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Model-based Indices Describing Cerebrovascular Dynamics

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.

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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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Varsos, G.V., Kasprowicz, M., Smielewski, P. et al. Model-based Indices Describing Cerebrovascular Dynamics. Neurocrit Care 20, 142–157 (2014). https://doi.org/10.1007/s12028-013-9868-4

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Keywords

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