Literature DB >> 13130182

Mechanisms underlying phase lag between systemic arterial blood pressure and cerebral blood flow velocity.

Terry B J Kuo1, Chang-Ming Chern, Cheryl C H Yang, Hung-Yi Hsu, Wen-Jang Wong, Wen-Yung Sheng, Han-Hwa Hu.   

Abstract

To explore the mechanisms underlying the phase lag between oscillations in arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV), ABP and CBFV signals were recorded noninvasively from normal volunteers who lay quietly in a supine position. Mean ABP (MAP) and CBFV (MFV) were calculated beat-to-beat by means of integration. Cerebral vascular resistance (CVR) was calculated by dividing MAP with MFV. Frequency domain analysis of MAP, MFV and CVR signals revealed very-low frequency (VLF, 0.016-0.04 Hz), low-frequency (LF, 0.04-0.15 Hz), and high-frequency (HF, 0.15-0.4 Hz) components. The transfer phase of MAP-CVR coupling in the LF and HF range was frequency-dependent, which is equivalent to a time delay of 2 s. However, the transfer phase differed in the CVR-MFV coupling in that the phase was distributed around 180 degrees across the LF and HF ranges. Cross-correlation analysis revealed a positive relationship between MAP-CVR coupling, with MAP leading by 2 s, and a negative relationship between CVR-MFV coupling, with CVR leading by 0.3 s. We concluded that the phase lag between oscillations in ABP and CBFV was chiefly contributed to by the starting latency of cerebral autoregulation (i.e. cerebral vasomotion, revealed by MAP-CVR coupling). Moreover, the negative correlation of the CVR-MFV coupling could offer a different explanation for the physiologic significance of the phase lead of CBFV-ABP oscillations. Copyright 2003 S. Karger AG, Basel

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Year:  2003        PMID: 13130182     DOI: 10.1159/000072564

Source DB:  PubMed          Journal:  Cerebrovasc Dis        ISSN: 1015-9770            Impact factor:   2.762


  10 in total

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Journal:  Neurosci Lett       Date:  2015-03-04       Impact factor: 3.046

2.  Continuous cerebral autoregulation monitoring by improved cross-correlation analysis: comparison with the cuff deflation test.

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3.  Low frequency oscillations in cephalic vessels assessed by near infrared spectroscopy.

Authors:  Dorte Phillip; Henrik W Schytz; Juliette Selb; Stephen Payne; Helle K Iversen; Lene T Skovgaard; David A Boas; Messoud Ashina
Journal:  Eur J Clin Invest       Date:  2012-08-16       Impact factor: 4.686

4.  Dynamic cerebral autoregulation is transiently impaired for one week after large-vessel acute ischemic stroke.

Authors:  Nils H Petersen; Santiago Ortega-Gutierrez; Andrés Reccius; Arjun Masurkar; Amy Huang; Randolph S Marshall
Journal:  Cerebrovasc Dis       Date:  2015-02-03       Impact factor: 2.762

5.  Cerebral autoregulation assessed by near-infrared spectroscopy: validation using transcranial Doppler in patients with controlled hypertension, cognitive impairment and controls.

Authors:  Arjen Mol; Carel G M Meskers; Marit L Sanders; Martin Müller; Andrea B Maier; Richard J A van Wezel; Jurgen A H R Claassen; Jan Willem J Elting
Journal:  Eur J Appl Physiol       Date:  2021-04-16       Impact factor: 3.078

6.  Preserved dynamic cerebral autoregulation in the middle cerebral artery among persons with migraine.

Authors:  M Reinhard; E Wehrle-Wieland; M Roth; W D Niesen; J Timmer; C Weiller; A Hetzel
Journal:  Exp Brain Res       Date:  2007-02-06       Impact factor: 2.064

7.  A nonlinear dynamic approach reveals a long-term stroke effect on cerebral blood flow regulation at multiple time scales.

Authors:  Kun Hu; Men-Tzung Lo; Chung-Kang Peng; Yanhui Liu; Vera Novak
Journal:  PLoS Comput Biol       Date:  2012-07-12       Impact factor: 4.475

Review 8.  Monitoring of cerebrovascular autoregulation: facts, myths, and missing links.

Authors:  Marek Czosnyka; Ken Brady; Matthias Reinhard; Piotr Smielewski; Luzius A Steiner
Journal:  Neurocrit Care       Date:  2009-01-06       Impact factor: 3.210

9.  Artifact rejection and missing data imputation in cerebral blood flow velocity signals via trace norm minimization.

Authors:  Cameron Allan Gunn; Xiao Hu; Lieven Vandenberghe
Journal:  Physiol Meas       Date:  2020-12-11       Impact factor: 2.833

10.  Transfer function analysis of respiratory and cardiac pulsations in human brain observed on dynamic magnetic resonance images.

Authors:  Yi-Hsuan Kao; Wan-Yuo Guo; Adrain Jy-Kang Liou; Ting-Yi Chen; Chau-Chiun Huang; Chih-Che Chou; Jiing-Feng Lirng
Journal:  Comput Math Methods Med       Date:  2013-04-24       Impact factor: 2.238

  10 in total

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