Kierans Andrea Siobhan, Fowler Kathryn J, Chernyak Victoria
Weill Cornell Medical College, New York, USA.
Scripps Health, San Diego, USA.
Abdom Radiol (NY). 2024 Dec 13. 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.
肝脏影像报告和数据系统（LI-RADS）CT/MRI诊断算法于2011年首次发布，它根据肝细胞癌、恶性肿瘤或良性病变的可能性，将肝脏观察结果按序数尺度进行分类，并指导肝脏影像的可重复解读、清晰沟通和标准化术语。在过去十年中，LI-RADS的范围显著扩大，纳入了涉及筛查和监测、对比增强超声（CEUS）诊断以及CEUS和CT/MRI治疗反应评估的算法。LI-RADS算法会根据不断积累的科学证据、用户反馈和技术进步进行定期完善。本文讨论了LI-RADS算法的近期改进、计划更新，重点是LI-RADS CT/MRI诊断算法以及未来目标。
