OPTIMIZING BREAST CANCER DIAGNOSIS: UNIFYING IAC YOKOHAMA SYSTEM WITH IMAGING AND HISTOPATHOLOGY IN EVALUATION OF BREAST LESIONS

Abstract

 Background: Determining the appropriate management for breast lesions relies on a combined approach using clinical examination, imaging techniques, and ne-needle aspiration biopsy (FNAB). This study investigates the effectiveness of integrating the established Breast Imaging-Reporting and Data System (BI-RADS) with the recently introduced International Academy of Cytology (IAC) Yokohama System for reporting FNAC results. Material and methods: A retrospective analysis was done on all breast FNAC cases from 2018 to 2023, which were recategorized according to IAC Yokohama system. Correlation with BIRADS and histopathology was performed and PPV, NPV, sensitivity, specicity, diagnostic accuracy and ROM for each category was calculated.

Results: The PPV, NPV, sensitivity, specicity and diagnostic accuracy of FNAC with category III assumed as benign were 94.3%, 95.70%, 86.8%, 98.2% and 95.3% respectively and the ROM for categories I to V were 33.4%, 0.0%, 12.5%, 83.4% and 100% respectively.

Conclusion: Study highlights the power of FNAB and IAC Yokohama System for breast lump diagnosis, especially when combined with BI-RADS. This "duo" excels in unclear FNAB cases and specic lesion types, offering valuable insights for treatment decisions. Further rening categories and embracing advancements can further strengthen this approach for improved patient care.