Literature DB >> 21049290

Dynamic cerebral autoregulation: different signal processing methods without influence on results and reproducibility.

Erik D Gommer1, Eri Shijaku, Werner H Mess, Jos P H Reulen.   

Abstract

Cerebral autoregulation controls cerebral blood flow under changing cerebral perfusion pressure. Standards for measurement and analysis of dynamic cerebral autoregulation (dCA) are lacking. In this study, dCA reproducibility, quantified by intraclass correlation coefficient, is evaluated for different methodological approaches of transfer function analysis (TFA) and compared with multimodal pressure flow analysis (MMPF). dCA parameters were determined in 19 healthy volunteers during three 15-min lasting epochs of spontaneous breathing. Every spontaneous breathing epoch was followed by 5 min of paced breathing at 6 cycles/min. These six measurements were performed in both a morning and an afternoon session. Analysis compared raw data pre-processing by mean subtraction versus smoothness priors detrending. The estimation of spectral density was either performed by averaging of subsequent time windows or by smoothing the spectrum of the whole recording. No significant influence of pre-processing and spectral estimation on dCA parameters was found. Therefore, there seems to be no need to prescribe a specific signal-processing regime. Poor reproducibility of gain and phase was found for TFA as well as for MMPF. Based on reproducibility, no preference can be made for morning versus afternoon measurements, neither for spontaneous versus paced breathing. Finally, reproducibility results are not in favour of TFA or MMPF.

Entities:  

Mesh:

Year:  2010        PMID: 21049290      PMCID: PMC2993898          DOI: 10.1007/s11517-010-0706-y

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  25 in total

1.  Assessment of the thigh cuff technique for measurement of dynamic cerebral autoregulation.

Authors:  P J Mahony; R B Panerai; S T Deverson; P D Hayes; D H Evans
Journal:  Stroke       Date:  2000-02       Impact factor: 7.914

2.  Assessing blood flow control through a bootstrap method.

Authors:  David M Simpson; Ronney B Panerai; Eloane G Ramos; José Maria A Lopes; Monica N Villar Marinatto; Jurandir Nadal; David H Evans
Journal:  IEEE Trans Biomed Eng       Date:  2004-07       Impact factor: 4.538

3.  Dynamic cerebral autoregulation during repeated squat-stand maneuvers.

Authors:  Jurgen A H R Claassen; Benjamin D Levine; Rong Zhang
Journal:  J Appl Physiol (1985)       Date:  2008-10-30

4.  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

Review 5.  Cerebral autoregulation.

Authors:  O B Paulson; S Strandgaard; L Edvinsson
Journal:  Cerebrovasc Brain Metab Rev       Date:  1990

6.  Variability of time-domain indices of dynamic cerebral autoregulation.

Authors:  R B Panerai; P J Eames; J F Potter
Journal:  Physiol Meas       Date:  2003-05       Impact factor: 2.833

7.  Transfer function analysis for clinical evaluation of dynamic cerebral autoregulation--a comparison between spontaneous and respiratory-induced oscillations.

Authors:  M Reinhard; T Müller; B Guschlbauer; J Timmer; A Hetzel
Journal:  Physiol Meas       Date:  2003-02       Impact factor: 2.833

8.  Comparison of flow and velocity during dynamic autoregulation testing in humans.

Authors:  D W Newell; R Aaslid; A Lam; T S Mayberg; H R Winn
Journal:  Stroke       Date:  1994-04       Impact factor: 7.914

9.  Multimodal pressure-flow method to assess dynamics of cerebral autoregulation in stroke and hypertension.

Authors:  Vera Novak; Albert C C Yang; Lukas Lepicovsky; Ary L Goldberger; Lewis A Lipsitz; Chung-Kang Peng
Journal:  Biomed Eng Online       Date:  2004-10-25       Impact factor: 2.819

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
View more
  19 in total

Review 1.  Transfer function analysis of dynamic cerebral autoregulation: A white paper from the International Cerebral Autoregulation Research Network.

Authors:  Jurgen A H R Claassen; Aisha S S Meel-van den Abeelen; David M Simpson; Ronney B Panerai
Journal:  J Cereb Blood Flow Metab       Date:  2016-01-18       Impact factor: 6.200

2.  Cerebrovascular hemodynamic changes in multiple sclerosis patients during head-up tilt table test: effect of high-dose intravenous steroid treatment.

Authors:  Zsolt Mezei; Laszlo Olah; Laszlo Kardos; Reka Katalin Kovacs; Laszlo Csiba; Tunde Csepany
Journal:  J Neurol       Date:  2013-06-12       Impact factor: 4.849

3.  Revisiting human cerebral blood flow responses to augmented blood pressure oscillations.

Authors:  J W Hamner; Keita Ishibashi; Can Ozan Tan
Journal:  J Physiol       Date:  2019-01-31       Impact factor: 5.182

4.  Methodological comparison of active- and passive-driven oscillations in blood pressure; implications for the assessment of cerebral pressure-flow relationships.

Authors:  Jonathan D Smirl; Keegan Hoffman; Yu-Chieh Tzeng; Alex Hansen; Philip N Ainslie
Journal:  J Appl Physiol (1985)       Date:  2015-07-16

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.  [Prediction of syncope with nonlinear dynamic analysis during head-up tilt in vasovagal syncope patients].

Authors:  F Li; H B Wang; Q Peng; Y C Sun; R Zhang; B Pang; J Fang; J Zhang; Y N Huang
Journal:  Beijing Da Xue Xue Bao Yi Xue Ban       Date:  2019-06-18

7.  Cerebral autoregulation, beta amyloid, and white matter hyperintensities are interrelated.

Authors:  Adam M Brickman; Vanessa A Guzman; Miguel Gonzalez-Castellon; Qolamreza Razlighi; Yian Gu; Atul Narkhede; Sarah Janicki; Masanori Ichise; Yaakov Stern; Jennifer J Manly; Nicole Schupf; Randolph S Marshall
Journal:  Neurosci Lett       Date:  2015-03-04       Impact factor: 3.046

8.  Assessment of dynamic cerebral autoregulation and cerebral carbon dioxide reactivity during normothermic cardiopulmonary bypass.

Authors:  Ervin E Ševerdija; Erik D Gommer; Patrick W Weerwind; Jos P H Reulen; Werner H Mess; Jos G Maessen
Journal:  Med Biol Eng Comput       Date:  2014-11-21       Impact factor: 2.602

Review 9.  Integrative physiological and computational approaches to understand autonomic control of cerebral autoregulation.

Authors:  Can Ozan Tan; J Andrew Taylor
Journal:  Exp Physiol       Date:  2013-10-04       Impact factor: 2.969

10.  Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure-flow relation: the CARNet study.

Authors:  Aisha S S Meel-van den Abeelen; David M Simpson; Lotte J Y Wang; Cornelis H Slump; Rong Zhang; Takashi Tarumi; Caroline A Rickards; Stephen Payne; Georgios D Mitsis; Kyriaki Kostoglou; Vasilis Marmarelis; Dae Shin; Yu-Chieh Tzeng; Philip N Ainslie; Erik Gommer; Martin Müller; Alexander C Dorado; Peter Smielewski; Bernardo Yelicich; Corina Puppo; Xiuyun Liu; Marek Czosnyka; Cheng-Yen Wang; Vera Novak; Ronney B Panerai; Jurgen A H R Claassen
Journal:  Med Eng Phys       Date:  2014-04-13       Impact factor: 2.242

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.