AI-enhanced MRI to find early Alzheimer's
Deep-Learning Enhanced ASL MRI For Early AD Assessment
This project uses artificial intelligence to improve a non‑invasive MRI that measures brain blood flow so it can better spot early Alzheimer's in adults.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Maryland Baltimore NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project ID | NIH-11248372 on NIH RePORTER |
What this research studies
You would get a non‑invasive MRI scan called arterial spin labeling (ASL) that measures blood flow in different brain regions. The research team will train deep‑learning algorithms to boost image clarity, increase spatial detail, and shorten scan time. They will tackle noise, resolution, and scan-length problems separately and combine the improvements into a single approach. The improved ASL method is meant to fit into routine MRI visits so it can be used safely and repeatedly to track early changes in people with memory concerns.
Who could benefit from this research
Good fit: Adults (21+) with memory complaints, mild cognitive impairment, or suspected early Alzheimer's who can undergo MRI scans would be ideal candidates.
Not a fit: People with advanced Alzheimer's, those whose symptoms are from non‑AD conditions, or anyone who cannot have an MRI (for example due to implanted devices) may not benefit from this approach.
Why it matters
Potential benefit: If successful, this could enable earlier, safer, and more precise detection and monitoring of Alzheimer's using routine MRI scans.
How similar studies have performed: ASL MRI has shown promise for Alzheimer's and AI has improved MRI image quality in early studies, but combining deep learning with ASL for early AD detection is still relatively new.
Where this research is happening
Baltimore, United States
- University of Maryland Baltimore — Baltimore, United States (Active)
Researchers
- Principal investigator: Wang, Ze — University of Maryland Baltimore
- Study coordinator: Wang, Ze
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.