Automated analysis of blood vessel walls in the brain using advanced imaging techniques
Automated Intracranial Vessel Wall Analysis Pipeline for Multi-contrast Multi-platform Applications
This study is working on a new way to use MRI scans to better understand and diagnose brain blood vessel problems, especially for patients who have had unexplained strokes, so that doctors can provide more effective treatments.
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-10910103 on NIH RePORTER |
What this research studies
This research focuses on developing an automated pipeline to analyze intracranial vessel wall images obtained through magnetic resonance imaging (MRI). By utilizing advanced deep learning techniques, the project aims to improve the diagnosis of intracranial atherosclerotic disease (ICAD) and related conditions, particularly for patients experiencing embolic strokes of undetermined source (ESUS). The approach will standardize the analysis across different MRI scanner platforms, ensuring consistent and accurate measurements that can facilitate multi-center studies. This could ultimately lead to better treatment options for patients with vascular issues in the brain.
Who could benefit from this research
Good fit: Ideal candidates for this research include patients with suspected intracranial atherosclerotic disease or those experiencing unexplained strokes.
Not a fit: Patients with non-vascular related neurological conditions or those not experiencing any stroke symptoms may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate diagnoses and improved treatment strategies for patients at risk of stroke due to intracranial vascular diseases.
How similar studies have performed: Previous research has shown promise in using automated imaging analysis for vascular conditions, indicating that this approach could be effective.
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.