Comparison of the Diagnostic Performance of Breast Ultrasound and CAD Using BI-RADS Descriptors and Quantitative Variables

Abstract

Background: Computer-aided diagnosis (CAD) as an adjunct to breast ultrasonography (US) has been extensively developed using different breast imaging techniques to help improve radiologists’ diagnostic performance, particularly in distinguishing malignant from benign breast lesions. Additionally, quantitative variables can be obtained using CAD. Objectives: The aim of this study was to evaluate the usefulness of CAD as an adjunct to breast US by exploring the diagnostic performance of US and CAD using the breast imaging reporting and data system (BI-RADS) descriptors and quantitative variables. Patients and Methods: Between October 2015 and December 2016, we performed breast US with CAD (S-Detect) for screening or diagnostic purposes. We assessed the diagnostic performance according to the BI-RADS descriptors, quantitative variables (width, height, height/width (H/W) ratio, area, and depth), and combined results. We analyzed the agreement in the descriptors between US and CAD. Results: Four hundred thirty-two women with 521 breast lesions were enrolled. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of US vs. CAD were 0.82 vs. 0.78, 95% vs. 78%, and 69% vs. 78%, respectively. When CAD was combined with breast US, the specificity was significantly improved from 69% to 72% (P < 0.05). Among all descriptors and quantitative variables, the height and H/W ratio exhibited the greatest AUC (0.76 and 0.75), and the H/W ratio had the highest sensitivity (90%). According to the concordance analysis, the orientation exhibited the greatest agreement (k = 0.57). Conclusion: Using CAD, we could accurately determine the BI-RADS descriptors, quantitative variables and improve the specificity. Additionally, the orientation and H/W ratio are consistent key factors for both US and CAD.