FINE NEEDLE ASPIRATION CYTOLOGICAL STUDIES OF THYROID LESIONS AND THEIR CLASSIFICATION BY BETHESDA SYSTEM OF REPORTING.
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Keywords
Thyroid lesions, Benign, Malignant, FNAC, BSRTC
Abstract
Background: Thyroid lesions are commonly encountered in clinical practice, and the differentiation between benign and malignant nodules is crucial for appropriate management. Fine Needle Aspiration Cytology (FNAC) is a widely used diagnostic tool to evaluate thyroid lesions due to its minimally invasive nature, accuracy, and cost-effectiveness. The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) provides a standardized approach to classify thyroid FNAC results, enhancing communication between pathologists and clinicians. The aim of this study was to evaluate the utility of FNAC in the diagnosis of thyroid lesions and to classify them according to the Bethesda system, assessing its impact on patient management.
Methodology: This retrospective study was conducted over a period of one year and included 150 patients who underwent FNAC for thyroid lesions at a tertiary care center. FNAC specimens were collected from patients with clinically suspicious thyroid nodules, and cytological findings were categorized based on the Bethesda System, which includes six diagnostic categories: non-diagnostic, benign, atypia of undetermined significance (AUS), follicular neoplasm, suspicious for malignancy, and malignant.
Results: In the present study, 199 cases of thyroid FNAC were received during the 2 years of study. These were categorized according to the Bethesda system of reporting thyroid cytology in to 6 categories. The distribution of FNAC findings was as follows; 70.8% benign, 4.5% AUS, 13% follicular neoplasm, 3.01% suspicious for malignancy, and 2.01% malignant. The Bethesda system allowed for better risk stratification and management decisions.
Conclusion: FNAC, when coupled with the Bethesda System for Reporting Thyroid Cytopathology, is an effective and reliable tool for evaluating thyroid lesions. The Bethesda classification helps stratify patients based on the risk of malignancy and guides clinical decision-making, reducing unnecessary surgeries while ensuring prompt management for patients with malignant nodules.
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Dr. Sheetal Balaji Gajale
Senior Resident at Dept. of Pathology at Dr. Shankarrao Chavan Government Medical College & Hospital - Vishnupuri, Nanded
Dr. Kedarnath V. Kute
Assistant Professor at Dept. of Pathology at Dr. Shankarrao Chavan Government Medical College & Hospital - Vishnupuri, Nanded
Dr. Prashant R. Shinde
Senior Resident at Dept. of Surgery at Government Medical College, Parbhani
Dr. Shivaji Birare
Professor at Dept. of Pathology at Government Medical College & Hospital - Sindhudurg
Dr. P. N. Kadam
Associate Professor at Dept. of Pathology at Dr. Shankarrao Chavan Government Medical College & Hospital - Vishnupuri, Nanded