论文标题
血管复杂性在最佳连接指数上的作用
The role of vascular complexity on optimal junction exponents
论文作者
论文摘要
我们检查了复杂性在动脉树结构上的作用，并使用模拟退火血管优化（SALVO）算法确定全球最佳血管排列，我们以前用来再现心脏和脑血管的特征。对复杂血管结构的基本生物物理理解具有对心血管疾病建模的应用，并改善了大型人造组织中血管的表示。为了进步用于生长动脉网络的硅胶方法，我们需要了解计算动脉生长算法对复杂性的稳定性，生理参数（例如组织需求）的变化以及有关连接指数价值的基本假设。我们确定二维动脉树的全球最佳结构；分析树形态的敏感性和对生理参数的最佳分叉指数。我们发现，对于生理相关的模拟参数，动脉结构是稳定的，而最佳连接指数则变化。我们得出的结论是，动脉树的全部复杂性对于确定血管的基本特性至关重要。这些结果对于确定基于优化的动脉生长算法对生理参数的不确定性稳定很重要，同时确定最佳分叉指数（许多动脉生长算法的关键参数）对复杂性敏感，并由器官决定的边界条件敏感。
We examine the role of complexity on arterial tree structures, determining globally optimal vessel arrangements using the Simulated AnneaLing Vascular Optimization (SALVO) algorithm, which we have previously used to reproduce features of cardiac and cerebral vasculatures. Fundamental biophysical understanding of complex vascular structure has applications to modelling of cardiovascular diseases, and for improved representations of vasculatures in large artificial tissues. In order to progress in-silico methods for growing arterial networks, we need to understand the stability of computational arterial growth algorithms to complexity, variations in physiological parameters such as tissue demand, and underlying assumptions regarding the value of junction exponents. We determine the globally optimal structure of two-dimensional arterial trees; analysing sensitivity of tree morphology and optimal bifurcation exponent to physiological parameters. We find that, for physiologically relevant simulation parameters, arterial structure is stable, whereas optimal junction exponents vary. We conclude that the full complexity of arterial trees is essential for determining the fundamental properties of vasculatures. These results are important for establishing that optimisation-based arterial growth algorithms are stable against uncertainties in physiological parameters, while identifying that optimal bifurcation exponents (a key parameter for many arterial growth algorithms) are sensitive to complexity and the boundary conditions dictated by organs.
