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21 March 2008 Utilization of mammographic complexity for improving risk assessment and cancer detection
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Abstract
Currently, breast cancer screening protocols are based on a woman's age, but not on other risk factors or on the physical characteristics of her breasts. One commonly cited risk factor is dense breast tissue. This study is part of an effort to provide basic information needed to develop automatically, individualized screening protocols, by clarifying the relationships between age, risk, breast composition, lesion conspicuity, and other factors. In this project, a database was established that includes 227 cancer negative cases and 116 cancer positive cases across a wide range of age groups. In the cancer positive cases, we included a subgroup in which the cancer had been missed in the previous exam. Using our physics based model of breast density, we quantified percentage of breast parenchyma as an index of density. Density distributions and changes over time were analyzed. The most significant finding within this data was a significantly slower density decrease over the time in the cancer positive group than in the cancer negative group, with no overall difference in the density distribution in those two groups. False negative cases were found to be significantly more dense than true positive cases. In addition, our results showed a trend of density decrease with increasing age, which is in agreement with others' widely reported results.
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Xiao Hui Wang, Jill King, Saraswathi Golla M.D., Janet E. Durick M.D., Cynthia Britton M.D., Jules H. Sumkin, Joseph K. Leader, and Walter F. Good "Utilization of mammographic complexity for improving risk assessment and cancer detection", Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 69161M (21 March 2008); https://doi.org/10.1117/12.770587
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