Delivery of oxygen to tissue is an essential function of the circulatory system. The distance that oxygen can diffuse into oxygen-consuming tissue is small, and so tissue oxygenation is critically dependent on the spatial arrangement of microvessels in tissue. Theoretical methods have been developed to simulate the spatial distribution of oxygen levels in tissue surrounding a network of microvessels. Here, numerical methods based on a Green's function approach are presented, for realistic three-dimensional network geometries derived from observations of skeletal muscle, brain, and tumor tissues. Relative to finite-difference methods, the Green's function approach reduces the number of unknowns in the numerical formulation and allows rapid computations even for complex vascular geometries. Generally, the boundary conditions on the exterior of the computational domain are not known. Imposition of a no-flux boundary condition can lead to exaggerated estimates of the extent of hypoxia in the tissue region. A new version of the method is described that avoids this problem and can be applied to arbitrarily shaped tissue domains.

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Formation of functionally adequate vascular networks by angiogenesis presents a problem in biological patterning. Generated without predetermined spatial patterns, networks must develop hierarchical tree-like structures for efficient convective transport over large distances, combined with dense space-filling meshes for short diffusion distances to every point in the tissue. Moreover, networks must be capable of restructuring in response to changing functional demands without interruption of blood flow. Here, theoretical simulations based on experimental data are used to demonstrate that this patterning problem can be solved through over-abundant stochastic generation of vessels in response to a growth factor generated in hypoxic tissue regions, in parallel with refinement by structural adaptation and pruning. Essential biological mechanisms for generation of adequate and efficient vascular patterns are identified and impairments in vascular properties resulting from defects in these mechanisms are predicted. The results provide a framework for understanding vascular network formation in normal or pathological conditions and for predicting effects of therapies targeting angiogenesis.

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Extravascular transport in tumors, and its consequences for tumor cell killing, can be predicted by measuring drug penetration through MCLs in vitro and modeling pharmacokinetics at each position in three-dimensional microvascular networks.