Efficacy of Follicular Cell Pattern Analysis in Thyroid Fine-needle Aspiration Cytology Evaluation.

CONTEXT

Fine-needle aspiration cytology (FNAC) is widely utilized for thyroid lesion diagnosis but faces challenges such as sample inadequacy and overlapping cytological features. This study examines how accurately these patterns correlate with histopathological diagnoses, shedding light on FNAC's limitations and diagnostic potential.

AIMS

To study the application of the architectural pattern of follicular cells in the interpretation of thyroid lesions and to demonstrate the diagnostic accuracy (DA) of FNAC.

SETTINGS AND DESIGN

Cross-sectional study carried over 1 year.

SUBJECTS AND METHODS

A total of 110 cases were reviewed by the cytopathologists. The prominent follicular cell architecture, namely macrofollicular, microfollicular, papillary, trabecular, three-dimensional clusters, and dispersed cells, was described in each case. In addition to these patterns, cellular morphology and background features were also noted, and a final cytological diagnosis was established. The cytology diagnosis was correlated with the histopathological diagnosis.

STATISTICAL ANALYSIS USED

Sensitivity, specificity, positive predictive value, negative predictive value, DA of FNAC in diagnosing nonneoplastic and neoplastic lesions.

RESULTS

Macrofollicular pattern was seen in 80.26% of colloid goiter cases. Microfollicular pattern was observed in 72.2% of follicular neoplasm. About 62.5% of papillary thyroid carcinomas showed a papillary pattern. The trabecular pattern was seen in 42.86% of chronic lymphocytic thyroiditis and 16.67% of follicular neoplasms. The sensitivity and specificity of FNAC in diagnosing neoplastic lesions was 92.59% and 97.59%, respectively.

CONCLUSIONS

FNAC is a simple, rapid, definite, and cost-effective primary diagnostic tool for thyroid evaluation. Cell architecture pattern is a simple and appropriate approach that complements cell morphology and background details in arriving at the final cytological diagnosis of thyroid lesions.