Effectiveness and Significance of Fine Needle Aspiration Cytology in the Diagnosis of Thyroid Swelling: A Single Institute Experience in a Series of 710 Patients
Journal Title: Indian Journal of Forensic Medicine and Pathology - Year 2018, Vol 11, Issue 3
Abstract
Context: Thyroid swelling is a relatively common problem encountered in clinical practice throughout the world. Early detection of thyroid neoplasm is the fundamental basis of thyroid screening. A quest for ease, simple and accurate diagnostic tool that would differentiate between benign and malignant lesion has facilitated fine needle aspiration cytology (FNAC) as the first line tool in the initial thyroid evaluation. Aims: The study was aimed at classifying thyroid lesions according to the Bethesda System for Reporting Thyroid Cytopathology and to compare the diagnostic efficacy of fine needle aspiration cytology by correlating with gold standard histopathology. Settings and Design: This prospective cross-sectional study was conducted over a period of two years in a tertiary hospital, Kerala. Methods and Material: A total of 710 patients were included in the study. FNAC was performed and Staining was performed with Haematoxylin & Eosin (H&E), Papanicolaou and May-Grünwald Giemsa Stains. Diagnosis was made based on TBSRTC. Excision biopsies were fixed in 10% formalin. Statistical Analysis used: IBM Statistical Package for the Social Sciences Software version 21 was used to perform Pearson Chi-square test and Fischer Exact. Results: In this study 592 (83.4%) cases of non-neoplastic lesions, 111 (15.6%) cases of neoplastic lesions and seven cases were found unsatisfactory for diagnosis. FNAC showed high sensitivity and specificity in diagnosing neoplastic thyroid lesions and it showed high level of significance in diagnosing papillary thyroid carcinoma. Conclusions: FNAC is an excellent diagnostic tool in the management of thyroid lesions since it provides rapid diagnosis with high accuracy rate.
Authors and Affiliations
Abilash Saidharannair Chandrakumar
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