Biophysical Modelling of Tumour Vasculature and Microenvironment in Brain Tumours
Poster No:
1508
Submission Type:
Abstract Submission
Authors:
Christian Behler1, Michael Breakspear1, Saadallah Ramadan2, Michael Fay1
Institutions:
1The University of Newcastle, Newcastle, Australia, 2Hunter Medical Research Institute, Newcastle, Australia
First Author:
Co-Author(s):
Introduction:
Brain tumours exhibit complex vascular characteristics that profoundly affect their microenvironment and treatment outcomes. While standard imaging sequences (T1, T1ce, T2, FLAIR) can visualise gross tumour features, they fail to resolve the intricate arterial and venous vasculature at the microscale. Even advanced techniques like Time-of-Flight MRI are resolution-limited, preventing complete vascular mapping. Furthermore, existing bioheat models (Blowers, 2018) for healthy brain tissue neglect the vascular and metabolic abnormalities of tumours, such as chaotic angiogenesis and localised hypoxia. These abnormalities disrupt blood flow, oxygen delivery, and temperature gradients, influencing tumour physiology and therapy. This study bridges the resolution gap with a biophysical framework for tumour-specific vasculature and microenvironment modelling, laying the groundwork for integrating these features into tumour-adapted bioheat models.
Methods:
We developed a simulation framework using a Rapidly-exploring Random Tree (RRT) algorithm (Lavalle, 1998) to generate biologically-inspired vascular structures. The model incorporates a simplified tumour geometry with a necrotic core surrounded by an active shell. Vessel growth is modulated by a bias factor in the RRT algorithm, where a 50% bias forces half of the newly generated vessels to grow close to existing vessels, mimicking the clustered angiogenesis characteristic of pathological conditions. In addition, vessels with many neighbours were assigned impaired permeability and oxygenation, reflecting the dysfunctional neovasculature typically found in tumours. These parameters, alongside the bias factor, were critical in determining the resulting oxygen distribution. The results will be integrated into existing bioheat frameworks, which have primarily focused on healthy brains, to model the unique temperature dynamics of brain tumours.
Results:
In the physiological pattern (0% bias), vessel growth was evenly distributed throughout the tumour shell, resulting in consistent oxygen gradients. In the pathological condition (50% bias), vessel growth clustered near existing vessels, creating uneven vascular networks and localised hypoxic regions. The reduced permeability and oxygenation of clustered vessels further exacerbated oxygen heterogeneity, mimicking tumour microenvironment conditions. These patterns reveal how angiogenesis and vessel functionality drive both oxygenation and thermal properties in the tumour microenvironment.
Conclusions:
This work establishes a flexible framework for modelling the complex interplay between tumour vasculature and microenvironmental parameters. By demonstrating how different angiogenesis patterns and vessel dysfunction shape vascular and oxygen distribution, we provide a foundation for integrating these results into tumour-specific bioheat models. This integration aims to refine the understanding of brain tumour temperature dynamics and inform the development of personalised hyperthermia treatments.
Modeling and Analysis Methods:
Methods Development 1
Physiology, Metabolism and Neurotransmission:
Cerebral Metabolism and Hemodynamics 2
Keywords:
ANGIOGRAPHY
Cerebral Blood Flow
Data analysis
Modeling
MRI
MRI PHYSICS
Neoplastic Disease
1|2Indicates the priority used for review
Abstract Information
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
Lavalle,S. (1998). Rapidly-exploring random trees: A new tool for path planning. Computer Science Dept. Oct., 98(11).