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Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet).

Authors :
Kostoglou K
Bello-Robles F
Brassard P
Chacon M
Claassen JA
Czosnyka M
Elting JW
Hu K
Labrecque L
Liu J
Marmarelis VZ
Payne SJ
Shin DC
Simpson D
Smirl J
Panerai RB
Mitsis GD
Source :
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism [J Cereb Blood Flow Metab] 2024 Sep; Vol. 44 (9), pp. 1480-1514. Date of Electronic Publication: 2024 Apr 30.
Publication Year :
2024

Abstract

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA.<br />Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Details

Language :
English
ISSN :
1559-7016
Volume :
44
Issue :
9
Database :
MEDLINE
Journal :
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Publication Type :
Academic Journal
Accession number :
38688529
Full Text :
https://doi.org/10.1177/0271678X241249276