Tracer harmonization for amyloid and tau PET imaging using statistics and deep learning
Official title: Tracer harmonization for amyloid and tau PET imaging using statistical and deep learning techniques
Funded at Banner Health · NIH-11382152 · Data updated 2026-11-12
Aims to make PET brain scans for Alzheimer's disease more comparable across different tracers so doctors can better use the results for diagnosis and treatment decisions.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Banner Health NIH-funded |
| Lab location | 1 site (Phoenix, United States) |
| Project start | August 1, 2022 |
| Project end | July 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $708,430 |
| NIH project number | 5R01AG073424-03 |
| Project ID | NIH-11382152 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are individuals undergoing amyloid and/or tau PET imaging as part of Alzheimer's disease evaluation or research programs.
✕Less likely to help
Patients not undergoing PET imaging or not involved in imaging-based studies may not directly benefit.
What this research studies
This project uses advanced statistics and deep learning to harmonize PET imaging data for amyloid and tau pathologies, helping clinicians interpret scans consistently across different imaging tracers. By creating generalizable methods for image quantification, it seeks to improve diagnostic and prognostic information that can guide future treatments while leveraging existing imaging datasets. The work focuses on methodological development with the goal of making imaging signals more comparable across studies and sites. Patients may indirectly benefit as harmonized imaging could support earlier and more accurate identification of disease progression and treatment responses in the future.
Why it matters
Potential benefit: If successful, imaging results could become more reliable across centers, supporting earlier diagnosis and better monitoring of Alzheimer's disease.
How similar studies have gone: Prior work suggests that harmonization approaches can improve cross-site comparability in imaging studies, supporting the potential effectiveness of this approach.
Where this research is happening
-
Banner Health
Phoenix, United States Active
Researchers
- Principal investigator: Su, Yi — Banner Health
- Study coordinator: Su, Yi
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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.