QSM Maps Highlight Distinct Vascular Characteristics Across Glioma Subtypes
Motivation: Investigating tumour-specific metabolic and vasculature differences could help with tumour characterization, treatment planning and monitoring response to therapy. Goal(s): We aim to implement a reliable and sensitive MRI method for detecting the physiological changes across different types of glioma based on quantitative susceptibility map (QSM) acquisition. Approach: We acquired QSM maps from which Oxygen Extraction Fraction, Vessels Diameter and Vascular Density were extracted and differences among glioma subtypes were investigated. Results: We observed distinct metabolic and vascular characteristics across glioma subtypes, highlighting the potential of QSM maps to identify subtype-specific vascular features. Impact: Brain tumour subtype and aggressiveness influence vascular parameters in surrounding tissue, with higher demand observed in more aggressive tumours. This relationship can be captured with quantitative susceptibility maps (QSM) and it can offer valuable insights for tumour diagnosis and characterization.
Authors
- James Powell (ORCID: https://orcid.org/0000-0002-3517-7485)
- Eleonora Patitucci (ORCID: https://orcid.org/0000-0002-1843-7046)
- Najmus Sahar Iqbal
- Michael Germuska (ORCID: https://orcid.org/0000-0003-0580-4350)
- Stefano Zappalá (ORCID: https://orcid.org/0000-0002-7057-8575)
- Richard Wise (ORCID: https://orcid.org/0000-0003-0903-8729)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/2375
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00