16 research outputs found
Editorial: Cerebrospinal fluid dynamics and intracranial pressure elevation-Novel insights on molecular and physiological mechanisms, and implications for neurological disease
Human intracranial pulsatility during the cardiac cycle: a computational modelling framework
Background
Today’s availability of medical imaging and computational resources set the scene for high-fidelity computational modelling of brain biomechanics. The brain and its environment feature a dynamic and complex interplay between the tissue, blood, cerebrospinal fluid (CSF) and interstitial fluid (ISF). Here, we design a computational platform for modelling and simulation of intracranial dynamics, and assess the models’ validity in terms of clinically relevant indicators of brain pulsatility. Focusing on the dynamic interaction between tissue motion and ISF/CSF flow, we treat the pulsatile cerebral blood flow as a prescribed input of the model.
Methods
We develop finite element models of cardiac-induced fully coupled pulsatile CSF flow and tissue motion in the human brain environment. The three-dimensional model geometry is derived from magnetic resonance images (MRI) and features a high level of detail including the brain tissue, the ventricular system, and the cranial subarachnoid space (SAS). We model the brain parenchyma at the organ-scale as an elastic medium permeated by an extracellular fluid network and describe flow of CSF in the SAS and ventricles as viscous fluid movement. Representing vascular expansion during the cardiac cycle, a prescribed pulsatile net blood flow distributed over the brain parenchyma acts as the driver of motion. Additionally, we investigate the effect of model variations on a set of clinically relevant quantities of interest.
Results
Our model predicts a complex interplay between the CSF-filled spaces and poroelastic parenchyma in terms of ICP, CSF flow, and parenchymal displacements. Variations in the ICP are dominated by their temporal amplitude, but with small spatial variations in both the CSF-filled spaces and the parenchyma. Induced by ICP differences, we find substantial ventricular and cranial-spinal CSF flow, some flow in the cranial SAS, and small pulsatile ISF velocities in the brain parenchyma. Moreover, the model predicts a funnel-shaped deformation of parenchymal tissue in dorsal direction at the beginning of the cardiac cycle.
Conclusions
Our model accurately depicts the complex interplay of ICP, CSF flow and brain tissue movement and is well-aligned with clinical observations. It offers a qualitative and quantitative platform for detailed investigation of coupled intracranial dynamics and interplay, both under physiological and pathophysiological conditions.publishedVersio
Brain solute transport is more rapid in periarterial than perivenous spaces
Fluid flow in perivascular spaces is recognized as a key component underlying brain transport and clearance. An important open question is how and to what extent differences in vessel type or geometry affect perivascular fluid flow and transport. Using computational modelling in both idealized and image-based geometries, we study and compare fluid flow and solute transport in pial (surface) periarterial and perivenous spaces. Our findings demonstrate that differences in geometry between arterial and venous pial perivascular spaces (PVSs) lead to higher net CSF flow, more rapid tracer transport and earlier arrival times of injected tracers in periarterial spaces compared to perivenous spaces. These findings can explain the experimentally observed rapid appearance of tracers around arteries, and the delayed appearance around veins without the need of a circulation through the parenchyma, but rather by direct transport along the PVSs.publishedVersio
CSF circulation and dispersion yield rapid clearance from intracranial compartments
In this paper, we used a computational model to estimate the clearance of a tracer driven by the circulation of cerebrospinal fluid (CSF) produced in the choroid plexus (CP) located within the lateral ventricles. CSF was assumed to exit the subarachnoid space (SAS) via different outflow routes such as the parasagittal dura, cribriform plate, and/or meningeal lymphatics. We also modelled a reverse case where fluid was produced within the spinal canal and absorbed in the choroid plexus in line with observations on certain iNPH patients. No directional interstitial fluid flow was assumed within the brain parenchyma. Tracers were injected into the foramen magnum. The models demonstrate that convection in the subarachnoid space yields rapid clearance from both the SAS and the brain interstitial fluid and can speed up intracranial clearance from years, as would be the case for purely diffusive transport, to days.publishedVersio
Simulating Cerebrospinal Fluid Flow and Spinal Cord Movement Associated with Syringomyelia
Syringomyelia is a progressive disease where fluid filled cavities develop inside the spinal cord, and is frequently seen together with Chiari Malformation I (CMI). CMI is characterized by downwards displacements of the Cerebellar Tonsils obstructing flow in the Subarachnoid space, (SAS) which causes abnormal Cerebrospinal fluid (CSF) flow. Many theories on the pathogenesis of syringomyelia have been proposed, many related to abnormal CSF flow, but a full explanation has not yet been given. In this study we formulate a monolithic mixed finite element formulation to investigate fluid structure interaction (FSI) effects of syringomyelia in idealized geometries of the spinal cord and SAS. Models are implemented with the FEniCS software in Python. Elastic and poroelastic representations of the spinal cord are investigated and compared to each other. We tested the hypothesis that fluid velocities within the syrinx can be explained by FSI or poroelasticity, and that these effects alter CSF dynamics. Our results indicate that FSI and poroelastic approaches yield the same results as rigid wall Computational Fluid Dynamics in healthy subjects. In the presence of a syrinx, greater displacements of the cord are predicted. A Poroelastic representation of the spinal cord added substantial damping of the pressure wave inducing syrinx velocity, and thus lower syrinx velocities were seen in these models
Multi-compartmental model of glymphatic clearance of solutes in brain tissue.
