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

Franklin N Tessler¹, William D Middleton¹, Edward G Grant¹

¹From 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.).

|March 21, 2018

Summary

This summary is machine-generated.

The American College of Radiology (ACR) developed a new system called ACR TI-RADS to classify thyroid nodules using ultrasound. This guide offers practical advice for implementing this thyroid nodule risk stratification system.

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Area of Science:

Radiology
Medical Imaging
Endocrinology

Background:

The American College of Radiology (ACR) introduced the Thyroid Imaging Reporting and Data System (TI-RADS) in 2017.
This system stratifies thyroid nodules based on ultrasonography (US) findings.
It assigns risk levels (TR1-TR5) by summing points from five feature categories.

Purpose of the Study:

To provide practical guidance on implementing and applying the ACR TI-RADS.
To share authors' experience with the ACR TI-RADS system for thyroid nodule classification.

Main Methods:

Utilizes ultrasonography (US) to assess thyroid nodule features.
Assigns points to five distinct feature categories.
Calculates a total score to determine the nodule's risk level (TR1-TR5).

Main Results:

Establishes a standardized risk stratification for thyroid nodules.
Recommendations for biopsy or follow-up are linked to ACR TI-RADS level and nodule size.

Conclusions:

The ACR TI-RADS provides a structured approach to thyroid nodule evaluation.
Practical application guidance is essential for effective implementation of the ACR TI-RADS system.