Research links tissue patterns on imaging with breast cancer risk
Experts have identified several tissue texture patterns they believe could indicate increased risks of breast cancer.
These findings could be beneficial for women with dense breasts, which increase the risk of developing cancer while making it significantly more difficult to detect. The new research was published Tuesday in the journal Radiology.
“We hypothesized that some patterns or phenotypes would be associated with a high risk of future breast cancer and suggest which women may benefit from supplemental screening or prevention strategies,” senior author, Celine M. Vachon, PhD, a professor of epidemiology at the Mayo Clinic in Rochester, Minnesota, explained. “Other phenotypes could be associated with low risk, ultimately, suggesting less frequent screening.”
For the study, researchers applied radiomics techniques to the mammograms of more than 30,000 women who had no history of breast cancer. From the dataset, 390 features were extracted and then narrowed down into 6 phenotypes. Those phenotypes were then tested in a set of 3,500 mammograms from women with and without a history of breast cancer to determine whether certain patterns were indicative of future risk.
After adjusting for age, body mass index and breast density categories, the team determined that the six phenotypes were associated with invasive breast cancer and symptomatic interval cancers in both White and Black women, but the risks were higher in Black women, the group noted.
“We were surprised to find that these radiomic phenotypes showed suggestion of a stronger risk among Black vs. White women,” co-senior author Despina Kontos, PhD, chief research information officer at Columbia University Irving Medical Center, suggested, adding that the finding “is particularly important as breast cancer tends to be more aggressive in Black women, highlighting the need for novel risk factors in this population.”
The team plans to expand their research into larger groups of women, combining the radiomic patterns they identified with additional data—genetic and lifestyle factors—to achieve further stratification of cancer risk.
Learn more about the team’s findings here.