Cerebral Autoregulation

Payne, Stephen J.

doi:10.1007/978-3-319-31784-7

Cited by 48 publications

(40 citation statements)

References 288 publications

(337 reference statements)

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“…Static CA, sometimes referred to as steady-state CA, are autoregulatory responses to steady-state changes in ABP or ICP, giving information about the range of CPP in which CA is active [1]. Dynamic CA refers to rapid changes, typically in ABP, where the response time in blood flow recovery is indicative of CA [15]. While the two groups are related, differences [12] and similarities [11] between them have been reported.…”

Section: Introductionmentioning

confidence: 99%

“…Derivatives of the above described static, dynamic, and pseudo-dynamic measurements have been proposed in order to reduce the need of invasive ICP sensors and improve reliability. Such methods often replace ICP or ABP with other hemodynamic measurements such as hemoglobin concentrations, tissue oxygenation or blood volume and summaries of them can be found elsewhere [15,[23][24][25], including non-invasive diffuse optical methods used in this article [26,27]. Despite many decades of research and a large variety of measurement methods, a consensus on the effectiveness and use of CA measurements to guide clinical treatment has not yet been reached.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of static and dynamic cerebral autoregulation under anesthesia influence in a controlled animal model

et al. 2021

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The brain’s ability to maintain cerebral blood flow approximately constant despite cerebral perfusion pressure changes is known as cerebral autoregulation (CA) and is governed by vasoconstriction and vasodilation. Cerebral perfusion pressure is defined as the pressure gradient between arterial blood pressure and intracranial pressure. Measuring CA is a challenging task and has created a variety of evaluation methods, which are often categorized as static and dynamic CA assessments. Because CA is quantified as the performance of a regulatory system and no physical ground truth can be measured, conflicting results are reported. The conflict further arises from a lack of healthy volunteer data with respect to cerebral perfusion pressure measurements and the variety of diseases in which CA ability is impaired, including stroke, traumatic brain injury and hydrocephalus. To overcome these differences, we present a healthy non-human primate model in which we can control the ability to autoregulate blood flow through the type of anesthesia (isoflurane vs fentanyl). We show how three different assessment methods can be used to measure CA impairment, and how static and dynamic autoregulation compare under challenges in intracranial pressure and blood pressure. We reconstructed Lassen’s curve for two groups of anesthesia, where only the fentanyl anesthetized group yielded the canonical shape. Cerebral perfusion pressure allowed for the best distinction between the fentanyl and isoflurane anesthetized groups. The autoregulatory response time to induced oscillations in intracranial pressure and blood pressure, measured as the phase lag between intracranial pressure and blood pressure, was able to determine autoregulatory impairment in agreement with static autoregulation. Static and dynamic CA both show impairment in high dose isoflurane anesthesia, while low isoflurane in combination with fentanyl anesthesia maintains CA, offering a repeatable animal model for CA studies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of static and dynamic cerebral autoregulation under anesthesia influence in a controlled animal model

et al. 2021

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“…the assumption of constant MCA cross-sectional area has to be made. This remains a poorly understood assumption, particularly in the context of changes in ABP: for a more detailed discussion of this see [1]. Our labelling of the feedback mechanisms that are driven by direct and shear stress as myogenic and metabolic is of course somewhat of a crude one that should be revisited in more detail in future.…”

Section: Discussionmentioning

confidence: 99%

“…The brain is one of the most tightly regulated organs in the human body, with cerebral blood flow being matched both locally and globally to metabolic needs through a number of different mechanisms. One of the most important aspects of control is that cerebral blood flow is maintained near constant over a wide range of arterial blood pressure (ABP): this is known as cerebral autoregulation [1], first quantified by [2] in its static form. Later studies then explored the dynamic response to changes in ABP, determining its characteristic biphasic response [3].…”

Section: Introductionmentioning

confidence: 99%

Identifying the myogenic and metabolic components of cerebral autoregulation

Payne

2018

Medical Engineering & Physics

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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.

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“…It is not yet clear whether or not this will affect the risk of stroke. After all, although impaired cerebral autoregulation is implicated in a number of pathological conditions, we do not yet know whether it is a cause or a symptom (Payne, ).…”

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confidence: 99%

Cerebral Autoregulation

Cited by 48 publications

References 288 publications

Comparison of static and dynamic cerebral autoregulation under anesthesia influence in a controlled animal model

Comparison of static and dynamic cerebral autoregulation under anesthesia influence in a controlled animal model

Identifying the myogenic and metabolic components of cerebral autoregulation

Continuous positive airway pressure might not solve your cerebral autoregulation problem if you have obstructive sleep apnoea

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