ESTRO 2025 - Abstract Book

S768

Clinical - CNS

ESTRO 2025

27 patients were recruited. Mean age was 45.4 years, 10 patients had glioblastoma multiforme, 11 patients had oligodendroglioma (4 with grade3 and 7 with grade2), and 6 patients had astrocytoma (3 with grade3 and 3 with grade2). There was a significant difference in vascular density between tumour subtypes and tumour grade (F( 1,21 )=8.530,p=0.008) (Figure1). There was a significant difference in vascular diameter according to the tumour type in oedema only (F( 2,21 )=4.380,p=0.026) (Figure2). A main effect of tumour grade on vessel diameter in healthy grey matter residual tissue was observed (F( 1,21 )=6.682, p=0.017) together with a significant difference between tumour subtype and tumour grade in vessel diameter in oedema (F( 1,21)= 4.346,p=0.04)), suggesting that tumour subtype and WHO grade can have an effect on vessel diameter (Figure2). Conclusion: Our findings align with the understanding that high-grade gliomas develop their own blood supply, resulting in higher vascular density. Oligodendrogliomas displayed larger vessel diameters, reflecting their vascular characteristics. Both oligodendrogliomas and glioblastomas can exhibit higher vascular density; though our analysis captured this in oligodendrogliomas only, likely due to glioblastoma's microvascular proliferation, which is hard to detect at QSM resolutions. Integrating QSM mapping in clinical assessments could support glioma diagnosis and characterization. References: Hardee,M.E. et al.,Mechanisms of glioma-associated neovascularization. Am J Pathol 181,1126–1141(2012). Farnsworth,R.H. et al.,Vascular remodelling in cancer. Oncogene 33, 3496–3505 (2014). Zong,H., et al., The cellular origin for malignant glioma and prospects for clinical advancements. Expert Rev Mol Diagn 12,383–394(2012). Carmeliet,P., et al., Molecular mechanisms and clinical applications of angiogenesis. Nature 473,298–307(2011). Ruetten,P.P.R., et al., Review: Introduction to quantitative susceptibility mapping and susceptibility weighted imaging. British Journal of Radiology 92,(2019). Sørensen,P.J. et al., Evaluation of the HD-GLIO deep learning algorithm for brain tumour segmentation on postoperative MRI. Diagnostics 13,363(2023). Keywords: glioma, quantitative susceptibility mapping