CSF flow

MODELING OF CEREBROSPINAL FLUID FLOW IN CHIARI MALFORMATION AND SYRINGOMYELIA

Reviewed By: Bryn A. Martin, University of Idaho, Department of Biological Engineering

This article aims to give an overview of the relevance of cerebrospinal fluid (CSF) flow in Type 1 Chiari malformation (CM) and syringomyelia (SM).  It is a breif introduction with limited references to key studies in the literature and their relevant findings.  A more complete reference on these studies is provided by Shaffer et al. [24] and Elliott et al. [20]. 

CSF Flow Study with Multidisciplinary Research

Engineers and medical doctors have teamed together to better understand the biomechanical forces and hydrodynamics (fluid movement) present in CM and SM patients. The ultimate goal of these engineering studies is to deeply understand the biomechanical nature of the disease to improve the treatment experiences of a CM patient. This may be accomplished through novel imaging and simulation tools to improve diagnosis or surgical planning. 

CSF Physiology Basics

CSF motion can be altered in patients with CM and/or SM.  CSF motion can be described in terms of a) net flow production/absorption and b) oscillatory motion.  These terms are often confused and necessitate clarification.  In CM, the type of CSF motion alteration is its oscillatory motion or back-and-forth movement over each cardiac and/or respiratory cycle.

Studies show that CSF net production is about 500 ml/day.  The source of CSF production is thought to be the choroid plexus along the ventricular walls of the brain.  CSF is absorbed into the arachnoid granulations into the venous system.  In addition to net CSF production and absorption, MR imaging has allowed us to measure the back-and-forth motion of CSF with each heart-beat [12,15] and respiration cycle [7,19] around the entire brain and spinal cord and within the ventricles of the brain.  This CSF motion is a special type with approximately zero net flow, also called “oscillatory” flow.

From an anatomic perspective, CM is characterized by cerebellar tonsils that are abnormally positioned downward, toward the feet, below the foramen magnum [1].  The downward position of the cerebellar tonsils makes the fluid space in the craniovertebral junction (connection between the brain and spine) smaller [18].  This smaller space can, and often does, impact the oscillation of CSF between the intracranial and spinal subarachnoid space (space between the neural tissue and outer layer surrounding that tissue called the dura).  Because the space is smaller, the cross-sectional area of the passage is reduced.  Thus, at least part of the CM problem appears to be geometric in nature.

Potential Relation of Geometry, Pressure and Tissue Deformation

However, as is often the case with biological systems, CM pathophysiology is likely more complex than static geometry alone and a chain reaction may, or may not, occur. First, the geometrical changes make it more difficult for CSF to oscillate between the brain and spine. Studies have shown that the smaller cross sectional area in CM patients increases pressure gradients between the intracranial and spinal subarachnoid space compared to healthy people [16,18].  Also, that surgical treatment of CM decreases these pressure gradients.  These studies indicate that in CM patients CSF can still oscillate, but with greater resistance to flow (also called impedance to flow for oscillatory flows).

Over time, these elevated oscillatory pressure gradients can potentially move and distort brain tissue and lead to static/permanent changes in brain stem and cerebellar tonsillar morphology. The heart beats more than 30 million times per year.  Even small alterations in pressure gradients acting over long periods could be impactful and lead to alterations in the elastic properties of the extremely soft brain tissue [2,8].  All these effects could combine to create a flow problem that is more complicated than a simple change in geometry. These pressure gradients are also thought to cause another craniospinal disorder called SM.  However, there are many questions that remain about the exact relationship between CSF flow, pressure and the complex fluid-structure interaction present in SM and CM and how these conditions affect CNS tissue biomechanics.

Studying CSF Motion With Computerized Modeling

The use of computational fluid dynamics (CFD) modeling (i.e., computerized modeling of fluid movement) presents the opportunity to characterize the biomechanical environment of the CSF system non-invasively. CFD modeling of CSF flow typically begins with a computer-aided design (CAD) model of the geometry of interest, either idealized or reconstructed from anatomic MRI, and flow data obtained from Phase Contrast (PC) MR techniques. Then, by utilizing the equations of motion for a fluid (Navier-Stokes equations) to numerically simulate CSF flow, key mechanical variables in the flow field such as pressure and fluid velocity, can be approximated with good accuracy in both space and time.  These models can then be validated against the real-life MRI measurements to confirm their results [10,11,21]. In addition, they provide details about CSF flow dynamics that cannot be directly measured from MRI.

