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Neurocritical Care

, Volume 20, Issue 1, pp 142–157 | Cite as

Model-based Indices Describing Cerebrovascular Dynamics

  • Georgios V. VarsosEmail author
  • Magdalena Kasprowicz
  • Peter Smielewski
  • Marek Czosnyka
Review Article

Abstract

Understanding the dynamic relationship between cerebral blood flow (CBF) and the circulation of cerebrospinal fluid (CSF) can facilitate management of cerebral pathologies. For this reason, various hydrodynamic models have been introduced in order to simulate the phenomena governing the interaction between CBF and CSF. The identification of hydrodynamic models requires an array of signals as input, with the most common of them being arterial blood pressure, intracranial pressure, and cerebral blood flow velocity; monitoring all of them is considered as a standard practice in neurointensive care. Based on these signals, physiological parameters like cerebrovascular resistance, compliances of cerebrovascular bed, and CSF space could then be estimated. Various secondary model-based indices describing cerebrovascular dynamics have been introduced, like the cerebral arterial time constant or critical closing pressure. This review presents model-derived indices that describe cerebrovascular phenomena, the nature of which is both physiological (carbon dioxide reactivity and arterial hypotension) and pathological (cerebral artery stenosis, intracranial hypertension, and cerebral vasospasm). In a neurointensive environment, real-time monitoring of a patient with these indices may be able to provide a detection of the onset of a cerebrovascular phenomenon, which could have otherwise been missed. This potentially “early warning” indicator may then prove to be important for the therapeutic management of the patient.

Keywords

Cerebrovascular bed Cerebral blood flow Cerebrospinal fluid Hydrodynamic models Model-based indices Mathematical modeling 

Notes

Conflict of interests

ICM+ software is licensed by Cambridge Enterprise Ltd (www.neurosurg.cam.ac.uk/icmplus). PS and MC have a share in a fraction of licensing fee. There is no other conflict of interest regarding equipment used for monitoring of clinical and experimental signals.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Georgios V. Varsos
    • 1
    • 4
    Email author
  • Magdalena Kasprowicz
    • 2
  • Peter Smielewski
    • 1
  • Marek Czosnyka
    • 1
    • 3
  1. 1.Neurosurgical Unit, Department of Clinical NeurosciencesAddenbrooke’s Hospital, University of CambridgeCambridgeUK
  2. 2.Institute of Biomedical Engineering and InstrumentationWroclaw University of TechnologyWroclawPoland
  3. 3.Institute of Electronic SystemsWarsaw University of TechnologyWarsawPoland
  4. 4.Division of Neurosurgery, Department of Clinical NeurosciencesAddenbrooke’s HospitalCambridgeUK

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