Thyroid Imaging Reporting and Data System (TI-RADS): A User's Guide.

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

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.

Related collections

Author and article information

Journal

Journal ID (iso-abbrev): Radiology

Title: Radiology

Publisher: Radiological Society of North America (RSNA)

ISSN (Electronic): 1527-1315

ISSN (Print): 0033-8419

Publication date (Electronic): Apr 2018

Volume: 287

Issue: 1

Affiliations

[1 ] 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.).

Article

DOI: 10.1148/radiol.2017171240

PubMed ID: 29558300

SO-VID: cc2e2735-a4f8-4e8f-b5d5-674a785ac500

History

Data availability:

Comments

Comment on this article

scite_

Cited by 66

See all cited by