Using machine learning to analyze brain scans of aging populations
Official title: Acquisition-independent machine learning for morphometric analysis of underrepresented aging populations with clinical and low-field brain MRI
Funded at Massachusetts General Hospital · NIH-10739049 · Data updated 2026-11-12
This study is working on new ways to use computer technology to look at brain MRI scans, especially from older Black individuals, to help us better understand aging and Alzheimer's disease, which could lead to improved tools for diagnosis and treatment.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts General Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | September 1, 2023 |
| Project end | August 31, 2026 |
| Funding year | 2023 |
| Award (this year) | $2,434,955 |
| NIH project number | 1RF1AG080371-01A1 |
| Project ID | NIH-10739049 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include aging individuals, particularly those from underrepresented populations, who have undergone brain MRI scans.
✕Less likely to help
Patients who do not have access to MRI scans or are not part of the aging demographic may not benefit from this research.
What this research studies
This research focuses on developing advanced machine learning techniques to analyze brain MRI scans, particularly from aging populations that are often underrepresented in studies, such as Black individuals. The project aims to overcome limitations in current MRI analysis methods that require high-quality imaging, which is often not available in clinical settings or low-field scanners. By utilizing innovative algorithms, the research seeks to extract meaningful morphometric data from these scans, potentially improving our understanding of aging and Alzheimer's disease. This could lead to better diagnostic tools and treatment strategies for affected individuals.
Why it matters
Potential benefit: If successful, this research could enhance the accuracy of brain imaging analyses, leading to improved diagnosis and treatment of Alzheimer's disease and related conditions.
How similar studies have gone: Previous research has shown promise in using machine learning for MRI analysis, but this approach specifically targeting underrepresented populations is relatively novel.
Where this research is happening
-
Massachusetts General Hospital
Boston, United States Active
Researchers
- Principal investigator: Iglesias Gonzalez, Juan Eugenio — Massachusetts General Hospital
- Study coordinator: Iglesias Gonzalez, Juan Eugenio
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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.