Three-dimensional cerebrospinal fluid flow within the human ventricular system

Cerebrospinal fluid (CSF) is a Newtonian fluid and can, therefore, be modelled using computational fluid dynamics (CFD). Previous modelling of the CSF has been limited to simplified geometric models. This work describes a geometrically accurate three dimensional (3D) computational model of the human ventricular system (HVS) constructed from magnetic resonance images (MRI) of the human brain. It is an accurate and full representation of the HVS and includes appropriately positioned CSF production and drainage locations. It was used to investigate the pulsatile motion of CSF within the human brain. During this investigation CSF flow rate was set at a constant 500 ml/day, to mimic real life secretion of CSF into the system, and a pulsing velocity profile was added to the inlets to incorporate the effect of cardiac pulsations on the choroid plexus and their subsequent influence on CSF motion in the HVS. Boundary conditions for the CSF exits from the ventricles (foramina of Magendie and Lushka) were found using a “nesting” approach, in which a simplified model of the entire central nervous system (CNS) was used to examine the effects of the CSF surrounding the ventricular system (VS). This model provided time varying pressure data for the exits from the VS nested within it. The fastest flow was found in the cerebral aqueduct, where a maximum velocity of 11.38 mm/s was observed over five cycles. The maximum Reynolds number recorded during the simulation was 15 with an average Reynolds number of the order of 0.39, indicating that CSF motion is creeping flow in most of the computational domain and consequently will follow the geometry of the model. CSF pressure also varies with geometry with a maximum pressure drop of 1.14 Pa occurring through the cerebral aqueduct. CSF flow velocity is substantially slower in the areas that are furthest away from the inlets; in some areas flow is nearly stagnant.     

Three-dimensional cerebrospinal fluid flow within the human ventricular system

Cerebrospinal fluid (CSF) is a Newtonian fluid and can, therefore, be modelled using computational fluid dynamics (CFD). Previous modelling of the CSF has been limited to simplified geometric models. This work describes a geometrically accurate three dimensional (3D) computational model of the human ventricular system (HVS) constructed from magnetic resonance images (MRI) of the human brain. It is an accurate and full representation of the HVS and includes appropriately positioned CSF production and drainage locations. It was used to investigate the pulsatile motion of CSF within the human brain. During this investigation CSF flow rate was set at a constant 500 ml/day, to mimic real life secretion of CSF into the system, and a pulsing velocity profile was added to the inlets to incorporate the effect of cardiac pulsations on the choroid plexus and their subsequent influence on CSF motion in the HVS. Boundary conditions for the CSF exits from the ventricles (foramina of Magendie and Lushka) were found using a "nesting" approach, in which a simplified model of the entire central nervous system (CNS) was used to examine the effects of the CSF surrounding the ventricular system (VS). This model provided time varying pressure data for the exits from the VS nested within it. The fastest flow was found in the cerebral aqueduct, where a maximum velocity of 11.38 mm/s was observed over five cycles. The maximum Reynolds number recorded during the simulation was 15 with an average Reynolds number of the order of 0.39, indicating that CSF motion is creeping flow in most of the computational domain and consequently will follow the geometry of the model. CSF pressure also varies with geometry with a maximum pressure drop of 1.14 Pa occurring through the cerebral aqueduct. CSF flow velocity is substantially slower in the areas that are furthest away from the inlets; in some areas flow is nearly stagnant.     

Computational modeling of the mechanical behavior of the cerebrospinal fluid system

A computational fluid dynamics (CFD) model of the cerebrospinal fluid system was constructed based on a simplified geometry of the brain ventricles and their connecting pathways. The flow is driven by a prescribed sinusoidal motion of the third ventricle lateral walls, with all other boundaries being rigid. The pressure propagation between the third and lateral ventricles was examined and compared to data obtained from a similar geometry with a stenosed aqueduct. It could be shown that the pressure amplitude in the lateral ventricles increases in the presence of aqueduct stenosis. No difference in phase shift between the motion of the third ventricle walls and the pressure in the lateral ventricles because of the aqueduct stenosis could be observed. It is deduced that CFD can be used to analyze the pressure propagation and its phase shift relative to the ventricle wall motion. It is further deduced that only models that take into account the coupling between ventricles, which feature a representation of the original geometry that is as accurate as possible and which represent the ventricle boundary motion realistically, should be used to make quantitative statements on flow and pressure in the ventricular space.     

Reduction of PrPC in human cerebrospinal fluid after spinal cord injury

It has been estimated that cerebrospinal fluid (CS F) contains approximately 80 proteins that significantly increase or decrease in response to various clinical conditions. Here we have evaluated the CS F protein PrP^C (cellular prion protein) for possible increases or decreases following spinal cord injury. The physiological function of PrP^C is not yet completely understood; however, recent findings suggest that PrP^C may have neuroprotective properties. Our results show that CS F PrP^C is decreased in spinal cord injured patients 12 h following injury and is absent at 7 days. Given that normal PrP^C has been proposed to be neuroprotective, we speculate that the decrease in CS F PrP^C levels may influence neuronal cell survival following spinal cord injury.Key words: CSF, PrP^C, Hsp25, crystallin domain, spinal cord injury     

The effect of cerebrospinal fluid thickness on traumatic spinal cord deformation

A spinal cord injury may lead to loss of motor and sensory function and even death. The biomechanics of the injury process have been found to be important to the neurological damage pattern, and some studies have found a protective effect of the cerebrospinal fluid (CSF). However, the effect of the CSF thickness on the cord deformation and, hence, the resulting injury has not been previously investigated. In this study, the effects of natural variability (in bovine) as well as the difference between bovine and human spinal canal dimensions on spinal cord deformation were studied using a previously validated computational model. Owing to the pronounced effect that the CSF thickness was found to have on the biomechanics of the cord deformation, it can be concluded that results from animal models may be affected by the disparities in the CSF layer thickness as well as by any difference in the biological responses they may have compared with those of humans.     

