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Updated: Jul 27, 2025

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
Published on: February 9, 2024
Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a
Fengping Liang1, Xiang Li1, Qiao Ji1
1Department of Medical Ultrasound, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Background:
The incidence of thyroid lumps is more and more high in population, and most biopsies of thyroid nodules are benign. To develop a practical risk stratification system based on five ultrasound features to stratify the malignancy risk of thyroid neoplasms.
Methods:
This retrospective investigation enrolled 999 consecutive patients with 1,236 thyroid nodules who underwent ultrasound screening. Fine-needle aspiration and/or surgery was performed, and pathology results were obtained at the Seventh Affiliated Hospital of Sun Yat-sen University in Shenzhen, China, which is a tertiary referral center, from May 2018 to February 2022. Each thyroid nodule's score was calculated based on five ultrasound features: composition, echogenicity, shape, margin, and echogenic foci. Additionally, each nodule's malignancy rate was calculated. The chi-square test was used to test whether the malignancy rate was different among the three subcategories (scores of 4-6, 7-8, and 9 or more) of thyroid nodules. We proposed the revised Thyroid Imaging Reporting and Data System (R-TIRADS), and its sensitivity and specificity were compared to the two existing systems [the American College of Radiology TIRADS (ACR TIRADS) and the Korean Society of Thyroid Radiology TIRADS (K-TIRADS)].
Results:
The final dataset consisted of 425 nodules from 370 patients. The malignancy rates of three subcategories [malignancy rate: 28.8% (scores from 4-6), 64.7% (scores from 7-8), and 84.2% (scores of 9 or more)] were significantly different (P<0.01). The unnecessary biopsy rates of the three systems (ACR TIRADS, R-TIRADS, and K-TIRADS) were 28.7%, 25.2%, and 14.8%, respectively. The R-TIRADS presented better diagnostic performance than the ACR TIRADS or K-TIRADS [area under the curve: 0.79 (95% CI: 0.74-0.83) vs. 0.69 (95% CI: 0.64-0.75), P=0.046; 0.79 (95% CI: 0.74-0.83) vs. 0.66 (95% CI: 0.60-0.71), P=0.041, respectively]. The R-TIRADS had the highest sensitivity [0.746 (95% CI: 0.689-0.803)], followed by the K-TIRADS [0.399 (95% CI: 0.335-0.463), P=0.000] and ACR TIRADS [0.377 (95% CI: 0.314-0.441), P=0.000].
Conclusions:
The R-TIRADS enables radiologists to diagnose thyroid nodules efficiently, and the number of unnecessary fine-needle aspirations can be considerably reduced.
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