A new technology has been developed by researchers at Washington University School of Medicine in St. Louis harnessing AI to “analyze mammograms and improve the accuracy of predicting a woman’s personalized five-year risk of developing breast cancer.”
The technology, which has been licensed to Prognosia Inc., received Breakthrough Device designation from the FDA. The technology is “compatible with both types of mammogram imaging available: the four 2D views of the breast produced by full-field digital mammography and the synthetic 3D view of the breast produced by digital breast tomosynthesis. Importantly, the system produces an absolute five-year risk that makes it possible to compare a woman’s risk to an average risk based on national breast cancer incidence rates. This provides a meaningful estimate that is aligned with the U.S. national risk reduction guidelines, so that clinicians will know what steps to take next if a woman’s risk is elevated.”
The software is a “pre-trained machine learning system that analyzes mammogram images and provides an estimate of how likely a patient is to develop breast cancer over the next five years, based solely on images and a woman’s age.” The developers say that this system, called Prognosia Breast, is “2.2 times more accurate” than the standard method in estimating. It was trained on past mammograms from “tens of thousands of individuals.”
Even with widespread screening as it is now, “about 34% of breast cancer patients in the U.S. are diagnosed at later stages of the disease. According to the investigators, being able to assess risk up to five years in advance of the onset of cancer is likely to improve early detection, reducing the number of late-stage cancers diagnosed.” The developers of the system are planning a clinical trial applying the risk score to the “standard mammography screening protocols.”
