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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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