Updated ACR Thyroid Imaging Reporting and Data Systems in risk stratification of thyroid nodules: 1-year experience at a Tertiary Care Hospital in Al-Qassim

Background Thyroid imaging reporting and data system (TI-RADS) is assessment of risk stratification of thyroid nodules, using a score. A novel ACR (American College of Radiology) TI-RADS has been recently suggested by American College of Radiology. But, the utility of ACR TI-RADS in risk stratification for thyroid lesion needs further evaluation. Aim Of this study was to evaluate ACR TI-RADS classification in discriminating benign and from other thyroid lesions as detected by fine needle aspiration cytology (FNAC). Methods This retrospective study included all patients referred to our institute for FNAC of a thyroid nodule over 1 year. Thyroid nodules were categorized according to the 2017 ACR TI-RADS. Ultimately, efficacy of ACR TI-RADS in differentiating benign from non-benign nodules was assessed using ROC curve, cross-tabulation, and Chisquare tests. According to the results of FNAC, nodules were classified into 2 groups; benign lesions (Bethesda II) and malignant lesions (Bethesda IV, V). Results The percentages of Bethesda IV and V lesions defined in our ACR-TIRADS were as follows: ACR TI-RADS 1, 2 (0%), ACR TI-RADS 3 (4%), ACR TI-RADS 4 (6.6%), and ACR TI-RADS 5 (22.6%). ROC curve analysis for ACR TI-RADS to differentiate benign from non-benign pathology showed (AUC 0.60, 95% CI: 0.505–0.713). ACR TI-RADS had sensitivity, specificity, positive predictive value and negative predictive value 75%, 62.35 %, 15.7%, 96.3% respectively. Conclusion Differentiation between benign and malignant thyroid lesion can be suggested from the ultrasound based ACR TI-RADS system. FNAC might be deferred in patients having ACR TI-RADS 1 and 2.