Creating tools to improve brain cancer diagnosis using advanced imaging techniques
Official title: Developing informatics tools for optimized MRS for brain cancer research
Funded at University of Minnesota · NIH-10926909 · Data updated 2026-11-12
This study is working on new tools that make it easier for doctors to use MRI scans to learn more about brain tumors, helping them understand the tumors better and see how well treatments are working, all without needing any special training.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Minnesota NIH-funded |
| Lab location | 1 site (Minneapolis, United States) |
| Project start | September 7, 2022 |
| Project end | August 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $177,201 |
| NIH project number | 5U01CA269110-03 |
| Project ID | NIH-10926909 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are adults diagnosed with brain tumors who require metabolic assessment for treatment planning.
✕Less likely to help
Patients with brain tumors who are not eligible for MRI or those with contraindications to MRS may not benefit from this research.
What this research studies
This research focuses on developing automated tools for single-voxel magnetic resonance spectroscopy (MRS) to enhance the assessment of brain tumors. By integrating these tools with clinical MRI systems, the project aims to provide real-time, noninvasive metabolic information that can help evaluate tumor characteristics and treatment responses. The methodology includes creating a 3D voxel placement technique and automating the MRS process to ensure high-quality data without requiring specialized expertise. The results will be made available as open-source tools for the broader research community.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and accessible diagnostic tools for brain cancer, improving patient outcomes.
How similar studies have gone: Previous research has shown promise in using automated imaging techniques for cancer diagnostics, indicating potential success for this novel approach.
Where this research is happening
-
University of Minnesota
Minneapolis, United States Active
Researchers
- Principal investigator: Marjanska, Malgorzata — University of Minnesota
- Study coordinator: Marjanska, Malgorzata
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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.