Diagnostic accuracy of the Yokohama system for reporting breast fine-needle aspiration cytology and breast imaging-reporting and data system in breast lesions

Objectives: The Yokohama system standardizes fine-needle aspiration cytology (FNAC) reporting for breast lesions, while the breast imaging-reporting and data system (BI-RADS) categorizes lesions based on imaging risk assessment. This study aimed to evaluate the diagnostic accuracy of FNAC using the Yokohama System in correlation with BI-RADS classifications. Material and Methods: A retrospective analysis was conducted on 188 breast lesion cases that underwent FNAC and were categorized using the BI-RADS system. The breast FNAs were classified according to the Yokohama System and compared with histopathological diagnoses to calculate the risk of malignancy (ROM). The ROM for the BI-RADS categories was also determined. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for both. Results: According to the Yokohama classification, 5.9%, 52.1%, 4.8%, 8.5%, and 28.7% were classified as non-diagnostic, benign, atypical, suspicious, and malignant, respectively. The majority of cases were classified as BIRADS 3 (23.9%) and 5 (23.9%), followed by 4a (22.3%). Higher Yokohama and BI-RADS categories were more prevalent among malignant cases, with 64.9% in Yokohama category 5 and 51.9% in BI-RADS 5. Sensitivity was highest in Yokohama Scenario C (81.8%), while specificity (96.4%) and PPV (92.6%) were highest in Scenario A. When BI-RADS 4b, 4c, 5, and 6 were considered malignant, Scenario C had the highest sensitivity (87.0%) and NPV (90.4%), while Scenario B demonstrated the highest diagnostic accuracy (87.7%). Conclusion: FNAC using the Yokohama System and imaging-based BI-RADS classification both show high diagnostic accuracy for breast lesions. While their individual performance is comparable, further studies are needed to explore whether combining these modalities improves diagnostic outcomes in clinically indeterminate cases.