Rationale and Objectives Breast density is a significant breast cancer risk factor that is measured from mammograms. However, uncertainty remains in both understanding its underlying physical properties as it relates to the breast and determining the optimal method for its measurement. A quantitative description of the information captured by the standard operator-assisted percentage of breast density (PD) measure was developed using full field digital mammography (FFDM) images that were calibrated to adjust for inter-image acquisition technique differences. Materials and Methods The information captured by the standard PD measure was quantified by developing a similar measure of breast density (PDc) from calibrated mammograms automatically by applying a static threshold to each image. The specific threshold was estimated by first sampling the probability distributions for breast tissue in calibrated mammograms. A percent glandular (PG) measure of breast density was also derived from calibrated mammograms. The PD, PDc, and PG breast density measures were compared using both linear correlation (R) and quartile odds ratio measures derived from a matched case-control study. Results The standard PD measure is an estimate of the number of pixel values above a fixed idealized x-ray attenuation fraction. There was significant correlation (P < 0.0001) between the PDc-PD (R = 0.78), PDc-PG (R = 0.87), and PD-PG (R = 0.71) measures of breast density. Risk estimates associated with the lowest to highest quartiles for the PDc measure [odds ratios: 1.0 (ref.), 3.4, 3.6, and 5.6], and the standard PD measure [odds ratios: 1.0 (ref.), 2.9, 4.8, and 5.1] were similar and greater than that of the calibrated PG measure [odds ratios: 1.0 (ref.), 2.0, 2.4, and 2.4]. Conclusions The information captured by the standard PD measure was quantified as it relates to calibrated mammograms and used to develop an automated method for measuring breast density. These findings represent an initial step for developing an automated measure built upon an established calibration platform. A fully developed automated measure may be useful for both research and clinical based risk applications.

IntroductionMammographic density has been established as a strong risk factor for breast cancer, primarily using digitized film mammograms. Full-field digital mammography (FFDM) is replacing film mammography, has different properties than film, and provides both raw and processed clinical display representation images. We evaluated and compared FFDM raw and processed breast density measures and their associations with breast cancer.MethodsA case-control study of 180 cases and 180 controls matched by age, postmenopausal hormone use, and screening history was conducted. Mammograms were acquired from a General Electric Senographe 2000D FFDM unit. Percent density (PD) was assessed for each FFDM representation using the operator-assisted Cumulus method. Reproducibility within image type (n = 80) was assessed using Lin's concordance correlation coefficient (rc). Correlation of PD between image representations (n = 360) was evaluated using Pearson's correlation coefficient (r) on the continuous measures and the weighted kappa statistic (κ) for quartiles. Conditional logistic regression was used to estimate odds ratios (ORs) for the PD and breast cancer associations for both image representations with 95% confidence intervals. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminatory accuracy.ResultsPercent density from the two representations provided similar intra-reader reproducibility (rc= 0.92 for raw and rc= 0.87 for processed images) and was correlated (r = 0.82 and κ = 0.64). When controlling for body mass index, the associations of quartiles of PD with breast cancer and discriminatory accuracy were similar for the raw (OR: 1.0 (ref.), 2.6 (1.2 to 5.4), 3.1 (1.4 to 6.8), 4.7 (2.1 to 10.6); AUC = 0.63) and processed representations (OR: 1.0 (ref.), 2.2 (1.1 to 4.1), 2.2 (1.1 to 4.4), 3.1 (1.5 to 6.6); AUC = 0.64).ConclusionsPercent density measured with an operator-assisted method from raw and processed FFDM images is reproducible and correlated. Both percent density measures provide similar associations with breast cancer.