Evaluation of quantitative measures of breast tissue density from mammography with truth from MRI data

Breast tissue density is one of the most cited risk factors in breast cancer development. Nevertheless, estimates of the magnitude of breast cancer risk associated with density vary substantially because of the inadequacy of methods used in tissue density assessment (e.g., subjective and/or qualitative assessment) and lack of a reliable gold standard. We have developed automated algorithms for quantitatively measuring breast composition from digitized mammograms. The results were compared to objective truth as determined by quantitative measures from breast MR images, as well as to subjective truth as determined by radiologists' readings from digitized mammograms using BI-RAD standards. Higher linear correlation between estimates calculated from mammograms using the methods developed herein and estimates derived from breast MR images demonstrates that the mammography-based methods will likely improve our ability to accurately determine the breast cancer risk associated with breast density. By using volumetric measures from breast MR images as a gold standard, we are able to estimate the adequacy and accuracy of our algorithms. The results can be used for providing a calibrated method for estimating breast composition from mammograms.