Literature DB >> 23292615

Closed-loop dynamic modeling of cerebral hemodynamics.

V Z Marmarelis1, D C Shin, M E Orme, R Zhang.   

Abstract

The dynamics of cerebral hemodynamics have been studied extensively because of their fundamental physiological and clinical importance. In particular, the dynamic processes of cerebral flow autoregulation (CFA) and CO2 vasomotor reactivity have attracted broad attention because of their involvement in a host of pathologies and clinical conditions (e.g., hypertension, syncope, stroke, traumatic brain injury, vascular dementia, Alzheimer's disease, mild cognitive impairment etc.). This raises the prospect of useful diagnostic methods being developed on the basis of quantitative models of cerebral hemodynamics, if cerebral vascular dysfunction can be quantified reliably from data collected within practical clinical constraints. This paper presents a modeling method that utilizes beat-to-beat measurements of mean arterial blood pressure, cerebral blood flow velocity and end-tidal CO2 (collected non-invasively under resting conditions) to quantify the dynamics of CFA and cerebral vasomotor reactivity (CVMR). The unique and novel aspect of this dynamic model is that it is nonlinear and operates in a closed-loop configuration.

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Mesh:

Year:  2013        PMID: 23292615      PMCID: PMC3625507          DOI: 10.1007/s10439-012-0736-8

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  22 in total

1.  Autonomic neural control of dynamic cerebral autoregulation in humans.

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Review 2.  Neurovascular regulation in the normal brain and in Alzheimer's disease.

Authors:  Costantino Iadecola
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3.  Cerebral hemodynamics during orthostatic stress assessed by nonlinear modeling.

Authors:  Georgios D Mitsis; Rong Zhang; Benjamin D Levine; Vasilis Z Marmarelis
Journal:  J Appl Physiol (1985)       Date:  2006-03-02

Review 4.  Cerebral autoregulation: an overview of current concepts and methodology with special focus on the elderly.

Authors:  Arenda Hea van Beek; Jurgen Ahr Claassen; Marcel Gm Olde Rikkert; René Wmm Jansen
Journal:  J Cereb Blood Flow Metab       Date:  2008-03-19       Impact factor: 6.200

5.  Transfer function analysis of dynamic cerebral autoregulation in humans.

Authors:  R Zhang; J H Zuckerman; C A Giller; B D Levine
Journal:  Am J Physiol       Date:  1998-01

6.  Identification of nonlinear biological systems using Laguerre expansions of kernels.

Authors:  V Z Marmarelis
Journal:  Ann Biomed Eng       Date:  1993 Nov-Dec       Impact factor: 3.934

7.  Dynamic pressure-flow relationship of the cerebral circulation during acute increase in arterial pressure.

Authors:  Rong Zhang; Khosrow Behbehani; Benjamin D Levine
Journal:  J Physiol       Date:  2009-04-09       Impact factor: 5.182

8.  Autonomic neural control of cerebral hemodynamics.

Authors:  Georgios D Mitsis; Rong Zhang; Benjamin D Levine; Efthalia Tzanalaridou; Demosthenes G Katritsis; Vasilis Z Marmarelis
Journal:  IEEE Eng Med Biol Mag       Date:  2009 Nov-Dec

9.  Linear and nonlinear modeling of cerebral flow autoregulation using principal dynamic modes.

Authors:  Vz Marmarelis; Dc Shin; R Zhang
Journal:  Open Biomed Eng J       Date:  2012-04-26

10.  Nonlinear assessment of cerebral autoregulation from spontaneous blood pressure and cerebral blood flow fluctuations.

Authors:  Kun Hu; C K Peng; Marek Czosnyka; Peng Zhao; Vera Novak
Journal:  Cardiovasc Eng       Date:  2008-03
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  14 in total

1.  Hippocampal closed-loop modeling and implications for seizure stimulation design.

Authors:  Roman A Sandler; Dong Song; Robert E Hampson; Sam A Deadwyler; Theodore W Berger; Vasilis Z Marmarelis
Journal:  J Neural Eng       Date:  2015-09-10       Impact factor: 5.379

2.  Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.

Authors:  Kunling Geng; Vasilis Z Marmarelis
Journal:  IEEE Trans Neural Netw Learn Syst       Date:  2016-06-24       Impact factor: 10.451

3.  Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Nonlinear Analysis.

Authors:  Brandon Christian Henley; Dae C Shin; Rong Zhang; Vasilis Z Marmarelis
Journal:  IEEE Trans Biomed Eng       Date:  2016-07-09       Impact factor: 4.538

4.  Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.

Authors:  B C Henley; D C Shin; R Zhang; V Z Marmarelis
Journal:  IEEE Access       Date:  2015-10-19       Impact factor: 3.367

5.  Model-based quantification of cerebral hemodynamics as a physiomarker for Alzheimer's disease?

Authors:  V Z Marmarelis; D C Shin; M E Orme; R Zhang
Journal:  Ann Biomed Eng       Date:  2013-06-15       Impact factor: 3.934

6.  Assessment of cerebrovascular reactivity during resting state breathing and its correlation with cognitive function in hypertension.

Authors:  Ihab Hajjar; Vasilis Marmerelis; Dae C Shin; Helena Chui
Journal:  Cerebrovasc Dis       Date:  2014-08-20       Impact factor: 2.762

7.  Model-based physiomarkers of cerebral hemodynamics in patients with mild cognitive impairment.

Authors:  V Z Marmarelis; D C Shin; M E Orme; R Zhang
Journal:  Med Eng Phys       Date:  2014-03-31       Impact factor: 2.242

8.  Non-Linear Characterisation of Cerebral Pressure-Flow Dynamics in Humans.

Authors:  Saqib Saleem; Paul D Teal; W Bastiaan Kleijn; Terrence O'Donnell; Trevor Witter; Yu-Chieh Tzeng
Journal:  PLoS One       Date:  2015-09-30       Impact factor: 3.240

9.  Impaired dynamic cerebral autoregulation and cerebrovascular reactivity in middle cerebral artery stenosis.

Authors:  Jie Chen; Jia Liu; Wei-Hai Xu; Ren Xu; Bo Hou; Li-Ying Cui; Shan Gao
Journal:  PLoS One       Date:  2014-02-04       Impact factor: 3.240

Review 10.  Blood pressure regulation IX: cerebral autoregulation under blood pressure challenges.

Authors:  Yu-Chieh Tzeng; Philip N Ainslie
Journal:  Eur J Appl Physiol       Date:  2013-06-05       Impact factor: 3.078

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