Linking normal aortic valve blood flow patterns to risk of aortic valve narrowing
Official title: Deep learning to link normal variation in aortic valve hemodynamics to pathogenesis of aortic stenosis
Funded at University of California, San Francisco · NIH-11377950 · Data updated 2026-11-12
This grant studies how normal differences in how the aortic valve moves and carries blood might influence who develops aortic stenosis.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | August 1, 2025 |
| Project end | July 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $673,293 |
| NIH project number | 5R01HL178603-02 |
| Project ID | NIH-11377950 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults with or without aortic valve disease who can contribute large-scale imaging and genetic data from population studies.
✕Less likely to help
Patients without access to or from populations not represented in the study datasets may not directly benefit.
What this research studies
Researchers at UCSF will analyze measurements from up to 100,000 people to understand how normal variation in aortic valve hemodynamics relates to the risk of aortic stenosis. They will leverage genetic and epidemiological data to identify shared factors that connect everyday valve function with disease development. The work aims to uncover new targets for treatment by linking population-level valve measurements to genetic risk. This approach could point to why some people develop clinically significant valve narrowing while others do not.
Why it matters
Potential benefit: Findings could lead to earlier identification of people at risk and inform new strategies to prevent or treat aortic stenosis.
How similar studies have gone: Preliminary data from tens of thousands of participants suggest shared genetic and anatomical factors related to normal valve variation and disease risk.
Where this research is happening
-
University of California, San Francisco
San Francisco, United States Active
Researchers
- Principal investigator: Pirruccello, James — University of California, San Francisco
- Study coordinator: Pirruccello, James
Related research
Other NIH-funded projects on the same topics.
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4D heart and vessel imaging using AI to analyze standard chest scans
A cloud-based AI tool aims to derive 4D blood-flow information from routine chest MRI scans to help monitor thoracic aortic aneurysm more accurately.
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AI-powered screening and monitoring for aortic stenosis in older adults
A powerful new AI-based approach uses a simple heart rhythm test and a hand-held ultrasound to detect and monitor advanced aortic valve narrowing in people aged 65 and older.
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AI tool to get detailed aorta blood-flow maps from routine chest MRIs
This project uses artificial intelligence to create detailed 4D pictures of aortic blood flow from standard chest MRI scans for people with thoracic aortic aneurysms.
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AI to find and monitor aortic valve narrowing (aortic stenosis)
This project uses AI on a single-lead ECG followed by AI-powered handheld ultrasound to find and track aortic valve narrowing in older adults.
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Using AI to improve heart imaging for better assessment of aortic aneurysms
This study is working on a new online tool that uses regular chest images to create detailed blood flow information for people with thoracic aortic aneurysms, helping doctors monitor and manage their condition more easily and quickly.
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Using AI to improve detection and monitoring of aortic stenosis
This study is exploring how artificial intelligence can help doctors find and keep track of aortic stenosis, a heart condition that mainly affects older adults, by using easy-to-use tools like simple heart tests and handheld ultrasounds to spot serious cases more accurately and quickly.
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.