Quantitative Classification of Mammographic Densities and Breast Cancer Risk: Results From the Canadian National Breast Screening Study

Abstract

The radiographic appearance of the female breast varies from woman to woman depending on the relative amounts of fat and connective and epithelial tissues present. Variations in the mammographic density of breast tissue are referred to as the parenchymal pattern of the breast. Fat is radiologically translucent or clear (darker appearance), and both connective and epithelial tissues are radiologically dense (lighter appearance). Previous studies have generally supported an association between parenchymal patterns and breast cancer risk(greater risk with increasing densities), but there has been considerable heterogeneity in risk estimates reported. Purpose: Our objective was to determine the level of breast cancer risk associated with varying mammographic densities by quantitatively classifying breast density with conventional radiological methods and novel computer-assisted methods. Methods: From the medical records of a cohort of 45 000 women assigned to mammography in the Canadian National Breast Cancer Screening Study (NBSS), a multicenter, randomized trial, mammograms from 354 case subjects and 354 control subjects were identified. Case subjects were selected from those women in whom histologically verified invasive breast cancer had developed 12 months or more after entering the trial. Control subjects were selected from those of similar age who, after a similar period of observation, had not developed breast cancer. The mammogram taken at the beginning of the NBSS was the image used for measurements. Mammograms were classified into six categories of density, either by radiologists or by computer-assisted measurements. All radiological classification and computer-assisted measurements were made using one craniocaudal view from the breast contralateral to the cancer site in case subjects and the corresponding breast of control subjects. All P values represent two-sided tests of statistical significance. Results: For all subjects, there was a 43% increase in the relative risk (RR) between the lower and the next higher category of density, as determined by radiologists, and there was a 32% increase as determined by the computer-assisted method. For all subjects, the RR in the most extensive category relative to the least was 6.05 (95% confidence interval [CI] = 2.82–12.97) for radiologists and 4.04 (95% CI = 2.12–7.69) for computer-assisted methods. Statistically significant increases in breast cancer risk associated with increasing mammographic density were found by both radiologists and computer-assisted methods for women in the age category 40–49 years (P =.005 for radiologists and P = .003 for computer-assisted measurements) and the age category 50–59 years (P =.002 for radiologists and P =. 001 for computer-assisted measurements). Conclusion: These results show that increases in the level of breast tissue density as assessed by mammography are associated with increases in risk for breast cancer. [J Natl Cancer Inst 87: 670–675, 1995]