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For this week’s post, I will focus on the recent, groundbreaking breast cancer research coming out of the University of California-Irvine, where a new mammography technique called quantitative spectral mammography is being developed. The research was recently presented by Sabee Molloi, PhD, a professor and vice chairman of research of the University of California, Irvine, at the 54th Annual Meeting of the American Association of Physicists in Medicine (AAPM) in Charlotte, NC, on July 26, 2012. Today’s blog post will focus on the content of that presentation.
Spectral mammography allows the health care provider or researcher to measure breast density, which actually refers to the amount of white area on a breast that, otherwise, appears black on a mammogram. The balance of white and black reflects the breast composition and relative amount of glandular tissue, connective tissue, and adipose tissue in the breast. Over the last 3 decades, studies have established that women with higher breast density have a higher risk of developing breast cancer than women with lower breast density, especially when other risk factors, such as a family history of breast cancer, are present.
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“Although breast density is a useful tool for estimating breast cancer risk, it is difficult to accurately measure it,” Dr. Molloi explained in his presentation. “In traditional aerial measurements, one can measure the breast pixels on the actual mammogram to project an image of the compressed breast…this method ignores the 3-D character of a real breast, making all aerial measurements of mammograms look identical to each other.” He further explains that, in order to measure volumetric breast density, it is necessary to know the glandular and adipose tissue content in each pixel. This information is not possible to ascertain from a standard mammogram and, therefore, difficult to obtain in practice.
“Spectral mammography allows the image to be viewed at two different energy levels, instead of just one, helping quantify the density of a woman’s breasts and, in turn, her relative risk. The higher sensitivity of this technology can help to identify high risk breast cancer patients,” said Dr. Molloi in his presentation.
Molloi’s group at UC-Irvine has created a method that measures volumetric breast density in a spectral mammography system using low-dose radiography, thus allowing women to have more frequent mammograms. The group is now conducting pilot studies to evaluate the system in a clinical setting. This technique will be tested for user/radiologist bias, reliability as a statistical tool for estimating breast cancer risk, and more.
Dr. Molloi concluded: “Our quantitative spectral mammography method could become the standard of care for the women at high risk for developing cancer who could benefit from more frequent mammograms.”
Readers, how will spectral mammography impact the way you diagnose and monitor breast cancer in your own practice?
