A generalized mathematical framework for estimating the residue function for arbitrary vascular networks
A generalized mathematical framework for estimating the residue function for arbitrary vascular networks
复制标题
用于估计任意血管网络的残差函数的广义数学框架
作者：
C. Park;S. Payne
微血管在心血管系统中起着重要作用。其功能的任何损害都可能导致显著的病理生理效应，特别是在结构和功能之间存在非常紧密耦合的器官（如大脑）中。然而，除了通过评估灌注，使用诸如动脉自旋标记的技术来量化体内微脉管系统的健康是极其困难的。最近的工作表明，体素内的流量分布也可能是一个有价值的措施。这也可以在临床上测量，但由于难以建模和表征这些强相互连接的网络，因此尚未与微血管系统的特性相关。在本文中，我们提出了一种新的技术来表征现有的生理准确模型的大脑微血管在其残留功能。一个新的分析数学框架计算的残留功能，质量传输方程的基础上，任何任意网络的模拟结果一起。然后，我们提出了一种方法来表征这个功能，它可以直接相关的临床数据，并显示所得到的参数是如何影响的条件下，减少灌注和减少网络密度。据发现，这两种效果的残余函数参数以不同的方式受到影响，打开了使用这样的参数的可能性，当从临床数据中获取时，推断关于网络属性和灌注分布的信息。这些结果开辟了获得有关体内微血管健康的有价值的临床信息的可能性，为脑血管疾病（如中风和痴呆）的临床医生提供了额外的工具。
The microvasculature plays a vital part in the cardiovascular system. Any impairment to its function can lead to significant pathophysiological effects, particularly in organs such as the brain where there is a very tight coupling between structure and function. However, it is extremely difficult to quantify the health of the microvasculature in vivo, other than by assessing perfusion, using techniques such as arterial spin labelling. Recent work has suggested that the flow distribution within a voxel could also be a valuable measure. This can also be measured clinically, but as yet has not been related to the properties of the microvasculature due to the difficulties in modelling and characterizing these strongly inter-connected networks. In this paper, we present a new technique for characterizing an existing physiologically accurate model of the cerebral microvasculature in terms of its residue function. A new analytical mathematical framework for calculation of the residue function, based on the mass transport equation, of any arbitrary network is presented together with results from simulations. We then present a method for characterizing this function, which can be directly related to clinical data, and show how the resulting parameters are affected under conditions of both reduced perfusion and reduced network density. It is found that the residue function parameters are affected in different ways by these two effects, opening up the possibility of using such parameters, when acquired from clinical data, to infer information about both the network properties and the perfusion distribution. These results open up the possibility of obtaining valuable clinical information about the health of the microvasculature in vivo, providing additional tools to clinicians working in cerebrovascular diseases, such as stroke and dementia.
影响因子：
2.4
作者：
Alastruey, J.;Parker, K. H.;Sherwin, S. J.
通讯作者：
Sherwin, S. J.