Improving the analysis of brain images for Alzheimer's disease
Official title: Bayesian Object-Oriented Modeling of Multi-Modal Imaging Data
Funded at University of California, San Francisco · NIH-10991810 · Data updated 2026-11-12
This study is working on new ways to look at brain scans from people with Alzheimer's and similar conditions to better understand how these diseases affect the brain, which could help improve care and treatment for patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | December 1, 2023 |
| Project end | November 30, 2028 |
| Funding year | 2025 |
| Award (this year) | $349,924 |
| NIH project number | 5R01NS131604-02 |
| Project ID | NIH-10991810 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals diagnosed with Alzheimer's disease or other neurodegenerative disorders who are undergoing imaging assessments.
✕Less likely to help
Patients with non-neurodegenerative cognitive impairments or those not undergoing brain imaging may not benefit from this research.
What this research studies
This research focuses on developing advanced statistical methods to analyze brain images from patients with Alzheimer's disease and other neurodegenerative disorders. By integrating different types of imaging data, the project aims to enhance the understanding of how these diseases disrupt brain structure and connectivity. The approach utilizes hierarchical Bayesian models to improve the accuracy and efficiency of clinical interpretations, which could lead to better monitoring and treatment strategies for patients. The research addresses significant challenges in current methodologies, aiming to provide a more comprehensive view of brain health in the context of aging and cognitive decline.
Why it matters
Potential benefit: If successful, this research could lead to improved diagnostic tools and treatment strategies for patients with Alzheimer's disease.
How similar studies have gone: Previous research has shown promise in using Bayesian methods for analyzing complex medical data, indicating potential for success in this novel approach.
Where this research is happening
-
University of California, San Francisco
San Francisco, United States Active
Researchers
- Principal investigator: Scheffler, Aaron Wolfe — University of California, San Francisco
- Study coordinator: Scheffler, Aaron Wolfe
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.