Improving treatment for glioblastoma using daily MRI and machine learning
Official title: A Physiologic Adaptive Radiation Therapy Pipeline for Glioblastoma by Daily Multiparametric MRI and Machine Learning
Funded at University of Miami School of Medicine · NIH-11026412 · Data updated 2026-11-12
This study is looking at how daily MRI scans during radiation therapy can help doctors spot early signs of glioblastoma progression, so they can provide better treatment options for patients who need them.
Quick facts
| Grant type | R37 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Miami School of Medicine NIH-funded |
| Lab location | 1 site (Coral Gables, United States) |
| Project start | March 3, 2022 |
| Project end | February 28, 2027 |
| Funding year | 2025 |
| Award (this year) | $554,834 |
| NIH project number | 5R37CA262510-04 |
| Project ID | NIH-11026412 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients diagnosed with glioblastoma who are undergoing radiation therapy.
✕Less likely to help
Patients with glioblastoma who are not receiving radiation therapy or those with advanced disease may not benefit from this research.
What this research studies
This research focuses on glioblastoma, a common and aggressive brain cancer, by utilizing daily multiparametric MRI scans during radiation therapy. The goal is to identify patients who are experiencing true tumor progression early in their treatment, which is often difficult to determine with standard imaging techniques. By employing advanced machine learning algorithms, the study aims to enhance the accuracy of MRI interpretations and enable timely interventions. This innovative approach could lead to more effective second-line therapies for patients who need them most.
Why it matters
Potential benefit: If successful, this research could significantly improve survival rates for glioblastoma patients by allowing for earlier and more targeted treatment interventions.
How similar studies have gone: Other research has shown promise in using advanced imaging techniques and machine learning for cancer treatment, suggesting that this approach could be effective.
Where this research is happening
-
University of Miami School of Medicine
Coral Gables, United States Active
Researchers
- Principal investigator: Mellon, Eric Albert — University of Miami School of Medicine
- Study coordinator: Mellon, Eric Albert
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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.