El-Bouri, Wahbi K 
ORCID: 0000-0002-2732-5927 and Payne, Stephen J
(2018)
Investigating the effects of a penetrating vessel occlusion with a multi-scale microvasculature model of the human cerebral cortex.
NEUROIMAGE, 172.
pp. 94-106.
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Investigating+Human+Cerebral+Occlusions.pdf - Author Accepted Manuscript Download (5MB) | Preview |
Abstract
The effect of the microvasculature on observed clinical parameters, such as cerebral blood flow, is poorly understood. This is partly due to the gap between the vessels that can be individually imaged in humans and the microvasculature, meaning that mathematical models are required to understand the role of the microvasculature. As a result, a multi-scale model based on morphological data was developed here that is able to model large regions of the human microvasculature. From this model, a clear layering of flow (and 1-dimensional depth profiles) was observed within a voxel, with the flow in the microvasculature being driven predominantly by the geometry of the penetrating vessels. It also appears that the pressure and flow are decoupled, both in healthy vasculatures and in those where occlusions have occurred, again due to the topology of the penetrating vessels shunting flow between them. Occlusion of a penetrating arteriole resulted in a very high degree of overlap of blood pressure drop with experimentally observed cell death. However, drops in blood flow were far more widespread, providing additional support for the theory that pericyte controlled regulation on the capillary scale likely plays a large part in the perfusion of tissue post-occlusion.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Cerebral microcirculation, Micro-infarct, Haemodynamics, Cerebral blood flow, Penetrating arterioles |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 23 Aug 2021 15:46 |
| Last Modified: | 18 Jan 2023 21:32 |
| DOI: | 10.1016/j.neuroimage.2018.01.049 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3134480 |
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