2D Computational Fluid Dynamic Modeling of Human Ventricle System Based on Fluid-Solid Interaction and Pulsatile...

Area of Science:

• Biomedical Engineering
• Fluid Dynamics
• Neuroscience

Background:

• Cerebrospinal fluid (CSF) hydrodynamics are linked to numerous diseases.
• Understanding CSF flow and intracranial pressure is crucial for disease pathology and treatment.
• Computational methods are vital for developing in vitro models for drug discovery.

Purpose of the Study:

• To develop and validate a computational fluid-solid interaction (FSI) model for simulating CSF flow.
• To investigate the phenomenon of diastolic backflow in CSF circulation.
• To evaluate the impact of brain tissue elasticity on CSF hydrodynamics.

Main Methods:

• A Fluid-Solid Interaction (FSI) model was constructed to simulate CSF flow.
• Both rigid and flexible conditions for the ventricular system were used to assess brain tissue effects.
• The model incorporated an elastic ventricular wall and pulsatile CSF input as boundary conditions.

Main Results:

• The flexible model successfully reproduced diastolic backflow, a phenomenon observed in clinical studies.
• Rigid models failed to capture diastolic backflow due to neglecting brain parenchyma interaction.
• Computational fluid dynamic (CFD) analysis showed CSF pressure and flow velocity concordant with experimental data.

Conclusions:

• Flexible computational models are superior for accurately simulating CSF hydrodynamics, including diastolic backflow.
• Accounting for brain tissue interaction is essential for realistic CSF flow modeling.
• This FSI approach provides a reliable method for in vitro CSF studies and potential drug development.