Automated PET tools to map how tracers spread in tumors
Official title: Automatic SUV Extraction and Biodistribution Analysis of Preclinical PET
Funded at In Vivo Analytics, INC. · NIH-11195063 · Data updated 2026-11-12
This project builds a cloud tool that automatically finds organs and measures PET tracer uptake in animal cancer scans to speed imaging and drug research.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | In Vivo Analytics, INC. NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | March 11, 2019 |
| Project end | August 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $1,059,972 |
| NIH project number | 5R44CA224841-03 |
| Project ID | NIH-11195063 on NIH RePORTER |
Who could benefit from this research
✓Could help
This grant does not enroll people; it is focused on preclinical animal imaging studies used by researchers and labs developing cancer tracers and therapies.
✕Less likely to help
Patients would not directly benefit from this project since it does not include human testing or patient enrollment.
What this research studies
Researchers are creating InVivoAX, a cloud-based system that automatically extracts organ regions from preclinical PET images and computes standardized uptake values and kinetic measures. They will pair the software with a Body Conforming Animal Mold (BCAM) to keep animals in consistent positions for better image alignment. The tool aims to remove operator bias, speed up co-registration between scans, and produce near-real-time biodistribution results. Overall, the approach combines automated image registration, ROI extraction, and rapid analytics to improve reproducibility and throughput in animal cancer imaging.
Why it matters
Potential benefit: If successful, this could make preclinical imaging faster and more reliable, helping new cancer imaging agents and treatments move toward patients more quickly.
How similar studies have gone: Automated PET analysis and image-registration methods exist, but combining a body-conforming mold with cloud-based, near-real-time ROI extraction for preclinical biodistribution is a relatively novel and less-tested approach.
Where this research is happening
-
In Vivo Analytics, INC.
New York, United States Active
Researchers
- Principal investigator: Klose, Alexander D. — In Vivo Analytics, INC.
- Study coordinator: Klose, Alexander D.
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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.