Using Mammographic Density to Predict Breast Cancer

Fall 2013

Dr. FuhrmanUAMS scientists are tracking key risk factors for breast cancer in an effort to measure that risk. One of those risk factors recognized for more than a decade is the density of breast tissue as it shows up in a mammogram.

Barbara Fuhrman, Ph.D., an assistant professor of epidemiology in the UAMS College of Public Health, is leading research looking more closely at a woman’s mammographic density and her risk for breast cancer.

Mammographic density (MD) is the measure of the extent of radiodense breast tissue. Fuhrman said that this factor has consistently been one of the best predictors of breast cancer risk in women other than age. Also, because radiodense tissue can obscure tumors, MD is also an indicator of the sensitivity of mammographic screening.

Even though MD has important implications for breast screening and health, its measurement has not been standardized or incorporated into screening algorithms. Methods for measuring MD have either been too time-consuming or subjective for use in the clinic.

With this study, Fuhrman and her colleagues are using the UAMS Enterprise Data Warehouse to collect information on women who have undergone digital mammography at UAMS.

They retrieve the images for each participant and then use special software to measure MD. They will use this dataset to demonstrate that the new automated measures predict breast cancer risk. They will also look at the impact of MD on screening practices and outcomes in women seen at UAMS.

Fuhrman said that so far, this method has proved as good as the standard method at predicting risk. In addition, it does not require a technician, and is more efficient when going through a large number of images.