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Identifying the myogenic and metabolic components of cerebral autoregulation

Abstract:
Cerebral autoregulation is the term used to describe a number of mechanisms that act together to maintain a near constant cerebral blood flow in response to changes in arterial blood pressure. These mechanisms are complex and known to be affected in a range of cerebrovascular diseases. However, it can be difficult to assign an alteration in cerebral autoregulation to one of the underlying physiological mechanisms without the use of a complex mathematical model. In this paper, we thus set out a new approach that enables these mechanisms to be related to the autoregulation behaviour and hence inferred from experimental measurements. We show that the arteriolar response is a function of just three parameters, which we term the elastic, the myogenic and the metabolic sensitivity coefficients, and that the full vascular response is dependent upon only seven parameters. The ratio of the strengths of the myogenic and the metabolic responses is found to be in the range 2.5 to 5 over a wide range of pressure, indicating that the balance between the two appears to lie within this range. We validate the model with existing experimental data both at the level of an individual vessel and across the whole vasculature, and show that the results are consistent with findings from the literature. We then conduct a sensitivity analysis of the model to demonstrate which parameters are most important in determining the strength of static autoregulation, showing that autoregulation strength is predominantly set by the arteriolar sensitivity coefficients. This new approach could be used in future studies to help to interpret the components of the autoregulation response and how they are affected under different conditions, providing a greater insight into the fundamental processes that govern autoregulation.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.medengphy.2018.04.018

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Keble College
Role:
Author


Publisher:
Elsevier
Journal:
Medical Engineering and Physics More from this journal
Volume:
58
Pages:
23-30
Publication date:
2018-07-03
Acceptance date:
2018-04-30
DOI:
ISSN:
1350-4533


Keywords:
Pubs id:
pubs:844876
UUID:
uuid:4fbb2066-59bc-43c4-a2c1-c266512472b9
Local pid:
pubs:844876
Source identifiers:
844876
Deposit date:
2018-04-30
ARK identifier:

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