From the Department of Radiology, University of Alabama at Birmingham, 619 S 19th St, JT N450, Birmingham, AL 35249 (F.N.T.); Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (W.D.M.); and Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, Calif (E.G.G.).
Radiology. 2018 Apr;287(1):29-36. doi: 10.1148/radiol.2017171240.
In 2017, the Thyroid Imaging Reporting and Data System (TI-RADS) Committee of the American College of Radiology (ACR) published a white paper that presented a new risk-stratification system for classifying thyroid nodules on the basis of their appearance at ultrasonography (US). In ACR TI-RADS, points in five feature categories are summed to determine a risk level from TR1 to TR5. Recommendations for biopsy or US follow-up are based on the nodule's ACR TI-RADS level and its maximum diameter. The purpose of this article is to offer practical guidance on how to implement and apply ACR TI-RADS based on the authors' experience with the system. RSNA, 2018.
2017 年，美国放射学院（ACR）的甲状腺成像报告和数据系统（TI-RADS）委员会发表了一份白皮书，提出了一种新的风险分层系统，根据超声（US）表现对甲状腺结节进行分类。在 ACR TI-RADS 中，根据五个特征类别的分数总和确定从 TR1 到 TR5 的风险级别。活检或 US 随访的建议基于结节的 ACR TI-RADS 级别及其最大直径。本文的目的是根据作者对该系统的经验，就如何实施和应用 ACR TI-RADS 提供实用指导。RSNA，2018 年。
