Glenny R W, Robertson H T
Department of Medicine, University of Washington, Seattle 98195.
J Appl Physiol (1985). 1991 Mar;70(3):1024-30. doi: 10.1152/jappl.1991.70.3.1024.
The heterogeneity of pulmonary blood flow is not adequately described by gravitational forces alone. We investigated the flow distributions predicted by two fractally branching vascular models to determine how well such networks could explain the observed heterogeneity. The distribution of flow was modeled with a dichotomously branching tree in which the fraction of blood flow from the parent to the daughter branches was gamma and 1-gamma repeatedly at each generation. In one model gamma was held constant throughout the network, and in the other model gamma varied about a mean of 0.5 with a standard deviation of sigma. Both gamma and sigma were optimized in each model for the best fit to pulmonary blood flow data from experimental animals. The predicted relative dispersion of flow from the two model fractal networks produced an excellent fit to the observed data. These fractally branching models relate structure and function of the pulmonary vascular tree and provide a mechanism to describe the spatially correlated distribution of flow and the gravity-independent heterogeneity of blood flow.
仅靠重力无法充分描述肺血流的异质性。我们研究了两种分形分支血管模型预测的血流分布,以确定此类网络能在多大程度上解释观察到的异质性。血流分布用二叉分支树建模,其中从父分支到子分支的血流分数在每一代中重复为γ和1 - γ。在一个模型中,γ在整个网络中保持恒定,而在另一个模型中,γ围绕均值0.5变化,标准差为σ。在每个模型中,γ和σ都进行了优化,以最佳拟合实验动物的肺血流数据。来自两个模型分形网络的预测血流相对离散度与观察数据拟合得非常好。这些分形分支模型将肺血管树的结构和功能联系起来,并提供了一种机制来描述血流的空间相关分布以及与重力无关的血流异质性。