The glymphatic system is the subject of numerous pieces of research in biology. Mathematical modelling plays a considerable role in this field since it can indicate the possible physical effects of this system and validate the biologists' hypotheses. The available mathematical models that describe the system at the scale of the brain (i.e. the macroscopic scale) are often solely based on the diffusion equation and do not consider the fine structures formed by the perivascular spaces. We therefore propose a mathematical model representing the time and space evolution of a mixture flowing through multiple compartments of the brain. We adopt a macroscopic point of view in which the compartments are all present at any point in space. The equations system is composed of two coupled equations for each compartment: One equation for the pressure of a fluid and one for the mass concentration of a solute. The fluid and solute can move from one compartment to another according to certain membrane conditions modelled by transfer functions. We propose to apply this new modelling framework to the clearance of 14C-inulin from the rat brain
Multi-compartmental model of glymphatic clearance of solutes in brain tissue
The Glymphatic system is the subject of numerous pieces of research in Biology. Mathematical modeling plays a considerable role in this field since it can indicate the possible physical effects in this system and validate the biologists' hypotheses. The available mathematical models that describe the system at the scale of the brain (i.e. the macroscopic scale) are often solely based on the diffusion equation and do not consider the fine structures formed by the perivascular spaces. We therefore propose a mathematical model representing the time and space evolution of a mixture flowing through multiple compartments of the brain. We adopt a macroscopic point of view in which the compartments are all present at any point in space. The equations system is composed of two coupled equations for each compartment: One equation for the pressure of a fluid and one for the mass concentration of a molecule. The fluid and solute can move from one compartment to another according to certain membrane conditions modeled by transfer functions. We propose to apply this new modeling framework to the clearance of 14 C-inulin from the rat brain
Correction to: Estimates of the permeability of extra-cellular pathways through the astrocyte endfoot sheath
Estimates of the permeability of extra-cellular pathways through the astrocyte endfoot sheath
Abstract Background Astrocyte endfoot processes are believed to cover all micro-vessels in the brain cortex and may play a significant role in fluid and substance transport into and out of the brain parenchyma. Detailed fluid mechanical models of diffusive and advective transport in the brain are promising tools to investigate theories of transport. Methods We derive theoretical estimates of astrocyte endfoot sheath permeability for advective and diffusive transport and its variation in microvascular networks from mouse brain cortex. The networks are based on recently published experimental data and generated endfoot patterns are based on Voronoi tessellations of the perivascular surface. We estimate corrections for projection errors in previously published data. Results We provide structural-functional relationships between vessel radius and resistance that can be directly used in flow and transport simulations. We estimate endfoot sheath filtration coefficients in the range L p = 2 × 10 - 11 m Pa - 1 s - 1 to 3 × 10 - 10 m Pa - 1 s - 1 , diffusion membrane coefficients for small solutes in the range C M = 5 × 10 2 m - 1 to 6 × 10 3 m - 1 , and gap area fractions in the range 0.2–0.6%, based on a inter-endfoot gap width of 20 nm. Conclusions The astrocyte endfoot sheath surrounding microvessels forms a secondary barrier to extra-cellular transport, separating the extra-cellular space of the parenchyma and the perivascular space outside the endothelial layer. The filtration and membrane diffusion coefficients of the endfoot sheath are estimated to be an order of magnitude lower than those of the extra-cellular matrix while being two orders of magnitude higher than those of the vessel wall