Thyroid Imaging Reporting and Data System (TIRADS) in Stratifying Risk of Thyroid Malignancy at The Medical City
Keywords:
thyroid imaging reporting and data system, histopathology, thyroid cancer, malignancy riskAbstract
Objective. To determine the accuracy of Thyroid Imaging Reporting and Data System (TIRADS) in detecting thyroid malignancy, determine risk of malignancy in each TIRADS category and determine the ultrasound characteristics associated with malignancy.
Methodology. This is a retrospective cross-sectional study involving patients who underwent ultrasound, thyroid fine needle aspiration biopsy (FNAB) and thyroidectomy at The Medical City from January 2014 to December 2015. Ultrasound reports were retrieved and reviewed by two radiologists on separate occasions who were blinded to the cytopathology and histopathology results. The histopathology reports were correlated with ultrasound features to determine features associated with malignancy. Stata SE 12 was used for data analysis. TIRADS sensitivity, specificity, positive predictive values and negative predictive values and accuracy were calculated.
Results. 149 patients with thyroid nodules were included. Solid composition is the ultrasound feature predictive of malignancy with adjusted OR 4.912 (95% Cl 1.3257 to 18.2011, p = 0.017). The risk of malignancy for TIRADS categories 3, 4a, 4b, 4c and 5 were 12.50%, 12.82%, 26.19%, 53.70% and 66.67%, respectively. The Crude OR (95% CI) for TIRADS 4a, 4b, 4c and 5 were 1.03 (0.10 to 10.23), 2.48 (0.27 to 22.54), 8.12 (0.93 to 70.59) and 14.0 (0.94 to 207.60), respectively. The sensitivity, specificity, PPV, NPV and accuracy of TIRADS in relation to surgical histopathology report were 98.00%, 7.07%, 34.75%, 87.50%, and 53% respectively in TIRADS categories 4 and 5.
Conclusion. This study showed that a solid nodule is the most frequent ultrasound feature predictive of thyroid malignancy. Higher TIRADS classification is associated with higher risk of thyroid malignancy. TIRADS is a sensitive classification in recognizing patients with thyroid cancer.
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