiology Information Systems; Review; Surveillance; Tomography, X-Ray Computed - methods; Ultrasonic imaging; Visualization; United States > US; Hepatocellular carcinoma; Liver imaging reporting and data system; Surveillance; LI-RADS; Treatment response assessment
• ISSN: 2366-0058; 2366-004X; 2366-0058
• DOI: 10.1007/s00261-024-04730-w

Initially released in 2011, liver imaging reporting and data (LI-RADS) CT/MRI diagnostic algorithm categorizes hepatic observations on an ordinal scale based on the probability of hepatocellular carcinoma, malignancy, or benignity, and guides reproducible interpretation, clear communication, and standardized terminology for liver imaging. LI-RADS has significantly expanded in scope in the past decade, with the inclusion of algorithms that address screening and surveillance, diagnosis with contrast enhanced ultrasound (CEUS), and treatment response assessment with both CEUS and CT/MRI. LI-RADS algorithms undergo periodic refinements based on accumulating scientific evidence, user feedback, and technological advancements. This manuscript discusses recent LI-RADS algorithm refinements, planned updates, with a focus on LI-RADS CT/MRI diagnostic algorithm, and future goals. Graphical abstract