Evaluating diagnostic accuracy and agreement of TI-RADS scoring in thyroid nodules: A comparative analysis between sonographers and radiologists - Alfuraih, Abdulrahman M.; Alotaibi, Abdullah M.; Alshammari, Alanoud K.; Alrashied, Basmah F.; Mashhor, Yahya M.; Mahmoud, Mustafa; Alsaadi, Mohammed J. (PLOS ONE, 2024)
Objective The Thyroid Imaging Reporting and Data System (TI-RADS) is an essential tool for assessing thyroid nodules, primarily used by radiologists. This study aimed to compare the agreement of TI-RADS scores between sonographers and radiologists and to assess the diagnostic performance of these scores against histological findings in suspicious thyroid nodules. Methods In a retrospective analysis, 168 patients with suspicious thyroid nodules classified as TR3 and above by the radiologists were included. Both sonographers and radiologists independently assigned the American College of Radiologists (ACR) TI-RADS scores, which were then compared for inter-reader agreement using Cohen’s Kappa statistic. The scores were also evaluated for diagnostic performance against histological results based on the Bethesda system. Results The study revealed a moderate overall agreement between sonographers and radiologists in TI-RADS scoring (κ = 0.504; 95% CI: 0.409–0.599), with poor agreement noted specifically for nodule margin scores (κ = 0.102; 95% CI: -1.430–0.301). In terms of diagnostic performance against histological outcomes, sonographers’ TI-RADS scores showed a sensitivity of 100% and a specificity of 44.6%, while radiologists’ scores showed a sensitivity of 100% but a lower specificity of 29.3%. Conclusion The findings indicate moderate agreement in TI-RADS scoring between sonographers and radiologists, with reproducibility challenges especially in scoring nodule margins. The marginally superior diagnostic performance of sonographers’ scores suggests potential efficiency benefits in involving sonographers in preliminary assessments. Future research should aim to encompass a wider range of TI-RADS categories and focus on minimizing scoring variability to enhance the system’s clinical utility.