Categorisation of thyroid lesions according to bethesda system and their histopathology correlation in a tertiary care hospital
Keywords:FNAC, Thyroid, Histopathology.
Introduction: Thyroid is affected by variety of conditions, whose preoperative diagnosis is of great significance in appropriate management. Fine needle aspiration cytology (FNAC) offers cellular level diagnosis with comparable sensitivity and specificity with respect to gold standard histopathological examination. Aim: To categories Fine Needle Aspiration Cytology of Thyroid lesions according to The Bethesda System of Reporting Thyroid Cytopathology and to correlate with histopathological findings wherever possible and to estimate diagnostic accuracy of FNAC. Materials and methods: A prospective study was carried out over a period of 2year, during which FNAC was done in 328 patients with thyroid swelling. Amongst whom 126 underwent surgery and histopathological correlation was done in those cases. Results: There was female preponderance with female to male ratio of 6.9:1, and mean age of 40.6 years. Out of 126 cases, 117 were non-neoplastic and 9 were neoplastic on histopathology. Among 117 non-neoplastic lesions, 106 cases showed cyto-histological concordance and 11 were discordant. Among the 9 neoplastic lesions, cyto-histological concordance was obtained in 4 cases and discordant in 5. Sensitivity and specificity of FNAC for non-neoplastic lesions were 93.8% and 69.2% respectively. Positive predictive value and negative predictive value were 96.3% and 56.2% respectively with a diagnostic accuracy of 91.2%. Conclusion: FNAC is simple, inexpensive and effective diagnostic modality with complications being minimal. Precise technique and rational use of USG guidance improves the adequacy and reduces the non-diagnostic rates. FNAC reporting according to TBSRTC aids clinicians and Pathologists in providing optimal management of patients.
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Copyright (c) 2021 Sathyashree K V, Mahesh H Karigoudar, Anil Reddy Konduru, Pyla Ramadevi, Disha B S, Ramyashree G
This work is licensed under a Creative Commons Attribution 4.0 International License.