Volumetric breast density combined with masking risk: Enhanced characterization of breast density from mammography images

Abstract

Automatic characterization of breast density can enable more personalized breast cancer screening work flows. In this work, we present a novel method to automatically characterize breast density in mammography images. Our method computes a volumetric density map and measures the relative volume of glandular tissue (VBD%). For critical cases when masking of small masses may be possible it additionally quantifies the masking effect of glandular tissue. VBD% and the masking risk combined provide a 4-point density score that correlates with the BI-RADS 5th edition guidelines. We evaluated our approach using a study with 32 radiologists and 2400 breast images (600 4-view FFDM exams). In a subset of 415 images identified as critical cases the accuracy to detect dense breasts (density categories c or d) increased as shown by the area under the curves (0.783 vs. 0.621). By taking masking risk into consideration our method provides a more comprehensive assessment of breast density.