Women with high mammographic breast density are at 4- to 6-fold increased risk of developing breast cancer compared
to women with fatty breasts. However, current breast density estimations rely on mammography, which cannot provide
accurate volumetric breast representation. Therefore, we explored two techniques of breast density evaluation via
ultrasound tomography. A sample of 93 patients was imaged with our clinical prototype; each dataset contained 45-75
tomograms ranging from near the chest wall through the nipple. Whole breast acoustic velocity was determined by
creating image stacks and evaluating the sound speed frequency distribution. Ultrasound percent density (USPD) was
determined by segmenting high sound speed areas from each tomogram using k-means clustering, integrating over the
entire breast, and dividing by total breast area. Both techniques were independently evaluated using two mammographic
density measures: (1) qualitative, determined by a radiologist's visual assessment using BI-RADS Categories, and (2)
quantitative, via semi-automatic segmentation to calculate mammographic percent density (MPD) for craniocaudal and
medio-lateral oblique mammograms. ~140 m/s difference in acoustic velocity was observed between fatty and dense BI-RADS
Categories. Increased sound speed was found with increased BI-RADS Category and quantitative MPD.
Furthermore, strong positive associations between USPD, BI-RADS Category, and calculated MPD were observed.
These results confirm that utilizing sound speed, both for whole-breast evaluation and segmenting locally, can be
implemented to evaluate breast density.