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Updated: Feb 22, 2026
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Malignancy risk stratification of thyroid nodules: comparisons of four ultrasound Thyroid Imaging Reporting and Data
Ying Wang1,2,3,4, Kai-Rong Lei2, Ya-Ping He1,4
1Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, 200072, China.
Abstract:
To compare the efficiency of four different ultrasound (US) Thyroid Imaging Reporting and Data Systems (TI-RADS) in malignancy risk stratification in surgically resected thyroid nodules (TNs). The study included 547 benign TNs and 464 malignant TNs. US images of the TNs were retrospectively reviewed and categorized according to the TI-RADSs published by Horvath E et al. (TI-RADS H), Park et al. (TI-RADS P), Kwak et al. (TI-RADS K) and Russ et al. (TI-RADS R). The diagnostic performances for the four TI-RADSs were then compared. At multivariate analysis, among the suspicious US features, marked hypoechogenicity was the most significant independent predictor for malignancy (OR: 15.344, 95% CI: 5.313-44.313) (P < 0.05). Higher sensitivity was seen in TI-RADS H, TI-RADS K, TI-RADS R comparing with TI-RADS P (P < 0.05 for all), whereas the specificity, accuracy and area under the ROC curve (Az) of TI-RADS P were the highest (all P < 0.05). Higher specificity, accuracy and Az were seen in TI-RADS K compared with TI-RADS R (P = 0.003). With its higher sensitivity, TI-RADS K, a simple predictive model, is practical and convenient for the management of TNs in clinical practice. The study indicates that there is a good concordance between TI-RADS categories and histopathology.
