Making MRI brain-age estimates understandable to spot Alzheimer’s risk
Interpretable machine learning to synergize brain age estimation and neuroimaging genetics
Researchers will build easy-to-understand MRI-based tools that estimate a person’s “brain age” to help people worried about Alzheimer’s disease or mild memory changes.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Southern California NIH-funded |
| Lab location | 1 site (Los Angeles, UNITED STATES) |
| Project ID | NIH-11295406 on NIH RePORTER |
What this research studies
This project uses structural MRI scans and machine learning to predict each person’s brain age while showing which brain regions drive those predictions. The team will design interpretable algorithms, train them on large MRI datasets, and test that they work reliably on new data. They will map neuroanatomic features that distinguish normal aging from the patterns seen in mild cognitive impairment and Alzheimer’s disease. The goal is accurate, trustworthy, and generalizable MRI markers that clinicians could use for earlier detection of abnormal brain aging.
Who could benefit from this research
Good fit: Ideal candidates are adults concerned about memory decline, people with mild cognitive impairment, or those with increased risk factors for Alzheimer’s disease.
Not a fit: People without MRI scans or whose symptoms stem from non-neurodegenerative causes may not directly benefit from these methods.
Why it matters
Potential benefit: If successful, this could provide a clearer, noninvasive MRI marker to spot early abnormal brain aging and identify people at higher risk for Alzheimer’s disease.
How similar studies have performed: Previous MRI brain-age models have shown promise for signaling neurodegeneration but were often opaque, so this project builds on promising approaches while adding interpretability.
Where this research is happening
Los Angeles, UNITED STATES
- University of Southern California — Los Angeles, United States (Active)
Researchers
- Principal investigator: Irimia, Andrei — University of Southern California
- Study coordinator: Irimia, Andrei
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.