Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA.
Abdom Radiol (NY). 2018 Jan;43(1):75-81. doi: 10.1007/s00261-017-1291-4.
The Liver Imaging Reporting and Data System (LI-RADS) was designed to standardize the interpretation and reporting of observations seen on studies performed in patients at risk for development of hepatocellular carcinoma (HCC). The LI-RADS algorithm guides radiologists through the process of categorizing observations on a spectrum from definitely benign to definitely HCC. Major features are the imaging features used to categorize observations as LI-RADS 3 (intermediate probability of malignancy), LIRADS 4 (probably HCC), and LI-RADS 5 (definite HCC). Major features include arterial phase hyperenhancement, washout appearance, enhancing capsule appearance, size, and threshold growth. Observations that have few major criteria are assigned lower categories than those that have several, with the goal of preserving high specificity for the LR-5 category of Definite HCC. The goal of this paper is to discuss LI-RADS major features, including definitions, rationale for selection as major features, and imaging examples.
肝脏影像报告和数据系统(LI-RADS)旨在标准化对有发展肝细胞癌(HCC)风险的患者进行的研究中观察结果的解释和报告。LI-RADS 算法指导放射科医生通过将观察结果分类为从肯定良性到肯定 HCC 的频谱过程。主要特征是用于将观察结果分类为 LI-RADS 3(恶性可能性中等)、LI-RADS 4(可能 HCC)和 LI-RADS 5(明确 HCC)的影像学特征。主要特征包括动脉期强化、洗脱外观、增强包膜外观、大小和阈值生长。具有较少主要标准的观察结果被分配的类别低于具有多个主要标准的观察结果,目的是为明确 HCC 的 LR-5 类别保留高特异性。本文的目的是讨论 LI-RADS 的主要特征,包括定义、作为主要特征选择的理由以及影像学示例。