Study the Diagnostic Role of Fnac in Thyroid Lesion by the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC)
Year: 2024
Type: article
Abstract: Background: When assessing thyroid lesions, Fine-Needle Aspiration Cytology (FNAC) is a crucial diagnostic technique. To help standardize reporting and clinical care, thyroid FNAC data are divided into six diagnostic groups using the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). This study aims to evalu-ate the diagnostic role of FNAC in thyroid lesions using TBSRTC and correlate with cytohistological correlation. Methods: A prospective and retrospective study was conducted at the Department of Pathology, Maharani Lax-mi Bai Medical College, Jhansi, on 350 patients with palpable thyroid swellings who underwent FNAC, fol-lowed by thyroidectomy for histopathological correlation in 60 cases. FNAC samples were categorized accord-ing to TBSRTC, and statistical analysis was performed to calculate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy. Results: The mean age of the study population was 37.50±14.14 years, and 82.29% of the participants were female. The majority of cases (72.29%) had nodular thyroid swellings upon presentation. The accuracy of FNAC samples was 96.57%. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy of FNAC were calculated based on histopathological correlation. Conclusion: As classified by TBSRTC, FNAC is a cost-effective, minimally invasive, and dependable diag-nostic method for thyroid lesions. It helps reduce needless procedures, guide clinical management, and differen-tiate benign from malignant lesions. The study confirms the usefulness of TBSRTC in offering consistent and repeatable thyroid cytopathology diagnostic standards.
Authors: Renu Sahay, Mayank Kumar Singh, Ramji Verma, Sufia Ahmad Khan, Jitendra Singh Yadav
Institution: Maharani Laxmi Bai Medical College
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6949360602
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