Predicting Heart Failure Risk After a Heart Attack with Computer Models
Official title: Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction
Funded at Yale University · NIH-11351029 · Data updated 2026-11-12
A patient-focused look at how advanced computer models of the heart, built from MRI scans, could predict who might develop heart failure after a heart attack.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project start | July 1, 2024 |
| Project end | June 30, 2027 |
| Funding year | 2026 |
| Award (this year) | $248,959 |
| NIH project number | 5R00HL161313-05 |
| Project ID | NIH-11351029 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are individuals who have experienced a myocardial infarction and are being evaluated for heart remodeling and risk of heart failure.
✕Less likely to help
Patients who have not had a heart attack or current conditions not involving heart remodeling may not benefit from this research.
What this research studies
This project uses detailed computer simulations of heart tissue and whole-heart movement, guided by MRI data, to forecast how the heart might remodel after a heart attack. The goal is to identify which patients are at higher risk of long-term heart failure so doctors can tailor treatment sooner. By validating these models with measurements from animal and human hearts, the research aims to create personalized predictions of heart remodeling after myocardial infarction. If successful, clinicians could use this approach to guide therapies that prevent deterioration and improve quality of life.
Why it matters
Potential benefit: This work could lead to personalized predictions that help prevent heart failure after a heart attack, guiding earlier and more targeted care.
How similar studies have gone: Previous studies using cardiovascular models and MRI data have shown promise in predicting remodeling, but this project aims to enhance accuracy with a cell-scale framework.
Where this research is happening
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: Pfaller, Martin R — Yale University
- Study coordinator: Pfaller, Martin R
Related research
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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.