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Chinese Journal of Medical Ultrasound (Electronic Edition) ›› 2022, Vol. 19 ›› Issue (06): 561-566. doi: 10.3877/cma.j.issn.1672-6448.2022.06.012

• Superficial Parts Ultrasound • Previous Articles     Next Articles

Efficacy of different TI-RADS classification systems in diagnosis of thyroid nodules

Yaning Kang1, Chao Fu1, Caifeng Si1, Yanfei Guo1, Jing Li1, Kefei Cui1,()   

  1. 1. Department of Ultrasonography, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
  • Received:2020-10-13 Online:2022-06-01 Published:2022-06-16
  • Contact: Kefei Cui

Abstract:

Objective

To compare the diagnostic value of American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS), Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS), and Kwak Thyroid Imaging Reporting and Data System (Kwak TI-RADS) for benign and malignant thyroid nodules.

Methods

The ultrasound images of 3134 thyroid nodules were collected from 2114 patients diagnosed as having thyroid nodules by ultrasound examination and confirmed by postoperative pathology at the First Affiliated Hospital of Zhengzhou University from May 2013 to July 2017. All nodules were categorized by ACR TI-RADS, AI TI-RADS, and Kwak TI-RADS, and receiver operating characteristic (ROC) curves were plotted to compare the diagnostic efficacy of the three.

Results

Among the 3134 nodules, 1566 were benign and 1568 were malignant. According to the maximum diameter, the nodules were divided into <10 mm group (1450 nodules) and ≥10 mm group (1684 nodules). The malignant rate of nodules in the <10 mm group was higher than that in the ≥10 mm group (59.7% vs 41.7%, χ2=101.399, P<0.001). The areas under the ROC curves of AI TI-RADS and Kwak TI-RADS for diagnosing benign and malignant thyroid nodules were 0.897 and 0.899, respectively, which were higher than that of ACR TI-RADS (0.879; P<0.05).The sensitivities of AI TI-RADS and Kwak TI-RADS were 86.4% and 88.2%, and the accuracies were 86.1% and 86.1%, respectively, which were significantly higher than those of ACR TI-RADS (80.9% and 83.0%; P<0.05). Pairwise comparisons of the specificities of the three showed no statistically significant difference (P>0.05). The areas under the ROC curves of the three classification systems for diagnosing benign and malignant thyroid nodules were higher in the ≥10 mm group than in the <10 mm group (Kwak TI-RADS: 0.922 vs 0.853; AI TI-RADS: 0.924 vs 0.845; ACR TI-RADS: 0.907 vs 0.830). Whether ≥10 mm group or <10 mm group, the areas under the ROC curves of AI TI-RADS and Kwak TI-RADS performed better than ACR TI-RADS (P<0.05).

Conclusion

Kwak TI-RADS and AI TI-RADS are more effective than ACR TI-RADS in the comprehensive diagnosis of thyroid nodules. Kwak TI-RADS is simple to operate and has strong clinical practicability, while AI TI-RADS is more comprehensive in the classification of nodules, which is more conducive to the risk management of thyroid nodules.

Key words: Thyroid nodules, Thyroid imaging reporting and data system, ROC curve

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