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. 2023 Apr 1;13(4):2109-2118.
doi: 10.21037/qims-22-592. Epub 2023 Feb 23.

Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds

Cai-Feng Si  1 , Chao Fu  1 , Yi-Yang Cui  1 , Jing Li  1 , Yuan-Jing Huang  1 , Ke-Fei Cui  1
Affiliations

Diagnostic and therapeutic performances of three score-based Thyroid Imaging Reporting and Data Systems after application of equal size thresholds

Cai-Feng Si et al. Quant Imaging Med Surg. .

Abstract

Background: The aim of this study was to explore the diagnostic and therapeutic performances of the artificial intelligence (AI), American College of Radiology (ACR), and Kwak Thyroid Imaging Reporting and Data Systems (TIRADSs) using the size thresholds for fine needle aspiration (FNA) and follow-up defined in the ACR TIRADS.

Methods: This retrospective study included 3,833 consecutive thyroid nodules identified in 2,590 patients from January 2010 to August 2017. Ultrasound (US) features were reviewed using the 2017 white paper of the ACR TIRADS. US categories were assigned according to the ACR/AI and Kwak TIRADS. We applied the thresholds for FNA and follow-up defined in the ACR TIRADS to the Kwak TIRADS. The diagnostic and therapeutic performances were calculated and compared using the McNemar or DeLong methods.

Results: The AI TIRADS had higher specificity, accuracy, and area under the curve (AUC) than did the ACR and Kwak TIRADS (specificity: 64.6% vs. 57.4% and 52.69%; accuracy: 78.5% vs. 75.4% and 73.0%; AUC: 88.2% vs. 86.6% and 86.0%; all P values <0.05). Meanwhile, the AI TIRADS had a lower FNA rate (FNAR), unnecessary FNA rate (UFR), and follow-up rate (FUR) than did the ACR and Kwak TIRADS using the size thresholds of the ACR TIRADS (specificity: 30.9% vs. 34.4% and 36.9%; accuracy: 41.1% vs. 47.8% and 48.7%; AUC: 34.2% vs. 37.7% and 41.0%; all P values <0.05). In addition, the Kwak TIRADS incorporating the size thresholds of the ACR TIRADS was almost similar to the ACR TIRADS in diagnostic and therapeutical performance.

Conclusions: The ACR TIRADS can be simplified, which potentially enhances its diagnostic and therapeutic performance. The method of score-based TIRADS (counting in the Kwak TIRADS and weighting in the ACR and AI TIRADS) might not determine the diagnostic and therapeutic performances of the TIRADS. Thus, we propose choosing a straightforward and practical TIRADS in daily practice.

Keywords: Score-based Thyroid Imaging Reporting and Data System (score-based TIRADS); missed malignancy; therapeutic performance; unnecessary fine needle aspiration (unnecessary FNA).

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-592/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Flowchart showing the recruitment of study participants. US-FNA, ultrasound fine needle aspiration.
Figure 2
Figure 2
Score assignments of ACR, AI, and Kwak TIRADS. ACR, American College of Radiology; AI, artificial intelligence; TIRADS, Thyroid Imaging Reporting and Data System; TR, Thyroid Imaging Reporting and Data System category.
Figure 3
Figure 3
The ROC curve of ACR AI and Kwak TI-RADS. The AUC of the ACR TIRADS was 0.866 (95% CI: 0.855–0.877), which was similar to the AUC of 0.860 of the Kwak TIRADS (95% CI: 0.848–0.871). The AUC of the AI TI-RADS was 0.880 (95% CI: 0.871–0.892), which was superior to that of the ACR TIRADS and Kwak TIRADS. ACR, American College of Radiology; AI, artificial intelligence; TIRADS, Thyroid Imaging Reporting and Data System; ROC, receiver operating characteristic curve; AUC, area under the curve.
See this image and copyright information in PMC

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