An early CFD project to study CSF motion in the spinal SAS was conducted by Loth, et al. [42]. This study demonstrated that the flow field in an open spinal canal (no tonsillar or fine structure obstructions) may vary significantly with position in the craniocaudal direction and with position of the spinal cord relative to the subarachnoid boundary. A subsequent study demonstrated that fine structures in the spinal canal (trabeculae, nerve bundles, denticulate ligaments) do not significantly alter gross CSF flow patterns [34,37].  However, subsequent studies by others showed that spinal cord nerve roots [13,17,24] and neural tissue motion of the cardiac cycle [14] can impact the CSF flow field to a great degree.  Other studies also showed that microscopic structures (arachnoid trabeculae) can alter CSF fluid mixing and solute transport [13,30].  In a study conducted by Roldan, et al. [31], geometrically realistic models (one from the spinal canal of a CM patient, one from a healthy volunteer) were used to confirm the notion from the Loth study that CSF velocities in the spinal canal increase with position in the craniocaudal direction. Those velocity increases, in turn, caused increases in the corresponding CSF pressures, which drive the flow. From the same study, the numerically-determined flow field yielded velocity jetting patterns near the foramen magnum in the CM patient, which matched up well with PCMR data from other studies [31]. Linge, et al., produced similar results using a geometrically idealized model of the posterior cranial fossa and cervical spine [25,26].  A review of numerical modeling CSF flow studies focused on CM is provided by Shaffer et al. [24]. 

CSF Flow Analysis in Syringomyelia

Because CFD analysis is such a time-efficient means of analysis for simple flow geometries, such as the idealized spinal canal, it has also proven useful in the non-invasive analysis of CSF flow fields in post-traumatic SM (PTSM). A comprehensive review of studies investigating SM biomechanics is provided by Elliott et al. [20].  Bilston, et al, used a simplified model of the spinal canal to demonstrate that the presence of focal arachnoiditis, modeled as a porous medium, creates elevated pressure pulses in comparison to unobstructed spinal canal [23,33,38]. The studies hypothesized then that the elevated CSF pressure may be a significant factor in the propagation of the syrinx in PTSM.  Martin et al. conducted a series of in vitro model studies to investigate the pressure environment inside and outside the syrinx cavity and how a spinal stenosis and various maneuvers such as coughing could alter the pressure environment [27,29,41]. 

CSF Flow Analysis In Brain Ventricles and the Cranial Subarachnoid Space

CFD modeling is also being used to approximate flow fields in the ventricles of the brain and the cranial subarachnoid space. Initially, such models were used to show that CSF flow fields in the ventricles and cranial SAS could be obtained using CFD methods and, going forward, might prove to be useful in producing a coupled cranial-spinal CSF flow model [35,36,39,40]. One concern noted by the authors of these studies was the risk involved in decoupling the cranial CSF system from the spinal CSF system and vice versa, as anomalies in the approximated flow field (i.e. seemingly cryptic or random pressure or velocity fluctuations) may be difficult to justify only in the context of one half of the system. Those studies have also shown that it may be possible to drive CSF flow in a complete CSF system model using brain motion data obtained from MRI. Linninger et al. completed a 3D coupled model of intracranial and spinal CSF [4,9,13,32] and Martin et al. completed a simplified 1-D coupled model [22].  Further studies have used a similar complex modeling methodology to accurately introduce the compliant behavior of the brain, spinal cord, and subarachnoid membrane [28,30], which, again, may be critical in forming a complete systemic model of the CSF system, and to study the influence of CSF drainage into the lymphatic system on the pressure and flow environment in the cranial subarachnoid space. Both of the aforementioned Gupta studies and recent studies by others [3,5,6] may prove to be useful base models for non-invasively studying transport of metabolites and neuroendocrine substances in the CSF system, which may prove useful in the study of the interrelation of hydrocephalus (and perhaps CM) and dementia/Alzheimer’s disease.

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Reviewed 03/2018