Artificial intelligence is beginning to show that it can not only detect breast cancer on mammograms, but it can predict a patient’s future risk of cancer. A new study in JAMA Network Open showed that a U.S. university’s homegrown AI algorithm worked well in predicting breast cancer risk across diverse ethnic groups.
Breast cancer screening traditionally has used a one-size-fits-all model based on age for determining who gets mammography.
- But screening might be better tailored to a woman’s risk, which can be calculated from various clinical factors like breast density and family history.
At the same time, research into mammography AI has uncovered an interesting phenomenon – AI algorithms can predict whether a woman will develop breast cancer later in life even if her current mammograms are normal.
- Indeed, last week AI startup Clairity announced FDA de novo clearance for Clairity Breast, which it said was the first FDA-authorized tool for predicting five-year cancer risk from mammograms.
The new study involves a risk prediction algorithm developed at Washington University School of Medicine in St. Louis that uses AI to analyze subtle differences and changes in mammograms over time, including texture, calcification, and breast asymmetry.
- The algorithm then generates a mammogram risk score that can indicate the risk of developing a new tumor.
In clinical trials in British Columbia, the algorithm was used to analyze full-field digital mammograms of 206.9k women aged 40-74, with up to four years of prior mammograms available. Results were as follows …
- The algorithm had an AUROC of 0.78 for predicting cancer over the next five years.
- Performance was higher for women older than 50 compared to 40-50 (AUROC of 0.80 vs. 0.76).
- Performance was consistent across women of different races.
- 9% of women had a five-year risk higher than 3%.
The algorithm’s inclusion of multiple mammography screening rounds is a major advantage over algorithms that use a single mammogram as it can capture changes in the breast over time.
- The model also showed consistent performance across ethnic groups, a problem that has befallen other risk prediction algorithms trained mostly on data from White women.
The Takeaway
The new study advances the field of breast cancer risk prediction with a powerful new approach that supports the concept of more tailored screening. This could make mammography even more effective than the one-size-fits-all approach used for decades.
