Literature DB >> 18432311

Altered Phase Interactions between Spontaneous Blood Pressure and Flow Fluctuations in Type 2 Diabetes Mellitus: Nonlinear Assessment of Cerebral Autoregulation.

Kun Hu1, C K Peng, Norden E Huang, Zhaohua Wu, Lewis A Lipsitz, Jerry Cavallerano, Vera Novak.   

Abstract

Cerebral autoregulation (CA) is an important mechanism that involves dilation and constriction in arterioles to maintain relatively s cerebral blood flow in response to changes of systemic blood pressure. Traditional assessments of CA focus on the changes of cerebral blood flow velocity in response to large blood pressure fluctuations induced by interventions. This approach is not feasible for patients with impaired autoregulation or cardiovascular regulation. Here we propose a newly developed technique-the multimodal pressure-flow (MMPF) analysis, which assesses CA by quantifying nonlinear phase interactions between spontaneous oscillations in blood pressure and flow velocity during resting conditions. We show that CA in healthy subjects can be characterized by specific phase shifts between spontaneous blood pressure and flow velocity oscillations, and the phase shifts are significantly reduced in diabetic subjects. Smaller phase shifts between oscillations in the two variables indicate more passive dependence of blood flow velocity on blood pressure, thus suggesting impaired cerebral autoregulation. Moreover, the reduction of the phase shifts in diabetes is observed not only in previously-recognized effective region of CA (<0.1Hz), but also over the higher frequency range from ~0.1 to 0.4Hz. These findings indicate that Type 2 diabetes alters cerebral blood flow regulation over a wide frequency range and that this alteration can be reliably assessed from spontaneous oscillations in blood pressure and blood flow velocity during resting conditions. We also show that the MMPF method has better performance than traditional approaches based on Fourier transform, and is more sui for the quantification of nonlinear phase interactions between nonstationary biological signals such as blood pressure and blood flow.

Entities:  

Year:  2008        PMID: 18432311      PMCID: PMC2329796          DOI: 10.1016/j.physa.2007.11.052

Source DB:  PubMed          Journal:  Physica A        ISSN: 0378-4371            Impact factor:   3.263


  55 in total

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  27 in total

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Authors:  Sunghan Kim; Marvin Bergsneider; Xiao Hu
Journal:  Physiol Meas       Date:  2011-02-01       Impact factor: 2.833

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Authors:  Vera Novak; Ihab Hajjar
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Authors:  Ronney B Panerai
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4.  The Fourier decomposition method for nonlinear and non-stationary time series analysis.

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Journal:  Proc Math Phys Eng Sci       Date:  2017-03-15       Impact factor: 2.704

5.  Detection of impaired cerebral autoregulation improves by increasing arterial blood pressure variability.

Authors:  Emmanuel Katsogridakis; Glen Bush; Lingke Fan; Anthony A Birch; David M Simpson; Robert Allen; John F Potter; Ronney B Panerai
Journal:  J Cereb Blood Flow Metab       Date:  2012-12-12       Impact factor: 6.200

6.  Spurious cross-frequency amplitude-amplitude coupling in nonstationary, nonlinear signals.

Authors:  Chien-Hung Yeh; Men-Tzung Lo; Kun Hu
Journal:  Physica A       Date:  2016-07-15       Impact factor: 3.263

7.  Correlation analysis of laser Doppler flowmetry signals: a potential non-invasive tool to assess microcirculatory changes in diabetes mellitus.

Authors:  Cerine Lal; Sujatha Narayanan Unni
Journal:  Med Biol Eng Comput       Date:  2015-03-10       Impact factor: 2.602

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Journal:  Beijing Da Xue Xue Bao Yi Xue Ban       Date:  2019-06-18

10.  Neurovascular regulation in the ischemic brain.

Authors:  Katherine Jackman; Costantino Iadecola
Journal:  Antioxid Redox Signal       Date:  2015-01-10       Impact factor: 8.401

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