Numerical simulation and fast method for the 0D-1D multi-scale coupled model and its application in ischemic brain...

Area of Science:

• Biomedical Engineering
• Computational Fluid Dynamics
• Neuroscience

Background:

• Rising living standards increase focus on cerebral blood flow issues like thrombosis and infarction.
• Accurate simulation of cerebral blood flow is vital for understanding and treating these conditions.
• Microcirculation in ischemic brain tissue presents complex modeling challenges.

Purpose of the Study:

• To develop and validate a 0D-1D geometric multi-scale coupled model for simulating microcirculatory blood flow in ischemic brain tissue.
• To improve the accuracy and computational efficiency of cerebral blood flow simulations.
• To analyze the effects of reduced vascular compliance and stenosis on intracranial pressure and blood flow.

Main Methods:

• Employed a 0D-1D geometric multi-scale coupled model.
• Utilized a numerical method combining the finite element method and the third-order Runge-Kutta method.
• Introduced a fast, reduced-order extrapolation algorithm for enhanced computational efficiency.

Main Results:

• The numerical method demonstrated stability and convergence accuracy.
• Significantly improved accuracy and efficiency in blood flow simulations.
• Illustrated variations in intracranial pressure and blood flow during a cardiac cycle.
• Showcased adverse effects of reduced vascular compliance and stenosis on cerebral hemodynamics.

Conclusions:

• The developed model and computational methods provide a robust tool for analyzing cerebral blood flow.
• Findings highlight the detrimental impact of vascular abnormalities on brain function and oxygen supply.
• The study enhances the accuracy of mechanism analysis for cerebrovascular diseases.