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The intracranial pressure curve correlates to the pulsatile component of cerebral blood flow

Unnerbäck, Mårten LU ; Bloomfield, Eric L. ; Söderström, Sven and Reinstrup, Peter LU (2019) In Journal of Clinical Monitoring and Computing 33(1). p.77-83
Abstract

Current methods to measure cerebral blood flow (CBF) in the neuro critical care setting cannot monitor the CBF continuously. In contrast, continuous measurement of intracranial pressure (ICP) is readily accomplished, and there is a component of ICP that correlates with arterial inflow of blood into the cranial cavity. This property may have utility in using continuous ICP curve analysis to continuously estimate CBF. We examined the data from 13 patients, monitored with an intraventricular ICP device determining the pulsatile amplitude ICPamp as well as the area under the ICP curve (AUCICP). Using an elastance measurement, the ICP curve was converted to craniospinal volume (AUCΔV). The patients were... (More)

Current methods to measure cerebral blood flow (CBF) in the neuro critical care setting cannot monitor the CBF continuously. In contrast, continuous measurement of intracranial pressure (ICP) is readily accomplished, and there is a component of ICP that correlates with arterial inflow of blood into the cranial cavity. This property may have utility in using continuous ICP curve analysis to continuously estimate CBF. We examined the data from 13 patients, monitored with an intraventricular ICP device determining the pulsatile amplitude ICPamp as well as the area under the ICP curve (AUCICP). Using an elastance measurement, the ICP curve was converted to craniospinal volume (AUCΔV). The patients were examined with Phase Contrast Magnetic Resonance Imaging (MRI), measuring flow in the carotid and vertebral arteries. This made it possible to calculate CBF for one cardiac cycle (ccCBFMRtot) and divide it into the pulsatile (ccCBFMRpuls) and non-pulsatile (ccCBFMRconst) flow. ICP derived data and MRI measurements were compared. Linear regression was used to establish wellness of fit and ANOVA was used to calculate the P value. No correlation was found between ICPamp and the ccICPMRpuls (P = 0.067). In contrast there was a correlation between the AUCICP and ccCBFMRpuls (R2 = 0.440 P = 0.013). The AUCΔV correlated more appropriately with the ccCBFMRpuls. (R2 = 0.688 P < 0.001). Our findings suggests that the pulsatile part of the intracranial pressure curve, especially when transformed into a volume curve, correlates to the pulsatile part of the CBF.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Cerebral blood flow, Intracranial pressure, Mathematical analysis, Monitoring, Phase contrast magnetic resonance imaging
in
Journal of Clinical Monitoring and Computing
volume
33
issue
1
pages
77 - 83
publisher
Springer
external identifiers
  • pmid:29549499
  • scopus:85044040398
ISSN
1387-1307
DOI
10.1007/s10877-018-0129-0
language
English
LU publication?
yes
id
6c111a7c-3b1b-4479-913f-7256d922c333
date added to LUP
2018-04-06 07:30:01
date last changed
2024-02-13 18:10:20
@article{6c111a7c-3b1b-4479-913f-7256d922c333,
  abstract     = {{<p>Current methods to measure cerebral blood flow (CBF) in the neuro critical care setting cannot monitor the CBF continuously. In contrast, continuous measurement of intracranial pressure (ICP) is readily accomplished, and there is a component of ICP that correlates with arterial inflow of blood into the cranial cavity. This property may have utility in using continuous ICP curve analysis to continuously estimate CBF. We examined the data from 13 patients, monitored with an intraventricular ICP device determining the pulsatile amplitude ICP<sub>amp</sub> as well as the area under the ICP curve (AUC<sub>ICP</sub>). Using an elastance measurement, the ICP curve was converted to craniospinal volume (AUC<sub>ΔV</sub>). The patients were examined with Phase Contrast Magnetic Resonance Imaging (MRI), measuring flow in the carotid and vertebral arteries. This made it possible to calculate CBF for one cardiac cycle (ccCBF<sub>MRtot</sub>) and divide it into the pulsatile (ccCBF<sub>MRpuls</sub>) and non-pulsatile (ccCBF<sub>MRconst</sub>) flow. ICP derived data and MRI measurements were compared. Linear regression was used to establish wellness of fit and ANOVA was used to calculate the P value. No correlation was found between ICP<sub>amp</sub> and the ccICP<sub>MRpuls</sub> (P = 0.067). In contrast there was a correlation between the AUC<sub>ICP</sub> and ccCBF<sub>MRpuls</sub> (R<sup>2</sup> = 0.440 P = 0.013). The AUC<sub>ΔV</sub> correlated more appropriately with the ccCBF<sub>MRpuls</sub>. (R<sup>2</sup> = 0.688 P &lt; 0.001). Our findings suggests that the pulsatile part of the intracranial pressure curve, especially when transformed into a volume curve, correlates to the pulsatile part of the CBF.</p>}},
  author       = {{Unnerbäck, Mårten and Bloomfield, Eric L. and Söderström, Sven and Reinstrup, Peter}},
  issn         = {{1387-1307}},
  keywords     = {{Cerebral blood flow; Intracranial pressure; Mathematical analysis; Monitoring; Phase contrast magnetic resonance imaging}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{77--83}},
  publisher    = {{Springer}},
  series       = {{Journal of Clinical Monitoring and Computing}},
  title        = {{The intracranial pressure curve correlates to the pulsatile component of cerebral blood flow}},
  url          = {{http://dx.doi.org/10.1007/s10877-018-0129-0}},
  doi          = {{10.1007/s10877-018-0129-0}},
  volume       = {{33}},
  year         = {{2019}},
}