Based on the results obtained from the four groups of women in our study, the "50-50" breast is not a representative model of the breast composition.

Variability in a repeated measurement of breast density is lowest for Volpara and Quantra; these algorithms may be more suited to incorporation into a risk model.

In this paper we present the results of an automated and entirely reproducible algorithm that estimates the breast volume, dense tissue volume and the volumetric breast density from digital mammograms. The algorithm was applied to 55, 087 digital images (CC view only) from 15 351 individual women, acquired between 2008 and 2011 at the Sunnybrook Health Sciences Centre in Toronto, Canada. The algorithm is based on a prior calibration of the digital image signal versus tissue thickness and composition, and the thickness of the compressed breast is estimated using an empirical model that corrects the thickness readout of the mammography system as a function of compression force. The mean volumetric density and breast volumes for our study group were 30% and 687 cm(3), respectively. The left and right volumetric density and breast volume were strongly correlated, with a Pearson correlation of 0.92 and 0.91, respectively. The volumetric density decreased from 45% to 25% as age increased from 35 to 75 years, with an increase to 30% at 80 years. For a given woman, the volumetric density decreased at an average rate of -2 density percentage points per year while the breast volume increased by 2% per year.