QTIME - Quantitative metabolic 7T imaging of tumours
QTIME - Quantitative metabolic 7T imaging of tumours
Disciplines
Chemistry (25%); Clinical Medicine (75%)
Keywords
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7T,
MRSI,
Mass Spectrometry,
Neurosurgery,
Gliomas,
Oncometabolism
Local mutations of brain tumour cells have become important over the last decade to the classification of different tumour types. They and resulting changes in tumour biochemistry and especially metabolism are also known to vary in time and space within a tumour. These changes are also suspected to be important for the spread of tumours in the brain that eventually leads to death. Our team has developed a new method for high-resolution imaging of metabolites in the brain with 7T magnetic resonance spectroscopic imaging (MRSI). It manages to show spatial and biochemical variation in tumour metabolism but is limited for now as it cannot directly detect the amount of tumour metabolites and has not been verified by methods that can precisely determine these amounts. This project will address this limitation. We want to introduce the mapping of water concentrations in brain tumours into our measurements which will allow us to calculate the concentrations of tumour metabolites as well. From these concentration maps, we will define volumes of interest were neurosurgeons will take samples during surgery to remove as much of the tumour volume as is safe. These samples will be flash-frozen for chemical analysis with mass spectrometry. These measurements will allow us to confirm and adjust our 7T MRSI concentration scans. Altogether, our results will allow us to create a database of tumour metabolism that we can use to find new research questions for future studies. Quantitative 7T MRSI of brain tumours is not possible yet. After referencing our method with mass spectroscopy, it can be far better tested for uses in non-invasive diagnostics and treatment planning. With metabolic data on an individuals brain tumour, precision medicine could lead to longer an better survival following long-term research.
- Universität Wien - 32%
- Medizinische Universität Wien - 68%
- Daniela Lötsch-Gojo, Medizinische Universität Wien , national collaboration partner
- Georg Widhalm, Medizinische Universität Wien , former principal investigator
- Georg Widhalm, Medizinische Universität Wien , national collaboration partner
- Gilbert Hangel, Medizinische Universität Wien , former principal investigator
- Siegfried Trattnig, Medizinische Universität Wien , national collaboration partner
- Wolfgang Bogner, Medizinische Universität Wien , national collaboration partner
- Gunda Köllensperger, Universität Wien , associated research partner
- Barbara Dymerska, University College London
- Martina Callaghan, University College London
Research Output
- 108 Citations
- 7 Publications
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2025
Title High-Resolution Mapping of Tumor and Peritumoral Glutamate and Glutamine in Gliomas Using 7-T MRSI DOI 10.1148/rycan.240494 Type Journal Article Author Hangel G Journal Radiology: Imaging Cancer Link Publication -
2024
Title 7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading DOI 10.1186/s40644-024-00704-9 Type Journal Article Author Cadrien C Journal Cancer Imaging Pages 67 Link Publication -
2024
Title Imaging of increased peritumoral glutamate and glutamine in gliomas using 7T MRSI DOI 10.1101/2024.10.25.24316010 Type Preprint Author Hangel G Pages 2024.10.25.24316010 Link Publication -
2024
Title A Comparison of 7 Tesla MR Spectroscopic Imaging and 3 Tesla MR Fingerprinting for Tumor Localization in Glioma Patients DOI 10.3390/cancers16050943 Type Journal Article Author Lazen P Journal Cancers Pages 943 Link Publication -
2023
Title Advanced MR Techniques for Preoperative Glioma Characterization: Part 2 DOI 10.1002/jmri.28663 Type Journal Article Author Hangel G Journal Journal of Magnetic Resonance Imaging Pages 1676-1695 Link Publication -
2023
Title Advanced MR Techniques for Preoperative Glioma Characterization: Part 1 DOI 10.1002/jmri.28662 Type Journal Article Author Hirschler L Journal Journal of Magnetic Resonance Imaging Pages 1655-1675 Link Publication -
2023
Title A comparison of 7 Tesla MR spectroscopic imaging and 3 Tesla MR fingerprinting for tumor localization in glioma patients DOI 10.48550/arxiv.2304.05254 Type Preprint Author Lazen P