Using AI and 3D CT scans to predict rupture risk for thoracic aortic aneurysms
Official title: Machine learning-based biomechanical analysis for thoracic aortic aneurysm rupture risk assessment
Funded at University of Miami Coral Gables · NIH-11260144 · Data updated 2026-11-12
This project uses machine learning plus 3D CT scans to help identify adults with thoracic aortic aneurysms—especially smaller ones—who may be at higher risk of rupture.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Miami Coral Gables NIH-funded |
| Lab location | 1 site (Coral Gables, United States) |
| Project start | December 3, 2021 |
| Project end | November 30, 2026 |
| Funding year | 2026 |
| Award (this year) | $505,392 |
| NIH project number | 5R01HL158829-05 |
| Project ID | NIH-11260144 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults (21+) diagnosed with a thoracic aortic aneurysm who have recent CT imaging and are willing to share their scans and follow-up data are ideal candidates.
✕Less likely to help
People without a thoracic aortic aneurysm, those with poor-quality CT imaging, or anyone needing immediate emergency care for a rupture would not benefit from this research approach.
What this research studies
If you take part, your clinical CT images would be processed by AI that builds a 3D model of your thoracic aorta. Computational biomechanics methods would then estimate stresses on the aortic wall in near real time. Those measurements would be combined with other patient features into a probabilistic risk score that accounts for uncertainty. The team will train and test these tools on an existing set of 1,000 patient scans and on new longitudinal patient data to validate predictions. The goal is a faster, automated way to flag small aneurysms that might need closer monitoring or earlier treatment.
Why it matters
Potential benefit: If successful, this approach could catch dangerous aneurysms that are smaller than current size-based rules would flag, potentially preventing sudden rupture.
How similar studies have gone: Related biomechanics and AI studies have shown promise in smaller cohorts, but combining automated 3D reconstruction, real-time stress analysis, and a probabilistic risk index is relatively novel and still under validation.
Where this research is happening
-
University of Miami Coral Gables
Coral Gables, United States Active
Researchers
- Principal investigator: Liang, Liang — University of Miami Coral Gables
- Study coordinator: Liang, Liang
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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.