Validation of a mathematical model for understanding intracranial pressure curve morphology

Research output: Contribution to journalArticle


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.


External organisations
  • Skåne University Hospital
  • Zealand University Hospital
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Anesthesiology and Intensive Care


  • Cerebral blood flow, Intracranial pressure, Mathematical modelling, Phase contrast magnetic resonance imaging
Original languageEnglish
Pages (from-to)469-481
Number of pages13
JournalJournal of Clinical Monitoring and Computing
Issue number3
Early online date2019 Jul 1
Publication statusPublished - 2020 Jun
Publication categoryResearch