Improving imaging techniques for brain blood vessel identification
Official title: Vessel Identification and Tracing in DSA Image Series for Cerebrovascular Surgical Planning
Funded at Brigham and Women's Hospital · NIH-10726103 · Data updated 2026-11-12
This study is working on improving brain imaging techniques to help doctors see blood vessels more clearly, especially in tricky cases like arteriovenous malformations (AVMs), using smart computer technology to make surgeries safer and more effective.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | August 1, 2023 |
| Project end | July 31, 2025 |
| Funding year | 2023 |
| Award (this year) | $179,000 |
| NIH project number | 1R03EB033910-01A1 |
| Project ID | NIH-10726103 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients diagnosed with arteriovenous malformations or other neurovascular pathologies requiring surgical intervention.
✕Less likely to help
Patients with non-cerebrovascular conditions or those not requiring surgical treatment may not benefit from this research.
What this research studies
This research focuses on enhancing Digital Subtraction Angiography (DSA) imaging to better visualize and identify blood vessels in the brain, particularly in complex cases like arteriovenous malformations (AVMs). By utilizing machine learning algorithms, the project aims to develop tools that can accurately distinguish between arteries and veins in DSA images, making it easier for clinicians to plan and execute neurovascular surgeries. The approach includes creating a classification system for different types of arteries and assessing the impact of these advancements on surgical planning through retrospective studies.
Why it matters
Potential benefit: If successful, this research could lead to more precise surgical planning and improved outcomes for patients with complex cerebrovascular conditions.
How similar studies have gone: Similar research approaches using machine learning in medical imaging have shown promise in enhancing diagnostic accuracy and surgical planning.
Where this research is happening
-
Brigham and Women's Hospital
Boston, United States Active
Researchers
- Principal investigator: Haouchine, Nazim — Brigham and Women's Hospital
- Study coordinator: Haouchine, Nazim
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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.