Predicting the Aqueductal Cerebrospinal Fluid Pulse: A Statistical Approach

Abstract

The cerebrospinal fluid (CSF) pulse in the Aqueduct of Sylvius (aCSF pulse) is often used to evaluate structural changes in the brain. Here we present a novel application of the general linear model (GLM) to predict the motion of the aCSF pulse. MR venography was performed on 13 healthy adults (9 female and 4 males—mean age = 33.2 years). Flow data was acquired from the arterial, venous and CSF vessels in the neck (C2/C3 level) and from the AoS. Regression analysis was undertaken to predict the motion of the aCSF pulse using the cervical flow rates as predictor variables. The relative contribution of these variables to predicting aCSF flow rate was assessed using a relative weights method, coupled with an ANOVA. Analysis revealed that the aCSF pulse could be accurately predicted (mean (SD) adjusted r2 = 0.794 (0.184)) using the GLM (p < 0.01). Venous flow rate in the neck was the strongest predictor of aCSF pulse (p = 0.001). In healthy individuals, the motion of the aCSF pulse can be predicted using the GLM. This indicates that the intracranial fluidic system has broadly linear characteristics. Venous flow in the neck is the strongest predictor of the aCSF pulse.