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Published in: Journal of Clinical Monitoring and Computing 3/2020

Open Access 01-06-2020 | Intracranial Hypertension | Original Research

Validation of a mathematical model for understanding intracranial pressure curve morphology

Authors: Mårten Unnerbäck, Johnny T. Ottesen, Peter Reinstrup

Published in: Journal of Clinical Monitoring and Computing | Issue 3/2020

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Abstract

The physiology underlying the intracranial pressure (ICP) curve morphology is not fully understood. Recent research has suggested that the morphology could be dependent on arterial cerebral inflow and the physiological and pathophysiological properties of the intracranial cavity. If understood, the ICP curve could provide information about the patient’s cerebrovascular state important in individualizing treatment in neuro intensive care patients. A mathematical model based on known physiological properties of the intracranial compartment was created. Clinical measurements from ten neuro intensive care patients in whom intracranial arterial blood inflow, venous blood outflow and cerebrospinal fluid flow over the foramen magnum had been measured with phase contrast MRI, concomitant with ICP measurements were used to validate the model. In nine patients the mathematical model was able to create an ICP curve mimicking the measured by using arterial intracranial inflow and adjusting physiological parameters of the model. The venous outflow and cerebrospinal fluid (CSF) flow over the foramen magnum predicted by the model were within physiologically reasonable limits and in most cases followed the MRI measured values in close adjunct. The presented model could produce an ICP curve in close resemblance of the in vivo measured curves. This strengthens the hypothesis that the ICP curve is shaped by the arterial intracranial inflow and the physiological properties of the intracranial cavity.
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Metadata
Title
Validation of a mathematical model for understanding intracranial pressure curve morphology
Authors
Mårten Unnerbäck
Johnny T. Ottesen
Peter Reinstrup
Publication date
01-06-2020
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 3/2020
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-019-00342-8

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