Better brain scan methods to predict early Alzheimer's progression
Multi-Site Neuroimage Harmonization for Personalized Brain Disorder Analysis
This project builds computer tools to combine and standardize brain scans and fluid tests from many hospitals so people with early memory concerns get clearer, personalized predictions about Alzheimer’s risk.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project ID | NIH-11325449 on NIH RePORTER |
What this research studies
Researchers are developing machine learning tools that clean up and harmonize MRI, PET, and cerebrospinal fluid data from many hospitals so results are comparable. They will combine data from over 5,300 people collected at 79 imaging centers to train and test these methods. The goal is to give a more precise, subject-specific interpretation of imaging for people with subjective cognitive decline or other early signs of Alzheimer's. The work mainly analyzes existing patient scans and fluid samples rather than testing new drugs or treatments.
Who could benefit from this research
Good fit: People with early memory complaints or subjective cognitive decline, especially those who have had MRI, PET, or cerebrospinal fluid testing, would be the most relevant candidates.
Not a fit: People without brain imaging or CSF data, or those whose memory problems are due to non‑Alzheimer causes, may not see direct benefit from this work.
Why it matters
Potential benefit: If successful, these tools could provide more accurate, personalized predictions of Alzheimer’s progression and help match people to early interventions or clinical trials.
How similar studies have performed: Previous harmonization and machine learning efforts have shown promise for combining multi-site brain scans but still face challenges and are not yet widely adopted in clinical care.
Where this research is happening
Chapel Hill, United States
- Univ of North Carolina Chapel Hill — Chapel Hill, United States (Active)
Researchers
- Principal investigator: Liu, Mingxia — Univ of North Carolina Chapel Hill
- Study coordinator: Liu, Mingxia
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.