Biomarkers for severity of spinal cord injury in the cerebrospinal fluid of rats

One of the major challenges in management of spinal cord injury (SCI) is that the assessment of injury severity is often imprecise. Identification of reliable, easily quantifiable biomarkers that delineate the severity of the initial injury and that have prognostic value for the degree of functional recovery would significantly aid the clinician in the choice of potential treatments. To find such biomarkers we performed quantitative liquid chromatography-mass spectrometry (LC-MS/MS) analyses of cerebrospinal fluid (CSF) collected from rats 24 h after either a moderate or severe SCI. We identified a panel of 42 putative biomarkers of SCI, 10 of which represent potential biomarkers of SCI severity. Three of the candidate biomarkers, Ywhaz, Itih4, and Gpx3 were also validated by Western blot in a biological replicate of the injury. The putative biomarkers identified in this study may potentially be a valuable tool in the assessment of the extent of spinal cord damage.     

Investigation on cerebrospinal fluid opioids and neurotransmitters related to spinal cord stimulation

The purpose of this study was to assess the biochemical mechanisms underlying spinal cord stimulation (SCS). Seventeen patients with chronic pain were investigated by measuring cerebrospinal fluid concentrations of endogenous opioids and biogenic amines before and during dorsal column stimulation. Basal cerebrospinal fluid beta-endorphin levels were below the normal range. No significant change of norepinephrine, epinephrine, dopamine, beta-endorphin, beta-lipotropin, or adrenocorticotropic hormone levels were found after SCS. A 50% increase of cerebrospinal beta-endorphin and beta-lipotropin levels occurred in 6 out of 16 patients, namely those where SCS gave the major pain relief. These data confirm the derangement of the endogenous opioid system in chronic pain conditions and suggest that the beta-endorphin response to SCS could have clinical value in predicting the success of treatment.     

Syrinx fluid transport: modeling pressure-wave-induced flux across the spinal pial membrane

Syrinxes are fluid-filled cavities of the spinal cord that characterize syringomyelia, a disease involving neurological damage. Their formation and expansion is poorly understood, which has hindered successful treatment. Syrinx cavities are hydraulically connected with the spinal subarachnoid space (SSS) enveloping the spinal cord via the cord interstitium and the network of perivascular spaces (PVSs), which surround blood vessels penetrating the pial membrane that is adherent to the cord surface. Since the spinal canal supports pressure wave propagation, it has been hypothesized that wave-induced fluid exchange across the pial membrane may play a role in syrinx filling. To investigate this conjecture a pair of one-dimensional (1-d) analytical models were developed from classical elastic tube theory coupled with Darcy's law for either perivascular or interstitial flow. The results show that transpial flux serves as a mechanism for damping pressure waves by alleviating hoop stress in the pial membrane. The timescale ratio over which viscous and inertial forces compete was explicitly determined, which predicts that dilated PVS, SSS flow obstructions, and a stiffer and thicker pial membrane-all associated with syringomyelia-will increase transpial flux and retard wave travel. It was also revealed that the propagation of a pressure wave is aided by a less-permeable pial membrane and, in contrast, by a more-permeable spinal cord. This is the first modeling of the spinal canal to include both pressure-wave propagation along the spinal axis and a pathway for fluid to enter and leave the cord, which provides an analytical foundation from which to approach the full poroelastic problem.     

Three dimensional modeling of the cerebrospinal fluid dynamics and brain interactions in the aqueduct of sylvius

A computational fluid dynamics (CFD) method is presented to investigate the flow of cerebro-spinal fluid (CSF) in the cerebral aqueduct. In addition to former approaches exhibiting a rigid geometry, we propose a model which includes a deformable membrane as the wall of this flow channel. An anatomical shape of the aqueduct was computed from magnetic resonance images (MRI) and the resulting meshing was immersed in a marker-and-cell (MAC) staggered grid for to take into account fluid-structure interactions. The time derivatives were digitized using the Crank-Nicolson scheme. The equation of continuity was modified by introducing an artificial compressibility and digitized by a finite difference scheme. Calculations were validated with the simulation of laminar flow in a rigid tube. Then, comparisons were made between simulations of a rigid aqueduct and a deformable one. We found that the deformability of the walls has a strong influence on the pressure drop for a given flow.     

Effect of anatomical fine structure on the flow of cerebrospinal fluid in the spinal subarachnoid space

The lattice Boltzmann method is used to model oscillatory flow in the spinal subarachnoid space. The effect of obstacles such as trabeculae, nerve bundles, and ligaments on fluid velocity profiles appears to be small, when the flow is averaged over the length of a vertebra. Averaged fluid flow in complex models is little different from flow in corresponding elliptical annular cavities. However, the obstacles stir the flow locally and may be more significant in studies of tracer dispersion.