Better 5-year breast cancer risk prediction from 3D mammograms
Advancing breast cancer risk assessment with digital breast tomosynthesis
This project uses artificial intelligence on 3D mammogram images to improve 5-year breast cancer risk predictions for Black women.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Washington University NIH-funded |
| Lab location | 1 site (Saint Louis, United States) |
| Project ID | NIH-11194399 on NIH RePORTER |
What this research studies
You would be part of work that trains deep learning models on a large set of digital breast tomosynthesis (DBT) images linked to five-year follow-up from Black women across multiple sites. The team will develop imaging-based risk signatures and place emphasis on model interpretability so clinicians can see which image features matter. Researchers will compare their AI models to existing mammography-based tools and adapt methods to the newer DBT imaging standard. The focus is on tailoring risk prediction to Black women who have been underrepresented in prior AI studies.
Who could benefit from this research
Good fit: Ideal candidates are Black women who receive routine screening with digital breast tomosynthesis (DBT) and whose images can be used for research, especially those without a prior breast cancer diagnosis.
Not a fit: People without DBT images, non-Black women, or those already diagnosed with breast cancer are less likely to benefit from this specific risk model.
Why it matters
Potential benefit: If successful, this could help identify Black women at higher 5-year breast cancer risk so screening and prevention can be more personalized.
How similar studies have performed: Previous AI work using 2D mammograms has shown promise but was mainly developed in White populations, while DBT-based and Black population–focused models remain less tested.
Where this research is happening
Saint Louis, United States
- Washington University — Saint Louis, United States (Active)
Researchers
- Principal investigator: Gastounioti, Aimilia — Washington University
- Study coordinator: Gastounioti, Aimilia
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.