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Compositional Breast Density as a Risk Factor

Grant #: Research Grant
PI Names: Shepherd J, Kerlikowske K, Cummings S
Title: Compositional Breast Density as a Risk Factor
Institute: California Breast Cancer Research Fund


Background: Other than age, mammographic breast density has been shown to be one of the strongest available indicators of breast cancer risk. Women who have greater than 50% of total breast area that is mammographically dense are at 3 to 5 fold greater risk of breast cancer than women with less than 25% mammographically dense breasts. Importantly, the prevalence of mammographically dense breasts is high among breast cancer cases with 42% of cases with 50% or more mammographically dense breasts compared with 32% of those without breast cancer (OR= 3.1). Although mammographic density is a widely used technique for clinical trials, it has serious limitations for clinical use. In this proposal, the investigators present two novel methods for measuring accurate breast compositional density in terms of either percentage fat or glandular density.

Hypothesis: The investigators' hypothesis is that that absolute breast compositional density, measured using novel techniques developed for bone densitometry, can be used as an accurate and precise surrogate marker/outcome for breast cancer and as a clinical risk classifier. In addition, the investigators believe that their techniques will be a stronger predictor of risk than current methods. This study is a preliminary investigation into this hypothesis.

Objectives/Aims: These aims will set the groundwork for a large prospective study to better characterize compositional density. Its aims are:

  • To further develop and validate a method to measure tissue composition using single x-ray absorptiometry (SXA) techniques using standard mammogram x-ray protocols against known standards of compositional density (DXA and phantoms).
  • To gather preliminary data to determine whether women with a greater proportion of compositionally dense breast tissue are at greater risk of breast cancer than women with less compositionally dense breasts controlling for known risk factors.
  • To quantify the least significant change in breast tissue composition that can be monitored using either the SXA or DXA methodology.
  • To contrast and describe the relationships of breast compositional density methods to mammographic density and BI-RADS categorical scoring systems in terms of cancer risk sensitivity, correlations, and the ability to monitor drug therapies.

Methods: Twenty-five women with breast cancer and 25 matched controls will be recruited from the San Francisco Mammography Registry and measured using the DXA, SXA, and Mammographic Density method, and the BI-RADS scores. Odds ratios for cancer risk and inter-correlation results will be generated for each method. Repeat scans with breast repositioning of all participants will be performed. The expected least significant changes in density will be calculated based on these precision values. Left/Right breast comparisons will be performed for the DXA method and compared to the mammographic density. In addition, the SXA methodology will be further developed for the in vivo work to include peripheral breast tissue definition, optimization of field nonuniformity corrections, and optimization of the SXA and field correction phantoms.

Impact on breast cancer: Breast compositional density, integrated into either routine mammography or a bone densitometry assessment, will have several important roles in clinical practice and clinical research: (1) To give women and doctors an estimate of breast cancer risks, (2) To identify women who will benefit most by available (and coming) treatments to prevent breast cancer, (3) To monitor preventive treatments and behavioral changes, (4) To determine whether these treatments reduce breast density and the associated risk of breast cancer, (5) To enable pharmaceutical companies and researchers to test the potential value of promising new drugs for reducing risk of breast cancer before committing to hugely expensive Phase III and Phase IV trials.