The response of the cerebral microvasculature to regional changes in cerebral blood flow
Journal
Journal of Cerebral Blood Flow and Metabolism
Journal Volume
27
Journal Issue
SUPPL. 1
Pages
BO01-6
Date Issued
2007
Author(s)
Abstract
Background: The cerebral microvasculature is a highly interconnected network of vessels, which delivers oxygen and other nutrients to brain tissue. Brain tissue is permeated with these vessels, from which no region of brain tissue is very far. The high level of connectivity provides a degree of 'redundancy', whereby no individual micro-vessel is crucial for oxygen supply to any region of brain tissue. Even at a higher level in the vascular tree, the effects of reductions or stoppages in blood flow can be ameliorated by this vessel connectivity, although, without detailed knowledge of the structural and connectivity properties of the microvasculature, the regional response to changes in blood flow cannot be estimated accurately. However, recent experimental work has led to the characterisation of the cerebral microvasculature in terms of vessel lengths, diameters and connectivity (Cassot et al., Microcirculation, 13: 1-18, 2006). This enables the response of the microvascular flow, and consequent tissue oxygen concentration, to be analysed under changing input conditions. Methods: Two and three-dimensional mathematical models of a section of the microvasculature have been constructed, using both regular patterns for vessel distribution and an approach based on random node allocation. The former model has vessels all of the same length, initially with each node connected to its 4 (in 2-D) and 6 (in 3-D) nearest neighbours: the three-connectedness of the microvasculature is obtained by removal of connections based on the flow patterns. These flow patterns are obtained by allocating sources and sinks to individual nodes, to simulate the supplying arterial and draining venous vessels. The latter model generates random nodes and connects the vessels in a way that obtains the correct length distribution and average connectivity. The blood flow through the network is then calculated by solving the pressure-resistance equations in matrix form and the oxygen concentration in the blood vessels is calculated from the mass transport equation. The tissue oxygen concentration is solved using the convection-diffusion equation for a given metabolic consumption. Results and conclusions: The response of the network to decreases in blood flow has been examined to investigate how the connectivity of the network provides redundancy. It is found that the greater the connectivity, the more robust the network is to local decreases in supplying blood flow. This is also heavily dependent upon the initial flow patterns, as the blood flow in the network can alter significantly upon a local decrease if the initial flow patterns are particularly directional. However, even under extreme conditions, the network is able to provide a high level of 'protection' by adjusting the flow patterns and this may play a key role in the response to decreases in cerebral blood flow. It is hoped that this will help in our understanding of the response of the cerebral vasculature in diseased states such as stroke and dementia as well as interpreting the low frequency oscillations that play an important role in resting state networks.
Subjects
blood pressure
blood vessel diameter
brain artery
brain blood flow
brain microcirculation
brain oxygen consumption
brain vein
conference paper
mathematical model
microvasculature
priority journal
Type
conference paper