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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)

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posted on 2024-05-13, 15:01 authored by Kyriaki Kostoglou, Felipe Bello-Robles, Patrice Brassard, Max Chacon, Jurgen AHR Claassen, Marek Czosnyka, Jan-Willem Elting, Kun Hu, Lawrence Labrecque, Jia Liu, Vasilis Z Marmarelis, Stephen J Payne, Dae Cheol Shin, David Simpson, Jonathan Smirl, Ronney PaneraiRonney Panerai, Georgios D Mitsis
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.

History

Author affiliation

College of Life Sciences/Cardiovascular Sciences

Version

  • VoR (Version of Record)

Published in

Journal of Cerebral Blood Flow & Metabolism

Pagination

271678X241249276

Publisher

SAGE Publications

issn

0271-678X

eissn

1559-7016

Copyright date

2024

Available date

2024-05-13

Spatial coverage

United States

Language

en

Deposited by

Professor Ronney Panerai

Deposit date

2024-05-12

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