大鼠脑动脉系统氧和葡萄糖浓度分布的估计

V. Kopylova, S. Boronovskiy, Y. Nartsissov
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引用次数: 1

摘要

葡萄糖和氧气浓度梯度是构成哺乳动物脑营养组织供应的关键指标。为了详细描述它们,必须结合血流动力学和组织中的对流-扩散-反应问题的解决方案。上述代谢物时空分布的可视化既可以使用梯度本身,也可以使用相应的概率密度函数。在考虑大脑的大部分以及整个器官作为一个整体的情况下,代谢物异质性描述的第二种方法在实际目的上更有意义。本文提出了一种基于Delaunay三角剖分法和球面源扩散场法对扩散区域进行结构分割的概率密度函数获取方法。结果表明,估计分布的平均值与实验结果相差8%,在基本拓扑的三角剖分简式中,它与有限元法验证时的最佳匹配相对应。考虑到分割过程和单个片段中浓度估计的计算复杂度相对较低,所提出的方法可以获得各种化合物的积分分布,特别是葡萄糖和氧,可以作为精确计算全脑及其不同解剖结构中的浓度梯度的一种经济实惠的替代方法。
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Estimation of Oxygen and Glucose Concentration Distribution in the Rat Brain Arterial System
Glucose and oxygen concentration gradients are the key indicators that form the trophic tissue supply in mammalian brain. To describe them in detail it is essential to combine the solution of both hemodynamics and the convection-diffusion-reaction problems in the tissue. Visualization of spatio-temporal distributions of the metabolites noted above can be carried out both using the gradients themselves and the corresponding probability density functions. In the case of considering large parts of the brain, as well as the entire organ as a whole, the second method for metabolite heterogeneity description is of greater interest for practical purposes. This paper presents an approach to obtain a probability density functions based on structural segmentation of the diffusion region using Delaunay triangulation and the spherical source diffusion field method. It is shown that the average values of the estimated distributions deviate by 8 % from the experimentally obtained results and it corresponds to the best match during the validation by the finite element method in the triangulation simplices of basic topology. Given the relatively low computational complexity of both the segmentation process and the estimation of concentration in a single segment, the proposed method to obtain integral distributions of various compounds, in particular glucose and oxygen, can be used as an affordable alternative to precise calculation of the concentration gradients in the whole brain and its distinct anatomical structures.
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来源期刊
Mathematical Biology and Bioinformatics
Mathematical Biology and Bioinformatics Mathematics-Applied Mathematics
CiteScore
1.10
自引率
0.00%
发文量
13
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