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Angiogenesis plays an essential role in many pathological processes such as tumor growth, wound healing, and keloid development. Low oxygen level is the main driving stimulus for angiogenesis. In an animal tissue, the oxygen level is mainly determined by three effects—the oxygen delivery through blood flow in a refined vessel network, the oxygen diffusion from blood to tissue, and the oxygen consumption in cells. Evaluation of the oxygen field is usually the bottleneck in large scale modeling and simulation of angiogenesis and related physiological processes. In this work, a fast numerical method is developed for the simulation of oxygen supply in tissue with a large-scale complex vessel network. This method employs an implicit finite-difference scheme to compute the oxygen field. By virtue of an oxygen source distribution technique from vessel center lines to mesh points and a corresponding post-processing technique that eliminate the local numerical error induced by source distribution, square mesh with relatively large mesh sizes can be applied while sufficient numerical accuracy is maintained. The new method has computational complexity which is slightly higher than linear with respect to the number of mesh points and has a convergence order which is slightly lower than second order with respect to the mesh size. With this new method, accurate evaluation of the oxygen field in a fully vascularized tissue on the scale of centimeter becomes possible.

AbstractOxygen field evaluation is important in modeling and simulation of many important physiological processes of animals, such as angiogenesis. However, numerical simulation of the oxygen field in animal tissue is usually limited by the unusual coupling of different mechanisms, the nonlinearity of the model, and the complex geometry of refined blood vessel networks. In this work, a fast numerical method is designed for the simulation of oxygen supply in tissue with a large-scale complex vessel network. This method employs an implicit finite-difference scheme to compute the oxygen field. By virtue of an oxygen source distribution technique from vessel center lines to mesh points and a corresponding post-processing technique that eliminate the local numerical error induced by source distribution, square mesh with relatively large mesh sizes can be applied while sufficient numerical accuracy is maintained. The new method has computational complexity which is slightly higher than linear with respect to the number of mesh points and has a convergence order which is slightly lower than second order with respect to the mesh size. As an example, the oxygen field of a tissue irrigated by a blood vessel network with more than four thousand blood vessels can be accurately computed within one minute with our new method. The new method will definitely promote further researches based on evaluation of oxygen field, such as modeling of angiogenesis and pathogenesis of many cardiovascular diseases.

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Transport networks such as blood vessel systems and leaf venation are universally required for large-size living organisms in order to overcome the low efficiency of the diffusion in large scale mass transportation. Despite substantial differences in living organisms, such networks have many common patterns -viz. biological transport networks are made up of tubes and flows in tubes deliver target substances. Besides, these networks maintain a tree-like backbone attached with small loops. Experimental and mathematical studies show many similarities in biological mechanisms, which drive structural optimisation in biological transport networks. It is worth noting that the structural optimisation of transport networks in living organisms is achieved in the sense of energy cost as a consequence of natural selection. In this review, we recall the exploration history and show mathematical structures used in the design of biological transport networks.