AI and Polygenic Risk Scores May Reshape Breast Cancer Screening Within the Decade

What if your patient's mammogram could predict her risk of developing breast cancer in the next five years—before any tumor is visible?

In this final segment of our interview series, breast imaging expert Donna M. Plecha, MD, peers into the near future of breast cancer screening, and it's more personalized than ever imagined. Plecha introduces emerging technologies that are already outperforming traditional risk assessment tools and discusses how these innovations will fundamentally change screening recommendations within the next decade.

The most exciting development? Artificial intelligence algorithms that analyze mammography images to predict future cancer risk—not by detecting early tumors, but by identifying invisible patterns that the human eye cannot perceive. These AI tools are already beating the widely-used Gail model for risk prediction, and they're not yet FDA-approved. When they are, they could revolutionize how we stratify patients and personalize screening intervals.

Key topics covered in this segment:

• How AI analyzes mammograms to predict 5-year breast cancer risk
• Why AI risk prediction outperforms the Gail model
• The potential role of chemoprevention for AI-identified high-risk patients
• Polygenic risk scores: personalized DNA-based risk assessment
• The vision for truly individualized screening pathways
• Why these changes may arrive sooner than you think