Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes

Cerebral Flow Autoregulation (CFA) is the dynamic process by which cerebral blood flow is maintained within physiologically acceptable bounds during fluctuations of cerebral perfusion pressure. The distinction is made with “static” flow autoregulation under steady-state conditions of perfusion press...

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Main Authors:	Marmarelis, VZ, Shin, DC, Zhang, R
Format:	Online
Language:	English
Published:	Bentham Open 2012
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3377891/

id	pubmed-3377891
recordtype	oai_dc
spelling	pubmed-33778912012-06-21 Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes Marmarelis, VZ Shin, DC Zhang, R Article Cerebral Flow Autoregulation (CFA) is the dynamic process by which cerebral blood flow is maintained within physiologically acceptable bounds during fluctuations of cerebral perfusion pressure. The distinction is made with “static” flow autoregulation under steady-state conditions of perfusion pressure, described by the celebrated “autoregulatory curve” with a homeostatic plateau. This paper studies the dynamic CFA during changes in perfusion pressure, which attains critical clinical importance in patients with stroke, traumatic brain injury and neurodegenerative disease with a cerebrovascular component. Mathematical and computational models have been used to advance our quantitative understanding of dynamic CFA and to elucidate the underlying physiological mechanisms by analyzing the relation between beat-to-beat data of mean arterial blood pressure (viewed as input) and mean cerebral blood flow velocity(viewed as output) of a putative CFA system. Although previous studies have shown that the dynamic CFA process is nonlinear, most modeling studies to date have been linear. It has also been shown that blood CO2 tension affects the CFA process. This paper presents a nonlinear modeling methodology that includes the dynamic effects of CO2 tension (or its surrogate, end-tidal CO2) as a second input and quantifies CFA from short data-records of healthy human subjects by use of the modeling concept of Principal Dynamic Modes (PDMs). The PDMs improve the robustness of the obtained nonlinear models and facilitate their physiological interpretation. The results demonstrate the importance of including the CO2 input in the dynamic CFA study and the utility of nonlinear models under hypercapnic or hypocapnic conditions. Bentham Open 2012-04-26 /pmc/articles/PMC3377891/ /pubmed/22723806 http://dx.doi.org/10.2174/1874230001206010042 Text en © Marmarelis et al.; Licensee Bentham Open. http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Marmarelis, VZ Shin, DC Zhang, R
spellingShingle	Marmarelis, VZ Shin, DC Zhang, R Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes
author_facet	Marmarelis, VZ Shin, DC Zhang, R
author_sort	Marmarelis, VZ
title	Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes
title_short	Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes
title_full	Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes
title_fullStr	Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes
title_full_unstemmed	Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes
title_sort	linear and nonlinear modeling of cerebral flow autoregulation using principal dynamic modes
description	Cerebral Flow Autoregulation (CFA) is the dynamic process by which cerebral blood flow is maintained within physiologically acceptable bounds during fluctuations of cerebral perfusion pressure. The distinction is made with “static” flow autoregulation under steady-state conditions of perfusion pressure, described by the celebrated “autoregulatory curve” with a homeostatic plateau. This paper studies the dynamic CFA during changes in perfusion pressure, which attains critical clinical importance in patients with stroke, traumatic brain injury and neurodegenerative disease with a cerebrovascular component. Mathematical and computational models have been used to advance our quantitative understanding of dynamic CFA and to elucidate the underlying physiological mechanisms by analyzing the relation between beat-to-beat data of mean arterial blood pressure (viewed as input) and mean cerebral blood flow velocity(viewed as output) of a putative CFA system. Although previous studies have shown that the dynamic CFA process is nonlinear, most modeling studies to date have been linear. It has also been shown that blood CO2 tension affects the CFA process. This paper presents a nonlinear modeling methodology that includes the dynamic effects of CO2 tension (or its surrogate, end-tidal CO2) as a second input and quantifies CFA from short data-records of healthy human subjects by use of the modeling concept of Principal Dynamic Modes (PDMs). The PDMs improve the robustness of the obtained nonlinear models and facilitate their physiological interpretation. The results demonstrate the importance of including the CO2 input in the dynamic CFA study and the utility of nonlinear models under hypercapnic or hypocapnic conditions.
publisher	Bentham Open
publishDate	2012
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3377891/
_version_	1611537597930143744

Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes

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