Positive Predictive Values of the Sonographic Bi-Rads Final Assessment Categories for Breast Lesions

Abstract

Objective: To evaluate the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of sonographic Breast-Imaging Reporting and Data System (BI-RADS) final assessment categories for nonpalpable breast lesions. Materials and Methods:Between January 2008 and 2011, a total of 245 nonpalpable breast lesions (223 patients) that had undergone excisional biopsy after ultrasound-guided wire needle localization in our clinic were evaluated retrospectively. Eight patients excluded from the study because we could not find the pathology results for them. Two hundred and thirty-seven lesions in 215 patients were included in the study. Lesion evaluation was done with a high resolution Logiq 7 USG device (General Electrics) by using a 10-14 MHz linear probe before ultrasound-guided wire needle localization. Static image records were evaluated by two expert radiologists on breast imaging without the knowledge of clinical information, mammographic images and pathologic results of the patients. The radiologists determined the most appropriate BI-RADS category for each lesion. The diagnostic performance of BI-RADS category was compared with the final pathology of the patient by using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).Results: Of the 237 lesions, 49 (20.6%) were malignant, 43 (18.1%) were high-risk atypical lesions and 145 (61.1%) were benign. Sensitivity and NPV were 100% for both radiologists, while specificity was 20.7% and 30.3%; PPV was 24.7% and 27.2%, respectively. When evaluation was done for BI-RADS subcategories; PPV for BI-RADS 4 was 15.6% and 22.8% (5.6% and 9.3% for 4; 17.6% and 24.3% for 4b; 40.6% and 66.7% for 4c); for BI-RADS 5 PPV was 66.7% and 84.6%. Conclusion

A Simple Ultrasound Based Classification Algorithm Allows Differentiation of Benign from Malignant Breast Lesions by Using Only Quantitative Parameters

“…As the priority in trying to omit unnecessary biopsies is not to miss cancer, maintaining a high sensitivity (in our case 98.46 %) is mandatory at the cost of a somewhat lower specificity. This specificity however can be directly translated into the potential to omit unnecessary biopsies which is evidenced by the fact that the specificity of the proposed classification algorithm remains substantially higher than the usually reported specificity of B-mode breast US [ 3 , 37 ].…”