Correlation Between Ultrasound-Based Acr Ti-Rads and Bethesda System for Reporting Thyroid-Cytopathology: A Prospective Study at Tertiary Care Center in Eastern India

Abstract

BACKGROUND: Ultrasound(USG) is the initial imaging tool for the assessment of thyroid lesions, due to its easy availability and no radiation risk.USG based TIRADS uses particular lexicons for reporting a focal thyroid nodule,based on which risk of malignancy is calculated and finally a TIRADS category is assigned.The lexicons used are helpful for effective communication between the practitioners. OBJECTIVE:To determine the efficacy of ACR based TIRADS in predicting suspicious thyroid nodules and categorizing the patients in need of further evaluation with FNAC or follow up. MATERIALS AND METHODS: This prospective study was done over a period of 1 year (January 2019–January 2020)and include 50 patients. Patients having thyroid nodules in B-mode ultrasound were included in the study. The nodules were then grouped into their respective categories based on ACR TI-RADS and further management was decided. Pathological correlation using Bethesda classification and cancer risk of each TIRADS category was determined in the follow-up period simultaneously. RESULTS:All the 6 nodules classified under the TIRADS 5 category were found to be malignant while none of the TIRADS 2 nodules out of 29 were malignant i.e.Bethesda IV or higher.The risk of malignancy for ACR TI-RADS categories 1,2,3,4 and 5 was 0, 14.3, 62.5 and 100%, respectively.The risk of cancer in our study is almost comparable to other prominent studies. CONCLUSION:ACR based TIRADS classification is reliable in predicting thyroid malignancy.

Sonographic evaluation of thyroid nodule based on thyroid imaging reporting and data system classification and its correlation with fine needle aspiration cytology findings

“…Comparative analysis with studies conducted by Patil et al, De et al and Siddheshwar et al revealed consistency in the risk stratification of thyroid nodules based on ACR-TIRADS categories. [23][24][25] These studies demonstrated varying degrees of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for malignancy prediction using ACR-TIRADS, providing a comprehensive understanding of its diagnostic utility across different populations.…”