Comparison of mammographic density estimation by Volpara software with radiologists' visual assessment: analysis of clinical-radiologic factors affecting discrepancy between them.

Abstract

Volumetric breast density analysis is useful for quantitative mammographic assessment. However, there are few studies about clinical-radiologic factors contributing to discrepancies in the visual assessment by radiologists. To compare automated volumetric breast density measurement with BI-RADS breast density category by radiologists' visual assessments and to evaluate the clinical-radiologic factors affecting disagreement between two estimations. From February 2011 to September 2012, 860 patients (mean age, 54.7 ± 10.2 years) who had undergone digital mammography including fully automated volumetric breast density analysis, were enrolled. The agreement in breast density assessments between two radiologists, and between an experienced radiologist and the automated software were evaluated using a weighted kappa (k) value. Clinical-radiologic factors contributing to disagreement between the results obtained by a radiologist and the automated software were evaluated using univariate and multivariate analysis. Breast density assessments obtained by two different radiologists were in good agreement (weighted k statistics 0.835%; 95% confidence interval [CI], 0.8098-0.8608); breast density assessments obtained by an experienced radiologist versus automated software were in moderate agreement (weighted k statistics 0.799%; 95% CI, 0.7708-0.8263). Univariate analysis identified a difference in bilateral breast density and patient age as two factors that significantly contributed to disagreement between the two approaches (P = 0.0002, P = 0.019). Multivariate analysis only identified a difference in bilateral breast density as a contributing factor. The automated volumetric breast density measurement showed good agreement with radiologists' assessment. The difference in bilateral breast density affected the disagreement between results from visual assessment and automated software.