Using artificial intelligence to improve heart rhythm treatments for atrial fibrillation
Official title: Artificial intelligence analysis of atrial remodeling evolution in patients with atrial fibrillation: Towards optimal ablation strategies
Funded at Johns Hopkins University · NIH-11009043 · Data updated 2026-11-12
This study is looking at how artificial intelligence can help understand changes in the heart for people with atrial fibrillation, so doctors can create better, personalized treatment plans after a procedure called catheter ablation, making it less likely that the heart rhythm problem will come back.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Johns Hopkins University NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project start | January 20, 2023 |
| Project end | December 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $735,422 |
| NIH project number | 5R01HL166759-03 |
| Project ID | NIH-11009043 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients with drug-refractory atrial fibrillation who are considering catheter-based ablation.
✕Less likely to help
Patients whose atrial fibrillation is well-managed with medication may not benefit from this research.
What this research studies
This research investigates how artificial intelligence can analyze changes in the heart's atria in patients with atrial fibrillation, a common heart rhythm disorder. By combining advanced imaging techniques and electroanatomical mapping, the study aims to identify the underlying causes of arrhythmia recurrence after catheter ablation, a procedure used to treat this condition. The goal is to develop personalized ablation strategies that take into account the unique remodeling of the atrial tissue in each patient, ultimately improving treatment outcomes and reducing the need for repeat procedures.
Why it matters
Potential benefit: If successful, this research could lead to more effective treatments for atrial fibrillation, reducing symptoms and improving quality of life for patients.
How similar studies have gone: Other research has shown promise in using artificial intelligence for analyzing cardiac conditions, suggesting that this approach could yield significant advancements.
Where this research is happening
-
Johns Hopkins University
Baltimore, United States Active
Researchers
- Principal investigator: Trayanova, Natalia a. — Johns Hopkins University
- Study coordinator: Trayanova, Natalia a.
Related research
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-
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-
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This NIH grant explores how a heart protein called JNK2 may drive atrial fibrillation, blood clots, and stroke, and whether it could serve as a biomarker and new treatment approach.
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A new tool uses patient data and heart MRI markers to identify heart failure patients without atrial fibrillation who might benefit from anticoagulation while minimizing bleeding risk.
-
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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.