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A mathematical framework for the dynamic interaction of pulsatile blood, brain, and cerebrospinal fluid. | LitMetric

A mathematical framework for the dynamic interaction of pulsatile blood, brain, and cerebrospinal fluid.

Comput Methods Programs Biomed

Department of Neurological Surgery, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA.

Published: April 2023

AI Article Synopsis

  • The study explores the dynamics of intracranial fluid flow to better understand hydrocephalus by using a mathematical model that compares healthy individuals with hydrocephalus patients.
  • It utilizes pulsatile blood velocity data from cine PC-MRI and applies mathematical equations to analyze the interactions between blood, brain tissue, and cerebrospinal fluid (CSF).
  • Results indicate that CSF velocity and pressure variations are influenced throughout the cardiac cycle, especially highlighting differences between healthy subjects and those with hydrocephalus.

Article Abstract

Background: Shedding light on less-known aspects of intracranial fluid dynamics may be helpful to understand the hydrocephalus mechanism. The present study suggests a mathematical framework based on in vivo inputs to compare the dynamic interaction of pulsatile blood, brain, and cerebrospinal fluid (CSF) between the healthy subject and the hydrocephalus patient.

Method: The input data for the mathematical formulations was pulsatile blood velocity, which was measured using cine PC-MRI. Tube law was used to transfer the created deformation by blood pulsation in the vessel circumference to the brain domain. The pulsatile deformation of brain tissue with respect to time was calculated and considered to be inlet velocity in the CSF domain. The governing equations in all three domains were continuity, Navier-Stokes, and concentration. We used Darcy law with defined permeability and diffusivity values to define the material properties in the brain.

Results: We validated the preciseness of the CSF velocity and pressure through the mathematical formulations with cine PC-MRI velocity, experimental ICP, and FSI simulated velocity and pressure. We used the analysis of dimensionless numbers including Reynolds, Womersley, Hartmann, and Peclet to evaluate the characteristics of the intracranial fluid flow. In the mid-systole phase of a cardiac cycle, CSF velocity had the maximum value and CSF pressure had the minimum value. The maximum and amplitude of CSF pressure, as well as CSF stroke volume, were calculated and compared between the healthy subject and the hydrocephalus patient.

Conclusion: The present in vivo-based mathematical framework has the potential to gain insight into the less-known points in the physiological function of intracranial fluid dynamics and the hydrocephalus mechanism.

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Source
http://dx.doi.org/10.1016/j.cmpb.2022.107209DOI Listing

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