Chapter 9
Modelling of Cerebrospinal Fluid Flow
by Computational Fluid Dynamics
Vartan Kurtcuoglu, Kartik Jain, and Bryn A. Martin
9.1 Introduction
The movement of cerebrospinal fluid (CSF) is linked to the cardiovascular and
respiratory systems. The heart not only drives blood flow but is also at the origin
of CSF pulsation through the expansion and contraction of cerebral blood vessels.
Respiration modulates this cardiovascular action while also directly influencing
spinal subarachnoid space (SAS) volume. CSF dynamics may be altered by pathologies such as hydrocephalus, Chiari malformation, syringomyelia and glioblastoma,
and, in turn, dynamics of the CSF can be analysed to aid in disease diagnosis and
prognosis. Several reviews delineate the current understanding of CSF motion [1–
3]. This chapter describes the basic approach of and trends in computational fluid
dynamics (CFD) modelling of CSF flow.
There are multiple types of computational models of fluid flow within and around
the central nervous system (CNS). These can be roughly categorized into bulk
models aimed at providing information on macroscale CSF dynamics and CFD
models that yield spatially resolved data. The principal advantage of bulk models is
their low computational demand, enabling calculations on personal computers rather
than necessitating high-performance computing (HPC) resources. This is especially
important in view of potential clinical applications, where access to HPC is scarce
and results must be provided with minimal time delay. However, bulk models do
not take into account the complex anatomy of the CSF spaces and cannot fully
resolve the intricate dynamics of CSF flow. In contrast, three-dimensional (3D) CFD
V. Kurtcuoglu () · K. Jain
University of Zurich, Institute of Physiology, Zurich, Switzerland
e-mail: vartan.kurtcuoglu@uzh.ch
B. A. Martin
University of Idaho, Department of Biological Engineering, Moscow, ID, USA
© Springer Nature Switzerland AG 2019
K. Miller (ed.), Biomechanics of the Brain, Biological and Medical Physics,
Biomedical Engineering, https://doi.org/10.1007/978-3-030-04996-6_9
215
Modelling of Cerebrospinal Fluid Flow
by Computational Fluid Dynamics
Vartan Kurtcuoglu, Kartik Jain, and Bryn A. Martin
9.1 Introduction
The movement of cerebrospinal fluid (CSF) is linked to the cardiovascular and
respiratory systems. The heart not only drives blood flow but is also at the origin
of CSF pulsation through the expansion and contraction of cerebral blood vessels.
Respiration modulates this cardiovascular action while also directly influencing
spinal subarachnoid space (SAS) volume. CSF dynamics may be altered by pathologies such as hydrocephalus, Chiari malformation, syringomyelia and glioblastoma,
and, in turn, dynamics of the CSF can be analysed to aid in disease diagnosis and
prognosis. Several reviews delineate the current understanding of CSF motion [1–
3]. This chapter describes the basic approach of and trends in computational fluid
dynamics (CFD) modelling of CSF flow.
There are multiple types of computational models of fluid flow within and around
the central nervous system (CNS). These can be roughly categorized into bulk
models aimed at providing information on macroscale CSF dynamics and CFD
models that yield spatially resolved data. The principal advantage of bulk models is
their low computational demand, enabling calculations on personal computers rather
than necessitating high-performance computing (HPC) resources. This is especially
important in view of potential clinical applications, where access to HPC is scarce
and results must be provided with minimal time delay. However, bulk models do
not take into account the complex anatomy of the CSF spaces and cannot fully
resolve the intricate dynamics of CSF flow. In contrast, three-dimensional (3D) CFD
V. Kurtcuoglu () · K. Jain
University of Zurich, Institute of Physiology, Zurich, Switzerland
e-mail: vartan.kurtcuoglu@uzh.ch
B. A. Martin
University of Idaho, Department of Biological Engineering, Moscow, ID, USA
© Springer Nature Switzerland AG 2019
K. Miller (ed.), Biomechanics of the Brain, Biological and Medical Physics,
Biomedical Engineering, https://doi.org/10.1007/978-3-030-04996-6_9
215