Computational Simulation of Tumor Hypoxia Based on In Vivo Microvasculature Assessed in a Dorsal Skin Window Chamber

Abstract

Malignant growth usually leads to the depletion of oxygen (O₂) supply in most solid tumors. Hypoxia can cause resistance to standard radiotherapy, some chemotherapy and immunotherapy. Furthermore, it can also trigger malignant progression by modulating gene expression and inducing genetic instability. The relationship between microvasculature, perfusion and tumor hypoxia has been intensively studied and many computational simulations have been developed to model tissue O₂ transport. Usually simplified 2D phantoms are used to investigate tumor hypoxia and it is assumed that vessels are perpendicular to the region of interest and randomly distributed across the domain. Such idealistic topology overlooks vascular heterogeneity and is not accurate enough to approximate real scenarios. In addition, experimental verification of the spatial gradient of computational simulations is not directly feasible. Realistic vasculature obtained from fluorescence imaging imported as geometry for partial differential equations solving did not receive necessary attention so far. Therefore, we established a computational simulation of in vivo conditions using experimental data obtained from dorsal skin window chamber tumor preparations in nude rats for the verification of computational results. Tumor microvasculature was assessed by fluorescence microscopy. Since the conventional finite difference method can hardly satisfy the real measurements, we established a finite element method (FEM) for the experimental data in this study. Realistic 2D tumor microvasculature was reconstructed by segmenting fluorescence images and then translated into FEM topology. O₂ distributions and the O₂ gradients were obtained by solving reaction-diffusion equations. The simulation results show that the development of tumor hypoxia is greatly influenced by the irregular architecture and function of microvascular networks.

Keywords: Oxygen gradients, tumor; Tumor hypoxia; Tumor microvasculature; Tumor oxygenation, computer simulation; Tumor oxygenation, heterogeneity.