CSF Dynamics: Implications for Hydrocephalus and Glymphatic Clearance

Author:

Bissenas Ashley,Fleeting Chance,Patel Drashti,Al-Bahou Raja,Patel Aashay,Nguyen Andrew,Woolridge Maxwell,Angelle Conner,Lucke-Wold Brandon

Abstract

Beyond its neuroprotective role, CSF functions to rid the brain of toxic waste products through glymphatic clearance. Disturbances in the circulation of CSF and glymphatic exchange are common among those experiencing HCP syndrome, which often results from SAH. Normally, the secretion of CSF follows a two-step process, including filtration of plasma followed by the introduction of ions, bicarbonate, and water. Arachnoid granulations are the main site of CSF absorption, although there are other influencing factors that affect this process. The pathway through which CSF is through to flow is from its site of secretion, at the choroid plexus, to its site of absorption. However, the CSF flow dynamics are influenced by the cardiovascular system and interactions between CSF and CNS anatomy. One, two, and three-dimensional models are currently methods researchers use to predict and describe CSF flow, both under normal and pathological conditions. They are, however, not without their limitations. “Rest-of-body” models, which consider whole-body compartments, may be more effective for understanding the disruption to CSF flow due to hemorrhages and hydrocephalus. Specifically, SAH is thought to prevent CSF flow into the basal cistern and paravascular spaces. It is also more subject to backflow, caused by the presence of coagulation cascade products. In regard to the fluid dynamics of CSF, scar tissue, red blood cells, and protein content resulting from SAH may contribute to increased viscosity, decreased vessel diameter, and increased vessel resistance. Outside of its direct influence on CSF flow, SAH may result in one or both forms of hydrocephalus, including noncommunicating (obstructive) and communicating (nonobstructive) HCP. Imaging modalities such as PC-MRI, Time-SLIP, and CFD model, a mathematical model relying on PC-MRI data, are commonly used to better understand CSF flow. While PC-MRI utilizes phase shift data to ultimately determine CSF speed and flow, Time-SLIP compares signals generated by CSF to background signals to characterizes complex fluid dynamics. Currently, there are gaps in sufficient CSF flow models and imaging modalities. A prospective area of study includes generation of models that consider “rest-of-body” compartments and elements like arterial pulse waves, respiratory waves, posture, and jugular venous posture. Going forward, imaging modalities should work to focus more on patients in nature in order to appropriately assess how CSF flow is disrupted in SAH and HCP.

Publisher

Aurora Publishing House Limited

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