Related Experiment Video
Updated: Oct 12, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
A Comparison of Two Widely Used Risk Stratification Systems for Thyroid Nodule Sonographic Evaluation
Miki Paker1, Tal Goldman2, Muhamed Masalha1
1Department of Ear, Nose, and Throat, Emek Medical Center, Afula, Israel.
Background:
The 2015 American Thyroid Association (ATA2015) and the American College of Radiology Thyroid Imaging and Reporting Data System (ACR TI-RADS) are two widely used thyroid sonographic systems.
Objectives:
To compare the two systems for accuracy of cancer risk prediction.
Methods:
Preoperative ultrasound images from 265 patients who underwent thyroidectomy at our hospital from January 2012 to March 2019 were retrospectively categorized by the ACR TI-RADS and ATA2015 systems. Diagnostic performances were compared.
Results:
Of 238 nodules assessed, 115 were malignant. Malignancy risks for the five ACR TI-RADS categories were 0%, 7.5%, 11.4%, 59.6%, and 90.0%. Malignancy risks for the five ATA2015 categories were 0%, 6.8%, 17.0%, 55.5%, and 92.1%. The proportion of total nodules biopsied was higher with the ATA2015 system than the ACR TI-RADS system: 88.7% vs. 66.3%. Proportions of malignant nodules and benign nodules biopsied were higher with ATA2015 than with ACR TI-RADS: 93.3% vs. 87.8% and 84.4% vs. 46.3%, respectively. Specificity and sensitivity rates were 53.6% and 84.3%, respectively, for ACR TI-RADS, and 15.5% and 93.3%, respectively, for ATA2015. The two systems showed similarly accurate diagnostic performance (AUC > 0.88). False negative rates for ACR TI-RADS and ATA2015 were 15.6% and 6.6%, respectively. Rates of missed aggressive cancer were similar for the two systems: 3.4% and 3.7%, respectively.
Conclusions:
ACR TI-RADS was superior to ATA2015 in specificity and avoiding unnecessary biopsies. ATA2015 yielded better sensitivity and a lower false negative rate. Identification of aggressive cancers was identical in the two systems.
More Related Videos
05:41Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
Published on: February 9, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025