Imaging and molecular tools to detect returning brain tumors
Quantitative imaging and molecular data modeling for brain tumor recurrence and progression analysis
This project uses brain scans and tumor molecular data with AI to help doctors spot when glioblastoma tumors come back in adults.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Old Dominion University NIH-funded |
| Lab location | 1 site (Norfolk, United States) |
| Project ID | NIH-11050657 on NIH RePORTER |
What this research studies
You would be part of a project that combines brain imaging scans and tumor molecular test results from multiple hospitals to teach AI how tumors change over time. The team will train and test algorithms to segment and track tumor, edema, and radiation-related changes on scans and link those imaging patterns to molecular markers. They will use explainable AI with uncertainty measures and validate the models using both in-house patient data and public datasets through the ReSPOND consortium.
Who could benefit from this research
Good fit: Adults (21+) with glioblastoma or suspected tumor recurrence who have clinical imaging and/or tumor molecular data are the ideal candidates.
Not a fit: People without glioblastoma, children, or patients who lack usable imaging or molecular test results may not benefit from this work.
Why it matters
Potential benefit: If successful, this could help detect tumor recurrence earlier and reduce the need for invasive biopsy.
How similar studies have performed: Previous AI approaches to brain tumor imaging have shown promising but limited results, and combining imaging with molecular data and explainable AI here is a relatively novel step.
Where this research is happening
Norfolk, United States
- Old Dominion University — Norfolk, United States (Active)
Researchers
- Principal investigator: Iftekharuddin, Khan M — Old Dominion University
- Study coordinator: Iftekharuddin, Khan M
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.