Using AI to understand aortic valve disease and predict patient outcomes
AI-enabled characterization of fibrocalcific aortic valve disease and inflammation from CT Angiography: Patient-specific outcome prediction
This project uses artificial intelligence to better understand aortic valve disease from CT scans and predict how the condition might progress for patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cedars-Sinai Medical Center NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project ID | NIH-11181172 on NIH RePORTER |
What this research studies
Aortic stenosis is a common heart valve condition where the valve narrows, leading to heart problems. Currently, doctors often wait until symptoms are severe before recommending valve replacement, but there isn't a good way to know which patients will get worse quickly. This project uses advanced artificial intelligence to analyze CT scans of the heart valve, looking for specific tissue characteristics and signs of inflammation. By combining these detailed scan findings with other patient information, we hope to create a new way to predict how the disease will progress and the risk of complications after valve replacement. This could help doctors make more timely decisions about care.
Who could benefit from this research
Good fit: This work is relevant for patients diagnosed with aortic stenosis who undergo CT angiography.
Not a fit: Patients without aortic stenosis or those who do not undergo CT angiography would not directly benefit from this specific prediction tool.
Why it matters
Potential benefit: If successful, this work could help doctors predict which patients with aortic stenosis are at higher risk for rapid disease progression or complications after valve replacement, allowing for more personalized and timely treatment plans.
How similar studies have performed: Preliminary studies guide this proposal, suggesting a foundation for this AI-driven approach, though the integrated risk score is a novel development.
Where this research is happening
Los Angeles, United States
- Cedars-Sinai Medical Center — Los Angeles, United States (Active)
Researchers
- Principal investigator: Dey, Damini — Cedars-Sinai Medical Center
- Study coordinator: Dey, Damini
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.