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Assessment of cerebral hemodynamic parameters using pulsatile versus non-pulsatile cerebral blood outflow models

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Abstract

Background

Prior methods evaluating the changes in cerebral arterial blood volume (∆CaBV) assumed that brain blood transport distal to big cerebral arteries can be approximated with a non-pulsatile flow (CFF) model. In this study, a modified ∆CaBV calculation that accounts for pulsatile blood flow forward (PFF) from large cerebral arteries to resistive arterioles was investigated. The aim was to assess cerebral hemodynamic indices estimated by both CFF and PFF models while changing arterial blood carbon dioxide concentration (EtCO2) in healthy volunteers.

Materials and methods

Continuous recordings of non-invasive arterial blood pressure (ABP), transcranial Doppler blood flow velocity (CBFVa), and EtCO2 were performed in 53 young volunteers at baseline and during both hypo- and hypercapnia. The time constant of the cerebral arterial bed (τ) and critical closing pressure (CrCP) were estimated using mathematical transformations of the pulse waveforms of ABP and CBFVa, and with both pulsatile and non-pulsatile models of ∆CaBV estimation. Results are presented as median values ± interquartile range.

Results

Both CrCP and τ gave significantly lower values with the PFF model when compared with the CFF model (p ≪ 0.001 for both). In comparison to normocapnia, both CrCP and τ determined with the PFF model increased during hypocapnia [CrCPPFF (mm Hg): 5.52 ± 8.78 vs. 14.36 ± 14.47, p = 0.00006; τPFF (ms): 47.4 ± 53.9 vs. 72.8 ± 45.7, p = 0.002] and decreased during hypercapnia [CrCPPFF (mm Hg): 5.52 ± 8.78 vs. 2.36 ± 7.05, p = 0.0001; τPFF (ms): 47.4 ± 53.9 vs. 29.0 ± 31.3, p = 0.0003]. When the CFF model was applied, no changes were found for CrCP during hypercapnia or in τ during hypocapnia.

Conclusion

Our results suggest that the pulsatile flow forward model better reflects changes in CrCP and in τ induced by controlled alterations in EtCO2.

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Acknowledgements

We thank Krystian Gruszczyński, Msc. Eng. for assistance with data collection and Tomasz Szczepański, PhD for reviewing medical history and physical examination.

Funding

This research was supported by the National Science Center (Poland) under Grant No. UMO-2013/10/E/ST7/00117.

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Agnieszka Uryga & Magdalena Kasprowicz

  2. Brain Physics Laboratory, Department of Clinical Neurosciences, Division of Neurosurgery, University of Cambridge, Cambridge, UK

    Leanne Calviello & Marek Czosnyka

  3. Department of Neurology, Alfried-Krupp-Krankenhaus, Essen, Germany

    Rolf R. Diehl

  4. Department of Neurosurgery, Mossakowski Medical Research Centre Polish Academy of Sciences, Warsaw, Poland

    Katarzyna Kaczmarska

  5. Institute of Electronic Systems, Warsaw University of Technology, Warsaw, Poland

    Katarzyna Kaczmarska & Marek Czosnyka

Authors
  1. Agnieszka Uryga
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  2. Magdalena Kasprowicz
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  3. Leanne Calviello
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  4. Rolf R. Diehl
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  5. Katarzyna Kaczmarska
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  6. Marek Czosnyka
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Corresponding author

Correspondence to Agnieszka Uryga.

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Conflict of interest

ICM + Software is licensed by Cambridge Enterprise, Cambridge, UK, http://www.neurosurg.cam.ac.uk/icmplus/. Prof. Czosnyka has a financial interest in a fraction of the licensing fee for ICM + software. The other authors declare that they have no conflicts of interest.

Informed consent

The protocol complied with the Declaration of Helsinki of the World Medical Association, and all participants gave written informed consent before participating in the study.

Research involving human and animal rights

The study was approved by the bioethical committee of the Wroclaw Medical University (Permission No. KB-170/2014).

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Uryga, A., Kasprowicz, M., Calviello, L. et al. Assessment of cerebral hemodynamic parameters using pulsatile versus non-pulsatile cerebral blood outflow models. J Clin Monit Comput 33, 85–94 (2019). https://doi.org/10.1007/s10877-018-0136-1

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  • DOI: https://doi.org/10.1007/s10877-018-0136-1

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