Three-dimensional computational prediction of cerebrospinal fluid flow in the human brain

Abstract

A three-dimensional model of the human cerebrospinal fluid (CSF) spaces is presented. Patient-specific brain geometries were reconstructed from magnetic resonance images. The model was validated by comparing the predicted flow rates with Cine phase-contrast MRI measurements. The model predicts the complex CSF flow patterns and pressures in the ventricular system and subarachnoid space of a normal subject. The predicted maximum rostral to caudal CSF flow in the pontine cistern precedes the maximum rostral to caudal flow in the ventricles by about 10% of the cardiac cycle. This prediction is in excellent agreement with the subject-specific flow data. The computational results quantify normal intracranial dynamics and provide a basis for analyzing diseased intracranial dynamics.