| Literature DB >> 29558300 |
Franklin N Tessler1, William D Middleton1, Edward G Grant1.
Abstract
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.Entities:
Mesh:
Year: 2018 PMID: 29558300 DOI: 10.1148/radiol.2017171240
Source DB: PubMed Journal: Radiology ISSN: 0033-8419 Impact factor: 11.105