Predicting heart changes to improve care for women with severe aortic stenosis
Leveraging Sexual Dimorphism to Predict Cardiac Remodeling and Enhance Treatment in Women with Severe Aortic Stenosis
This project uses advanced medical imaging and computer models to better predict how women's hearts remodel from severe aortic stenosis so care can be more personalized.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project ID | NIH-11175320 on NIH RePORTER |
What this research studies
From my perspective as a patient, the team will analyze heart images and use artificial intelligence and shape-analysis tools to map how the left ventricle changes in women with severe aortic stenosis. They will combine convolutional neural networks with mathematical models like inverse finite element analysis to create personalized models of heart structure and function. The focus is on sex-specific anatomical and functional differences to understand why women have different outcomes and receive different treatment rates. The ultimate aim is to use these models to guide timing and type of aortic valve interventions to improve survival for women.
Who could benefit from this research
Good fit: Ideal candidates are women with clinically diagnosed severe aortic stenosis who have accessible cardiac imaging (such as echocardiography or CT) and clinical follow-up data.
Not a fit: People without aortic stenosis, men (if sex-specific models are not applied to them), or patients without suitable cardiac imaging are unlikely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this work could help clinicians tailor valve-timing and treatment strategies for women, potentially lowering complications and improving survival.
How similar studies have performed: Related AI and imaging approaches have shown promise for heart structure analysis, but applying sex-specific computational remodeling models to improve treatment decisions for women with severe AS is relatively novel.
Where this research is happening
Boston, United States
- Brigham and Women's Hospital — Boston, United States (Active)
Researchers
- Principal investigator: Rikhtegar Nezami, Farhad — Brigham and Women's Hospital
- Study coordinator: Rikhtegar Nezami, Farhad
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.