Author: Yi Fan, Andrew Friberg, Costas Koumenis, Kevin Teo, Ioannis I Verginadis, Ledi Wang, Jennifer Wei Zou 👨🔬
Affiliation: Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania 🌍
Purpose: Glioblastomas (GBM) are aggressive and lethal malignancies characterized by their highly refractory nature, contributing to a five-year survival rate of approximately 7%. Physically, GBM exhibits disordered vasculature that leads to low oxygen content and elevated interstitial pressure. These conditions give rise to increased radio-resistance and prevent the uptake of therapeutic agents such as CAR-T. Investigating the impact of vasculature structure on oxygen diffusion and uptake provides a critical framework for evaluating interventions, such as targeting PHGDH, which reordered the vasculature and provides better outlooks for oxygenation and targeted therapy.
Methods: Normal and GBM murine brain tissue was stained using TdTomato for vasculature and pimonidazole for hypoxia. The samples were scanned using Light Sheet Fluorescent Microscopy (LSFM), and 3D models were reconstructed. These models were subsequently imported into Finite Element Software, where inlet faces for capillaries were defined with Dirichlet oxygen boundary conditions. Fluid dynamics simulations were incorporated with a no-slip condition at the surface of the vasculature, and a combined transport-diffusion system was solved, yielding oxygen distribution and blood flow velocity within the simulated volume.
Results: A decrease in oxygen concentration from 410 mol/m3 to 270 mol/m3 is observed along the length of the capillary, corresponding to oxygen transfer from the blood into the surrounding tissue. Along poorly formed regions of the vasculature, the simulations reveal impaired blood flow, resulting in diminished oxygen delivery to those areas.
Conclusion: Our model successfully captures key aspects of oxygen distribution and blood flow within the simulated volume, highlighting impaired oxygen delivery in poorly formed GBM vasculature regions. The simulations demonstrate a maximum diffusion length of approximately 100 µm, providing insights into the interplay between vascular morphology, oxygen diffusion, and perfusion. By incorporating realistic vasculature dynamics, the model surpasses traditional Kroghian analysis, offering a more comprehensive understanding of tumor and normal tissue vasculature.