LI-RADS 在 CT 和 MRI 上的辅助特征。
LI-RADS ancillary features on CT and MRI.
机构信息
Montefiore Medical Center, Bronx, NY, USA.
Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, QC, Canada.
出版信息
Abdom Radiol (NY). 2018 Jan;43(1):82-100. doi: 10.1007/s00261-017-1220-6.
The Liver Imaging Reporting and Data System (LI-RADS) uses an algorithm to assign categories that reflect the probability of hepatocellular carcinoma (HCC), non-HCC malignancy, or benignity. Unlike other imaging algorithms, LI-RADS utilizes ancillary features (AFs) to refine the final category. AFs in LI-RADS v2017 are divided into those favoring malignancy in general, those favoring HCC specifically, and those favoring benignity. Additionally, LI-RADS v2017 provides new rules regarding application of AFs. The purpose of this review is to discuss ancillary features included in LI-RADS v2017, the rationale for their use, potential pitfalls encountered in their interpretation, and tips on their application.
肝脏影像报告和数据系统（LI-RADS）使用一种算法来分配类别，反映肝细胞癌（HCC）、非 HCC 恶性肿瘤或良性肿瘤的可能性。与其他成像算法不同，LI-RADS 利用辅助特征（AFs）来细化最终类别。LI-RADS v2017 中的 AFs 分为一般倾向于恶性肿瘤、特别倾向于 HCC 和倾向于良性肿瘤的特征。此外，LI-RADS v2017 提供了关于应用 AFs 的新规则。本文旨在讨论 LI-RADS v2017 中包含的辅助特征、使用这些特征的基本原理、在解释过程中遇到的潜在陷阱以及应用这些特征的技巧。
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