FRACTAL GEOMETRIC ANALYSIS OF BRAIN MICROCIRCULATION

在所有器官中都发现了区域流动的可变性。然而， 这种变化不是随机的，因为有相当大的相关性 在相邻地区的流动之间。分形图提供了一种度量 变异和关联，同时。关键是 自相似：表观变异的对数增加 与流动的组织样本的大小的对数成反比 是经过测量的。以前已经有过两种不同的分形描述 发现足以描述内部区域流动的异质性 心脏和肺超过200倍的体素大小；其中一个是基于 一种是统计自相似，另一种是自相似分支 算法。该项目的目标是开展联合研究。 为了获得所需的关于器官内血流分布的数据 大脑皮层，与塞梅尔韦斯的Eke博士合作 布达佩斯医科大学。通过他的计算机视频成像 方法、实质内血流分布及其 成分、红细胞和血浆微血流可重复成像 在猫和大鼠的大脑皮质中导致微循环 具有足够空间分辨率的参数图像(216微流数据 每幅图像)，用于执行分形图分析。它将基于 关于统计自相似在空间确定中的应用 观测到的微流非均质性(DS)的分维 体素大小的折叠范围。我们期待着获得更好的 对红细胞和血浆分维的理解 脑实质内分布模式在以下情况下相互关联 生理和病理条件。因为艾克博士的方法 允许直接观察和覆盖软脑膜血管 网络上的微流图像，网格法可以用来 测定观察到的软脑膜维管树供、引流的D值 绘制的组织区域。访问这两个空间分形图 维度为开发计算机模型提供了独特的可能性 观察到的软脑膜和实质内循环。通过互动 在模型和实验之间，模型将被改进到适当的程度。 当它模拟任何水平或截面的微流分布时 并提供模拟的微流图像，从 单独的毛细数据。我们将使用该模型来扩展我们的 对内部结构的拓扑结构的理解 脑实质内微血流相对于软脑膜动脉的分布 软膜表面的输入、静脉输出量和深度。

Variability in regional flows is found in all organs. However this variation is NOT random, for there is considerable correlation between flows in neighboring regions. Fractals provide a measure of the variation AND the correlation, simultaneously. The key is self-similarity: the log of the apparent variation increases inversely with the log of the size of the tissue samples in which flow is measured. Two different fractal descriptions have been previously found adequate to describe the heterogeneity of regional flows within the heart and lung over a 200-fold range of voxel sizes; one was based on statistical self similarity, the other on a self-similar branching algorithm. The goals of this project are to carry out joint studies to yield needed data about the intraorgan flow distribution in the brain cortex in cooperation with Dr. Eke from the Semmelweis University of Medicine in Budapest. By his computerized videoimaging methodology, intraparenchymaldistribution of blood flow and its components, red cell and plasma microflow can be repetitively imaged in the feline and rat brain cortex resulting in microcirculatory parameter images of adequate spatial resolution (216 microflow data per image) for fractal analysis to be carried out. It will be based on statistical self similarity to be applied to determine the spatial fractal dimension of the observed microflow heterogeneity (Ds) within a 64-fold range of voxel sizes. We expect to gain a better understanding of how the fractal dimensions of red cell's and plasma's intraparenchymal distribution patterns relate to each other under physiological and pathological conditions. Because Dr. Eke's method allows for direct observation and overlaying of the pial vascular network on the microflow images, the grid method can be used to determine Ds of the observed pial vascular tree supplying and draining the mapped tissue area. Access to these two spatial fractal dimensions offers the unique possibility to develop a computer model of the observed pial and intraparenchymal circulation. By interaction between model and experiment, the model will be refined to the point when it will simulate microflow distributions at any level or section of the network and to provide simulated microflow images compiled from individual capillary data. We will use the model to extend our understanding of the topology of the internal structure of intraparenchymal microflow distributions relative to pial arterial inputs and venous outputs and depth from the pial surface.