Correlation of FNAC diagnosis with histopathological diagnosis of thyroid lesions: a five-year retrospective study
Keywords:
Correlation, FNAC, Histopathology, Nepal, ThyroidAbstract
Introduction: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) provides a standardized reporting framework that facilitates clinical management. This study aimed to determine the correlation between fine-needle aspiration cytology (FNAC) diagnosis (as per TBSRTC) with final histopathological diagnoses in a surgical cohort.
Method: A retrospective cross-sectional analysis was conducted on 152 thyroidectomy cases with a history of prior FNAC, over five years’ duration. FNAC diagnoses were categorized as per TBSRTC, and correlated with final histopathological findings. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and kappa statistics were calculated. The risk of malignancy (ROM) was calculated for each category based on its corresponding final histopathological results.
Result: The study showed a female predominance (86.18%) with a peak incidence in the fifth decade. Bethesda category II was the most common cytological diagnosis (44.08%), followed by category VI (32.24%). Histopathological evaluation revealed 57.24% malignant lesions, with papillary thyroid carcinoma being the most frequent malignancy. FNAC demonstrated a sensitivity of 78.50%, specificity of 98.00%, PPV of 98.40%, and NPV of 74.60%. The cyto-histopathological concordance was substantial, with a kappa-value of 0.724. The ROM for Bethesda-II, Bethesda-VI, Bethesda-V and Bethesda-IV were 23.88%, 97.96%, 92.86% and 35.71%, respectively.
Conclusion: FNAC is a reliable diagnostic tool for triaging thyroid lesions, demonstrating high specificity and a strong PPV, with significant cyto-histological concordance, especially for category V lesions. However, relatively higher risk of malignancy in the benign category in this specific study highlights the limitation of FNAC in isolation. Clinico-radiological correlation is essential in minimizing diagnostic discrepancies.
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