Comparison of K-TIRADS, EU-TIRADS and ACR-TIRADS Guidelines for Malignancy Risk Determination of Thyroid Nodules - Eren Tobcu; Erdal Karavaş; Gülden Taşova Yılmaz; Bilgin Topçu (Diagnostics)
Background/Objectives: Thyroid nodules are commonly observed in neck ultrasonography. Most nodules are benign; hence, several nodules require biopsy to accurately identify the malignant ones. Numerous risk classification guidelines have been developed for thyroid nodules, varying in their indications for fine-needle aspiration biopsy (FNAB). The aim of this study is to evaluate the performances of three internationally recognized thyroid imaging reporting and data systems (TIRADS) for risk stratification of malignancy in comparison to one another. Methods: A total of 225 thyroid nodules with definitive FNAB cytology or histopathological diagnoses were included in this study. Various ultrasound (US) features were classified into categories based on three TIRADS editions. The guidelines were assessed regarding sensitivity, specificity, predictive values, and diagnostic accuracy to compare diagnostic value. Results: The American College of Radiology (ACR)-TIRADS demonstrated the best diagnostic accuracy (63.1%), the highest specificity (58.7%) and positive predictive value (36.3%), among three different TIRADS systems. Korean (K)-TIRADS exhibited the highest sensitivity (94.2%), negative predictive value (96.1%), and the most favorable negative likelihood ratio (0.13). The European (EU)-TIRADS had a sensitivity of 90.4%, specificity of 48.6%, and diagnostic accuracy of 58.2%, ranking between the other two guidelines across most parameters. Conclusions: The rigorous use of the guidelines established by each of the three TIRADS systems would have markedly reduced the number of FNABs performed. The comparison of the three guidelines in our study indicated that they are effective screening methods for identifying malignant thyroid nodules. Among them, K-TIRADS showed the most effective diagnostic performance in sensitivity, while ACR-TIRADS yielded the best specificity.