Automated MRI analysis of brain artery walls across scanner types
Automated Intracranial Vessel Wall Analysis Pipeline for Multi-contrast Multi-platform Applications
This project builds automated computer tools to read MRI images of the walls of brain arteries to help doctors diagnose and treat people at risk for stroke.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project ID | NIH-11164531 on NIH RePORTER |
What this research studies
They will build a computer pipeline that automatically analyzes 3D, multi-contrast MRI scans of intracranial artery walls using deep learning and domain-adaptive methods so it works across different MRI machine brands. The pipeline will automate image registration, artery tracing, labeling, and quantitative measurements of vessel wall features. The team will test and validate the tools on images from multiple scanner platforms to reduce variability between centers. The aim is to make vessel wall MRI faster and more consistent so clinicians can better identify artery disease linked to unexplained strokes.
Who could benefit from this research
Good fit: Ideal candidates are people with suspected intracranial atherosclerotic disease or embolic stroke of undetermined source who are undergoing intracranial vessel wall MRI.
Not a fit: People without intracranial vessel wall MRI scans, those with clearly non-atherosclerotic causes of stroke, or those unable to have MRI may not directly benefit from this work.
Why it matters
Potential benefit: If successful, this could make diagnosis of intracranial artery wall disease faster and more consistent across hospitals, helping guide treatment decisions to prevent stroke.
How similar studies have performed: Earlier semiautomatic methods from this group and other AI-based MRI tools have shown promise, but a fully automated, validated cross-platform vessel wall analysis remains relatively novel.
Where this research is happening
Seattle, United States
- University of Washington — Seattle, United States (Active)
Researchers
- Principal investigator: Yuan, Chun — University of Washington
- Study coordinator: Yuan, Chun
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.