ProFound AI Risk utilizes breast complexity findings, automated breast density and age in order to calculate a woman's short-term, absolute risk of breast cancer. All of this information is within a woman's screening mammogram, making risk assessment simple. Results include the woman's absolute breast cancer risk score and breast cancer risk category [low, general, moderate and high].
"The need for technology like this has never been greater. The COVID pandemic truly highlighted the absence of a practical solution to accurately determine an individual's risk of developing breast cancer between screenings, as several medical societies recommended last year that women of 'average risk' postpone mammograms. The issue is, most women simply don't know their risk," added Stevens. "As clinicians and facilities recover from the impact of the pandemic this year, they are presented with unprecedented challenges, including a significant reduction in patient volume, loss of income, and a growing mammography backlog. This technology offers a viable solution for the challenges clinicians are facing today and offers a solution that will remain relevant for years to come."
Regular, age-based mammography screening reduces breast cancer mortality by approximately 20%,[4] but screening mammography can still miss 20 to 40% of breast cancers.[5],[6] Many of these cancers are diagnosed as interval breast cancers, defined as those that emerge after a normal mammogram but before the woman's next scheduled screening. These tumors are often diagnosed at a later stage than cancers detected by screening, and are associated with an increased risk of breast cancer-specific mortality, compared with cancers detected by screening.[7]
Clinicians have traditionally considered risk factors such as family history as a way to assess women's risks of developing breast cancer, but about 85% of breast cancers occur in women who have no family history of breast cancer.[8]
ProFound AI Risk was created from an exclusive relationship between iCAD and leading researchers at the Karolinska Institutet in Stockholm, Sweden, one of the world's foremost medical research universities and the home of the Nobel Assembly, which selects the Nobel laureates in Physiology or Medicine. This partnership built upon a previous research agreement whereby researchers at the Karolinska Institutet developed a breast cancer risk prediction model using information identified in mammography images provided by iCAD's AI solutions.
