Using machine learning to assess the risk of thoracic aortic aneurysm rupture
Machine learning-based biomechanical analysis for thoracic aortic aneurysm rupture risk assessment
This study is looking at how advanced computer technology can help doctors better understand the risk of smaller thoracic aortic aneurysms bursting, so they can identify patients who might need surgery sooner.
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 ID | NIH-10993130 on NIH RePORTER |
What this research studies
This research investigates how machine learning can improve the assessment of rupture risk in thoracic aortic aneurysms (TAAs), particularly for those smaller than the current surgical intervention threshold. By analyzing 3D CT images of the thoracic aorta, the study aims to develop automated models that can reconstruct aorta geometry and perform real-time stress analysis. The goal is to create a probabilistic risk index that combines various patient characteristics to provide a more accurate risk assessment. This innovative approach seeks to identify patients who may benefit from surgical intervention before reaching critical sizes.
Who could benefit from this research
Good fit: Ideal candidates for this research are adults with thoracic aortic aneurysms, particularly those with aneurysms smaller than 5 cm in diameter.
Not a fit: Patients with thoracic aortic aneurysms that are already larger than 5.5 cm or those without any aortic aneurysm may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate identification of patients at risk for TAA rupture, potentially saving lives through timely surgical intervention.
How similar studies have performed: Other research has shown promise in using machine learning for medical imaging and risk assessment, indicating that this approach could be effective.
Where this research is happening
Coral Gables, United States
- University of Miami Coral Gables — Coral Gables, United States (Active)
Researchers
- Principal investigator: Liang, Liang — University of Miami Coral Gables
- Study coordinator: Liang, Liang
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.