Quantitative Mammographic Absorptiometry to measure breast density in clinical practice

Abstract:

Purpose: To determine if Quantitative Mammographic Absorptiometry (QMA), a novel automated method to measure volumetric compositional breast density that has been integrated into clinical care, is associated with standard breast cancer risk factors. Methods: Radiographic uniformity and calibration of attenuation to measure breast composition from standard mammograms is not known. We designed a calibration method that includes a correction algorithm, quality control and within-image reference phantom to automatically quantify breast density. The within-image reference phantom consists of two polymers atomically equivalent to adipose fat and breast fibroglandular materials. The phantom is being compressed and imaged with the screening craniocaudal views at California Pacific Medical Center Breast Health Center in San Francisco, CA. The reference phantom has been placed between compression surfaces. For small breasts, the two wedges slide away from each other to provide a thin reference at the thickness of the breast, while with large breasts, the wedges spring together for a thick reference. Comparing the attenuation of the reference materials to the breast pixels calibrates each breast pixel to % fibroglandular density. Summing all pixels in a mammogram results in a total percent fibroglandular density (BDQMA). Risk factor information isself-reported and collected on a survey with standardized questions created by the NIH-funded San Francisco Mammography Registry. We tested the association between BDQMA and age, family history of breast cancer, age at first live birth, menopause, postmenopausal hormone therapy and body massindex adjusting for age. Results: From April to December 2004, 1764 women had a BMQMA measure with 7% having a measure of <10%, 33% of 10-25%, 41% of 26-50%, 17% of 51-75%, and 2% greater than 75%. We found strong relationships between BDQMA and age (P< 0.001), current postmenopausalhormone therapy (P= 0.05), menopause (P< 0.001), and body mass index (P<0.001). BDQMA was not associated with age at first live birth or family history of breast cancer. Analyses measuring the association of BDQMA and breast cancer are underway. Conclusion: BDQMA is associated with characteristics that are known from previous work to be related to mammographic breast density, a strong predictor of breast cancer risk. This suggests BDQMA will be associated with breast cancer risk.

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