A Retrospective Study of Breast Imaging Reporting and Data System and Histopathological Correlation in Breast Lumps: A Single-Center Experience at R.L. Jalappa Hospital, Kolar, India

Introduction: The Breast Imaging-Reporting and Data System (BI-RADS) serves as a standardized classification system for breast imaging interpretation and management recommendations. This study evaluates the correlation between BI-RADS categories and histopathological findings in patients presenting with breast lumps at a tertiary care center in India. Methods: A retrospective observational study was conducted at R.L. Jalappa Hospital and Research Centre, Kolar, from 1st November 2024 to 30th November 2025. Female patients aged 22-78 years who underwent breast imaging with BI-RADS categorization (categories 3-5) followed by histopathological examination were included. Statistical analysis was performed using chi-square tests with calculation of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy. Results: A total of 215 patients were analyzed with a mean age of 48.7 ± 13.2 years. BI-RADS category distribution was: BI-RADS 3 (45 cases, 20.9%), 4A (52 cases, 24.2%), 4B (41 cases, 19.1%), 4C (28 cases, 13.0%), and 5 (49 cases, 22.8%). Malignancy rates showed progressive increase: BI-RADS 3 (8.9%), 4A (32.7%), 4B (46.3%), 4C (82.1%), and 5 (91.8%). Overall diagnostic performance showed sensitivity 96.3%, specificity 38.3%, PPV 61.2%, NPV 91.1%, and accuracy 67.4%. Strong positive correlation was found between BI-RADS categories and malignancy rates (p < 0.001, X² = 36.849). Conclusion: BI-RADS classification demonstrates strong correlation with histopathological malignancy rates in breast lump evaluation. Higher BI-RADS categories are reliably associated with increased malignancy probability, supporting the clinical utility of BI-RADS in breast lesion management and biopsy decision-making in the Indian healthcare context.