Association between TI-RADS ultrasound categories and BETHESDA cytology categories of thyroid lesions
Year: 2024
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Ultrasound and cytology are the two major diagnostic modalities employed for the preoperative evaluation of thyroid lesions. Ultrasound thyroid imaging reporting and data systems (TI-RADS) have been proposed for risk stratification of thyroid nodules. The Bethesda system for reporting thyroid cytopathology (TBSRTC) by using six diagnostic categories with a stratified risk of malignancy (ROM) in each category is employed for unambiguous cytology reporting of thyroid lesions. Our objective is to study the association between TI-RADS ultrasound categories and Bethesda cytology categories in thyroid lesions and to find their diagnostic accuracy as compared with histopathological diagnosis wherever possible. METHODS: This is a prospective observational study in which a total of 107 patients were studied. Thyroid ultrasound was scored according to TI-RADS classification. A pathologist screened ultrasound-guided FNAC smear, and reporting was done using the Bethesda system of reporting. The pathologist was blinded for the TI-RADS report. RESULTS: Among all the 107 cases, the patients' age ranged from 8 to 70 years with a mean age of 41.67 ± 14.41 years. The men: women ratio was 1:5. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of TI-RADS were 50%, 95.24%, 88.89%, and 71.43%, respectively, with a diagnostic accuracy of 75.68%, while the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of Bethesda were 81.25%, 85.71%, 81. 25%, and 85.71%, respectively, as compared with the histopathological diagnosis. TI-RADS ultrasound categories and Bethesda cytology categories were correlated in 88% of cases. CONCLUSIONS: TI-RADS and TBSRTC classification systems are specific diagnostic modalities in thyroid lesions. They are correlated in the majority of cases.
Source: Indian Journal of Cancer
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4407626146