Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique

Area of Science:

• Biomedical Engineering
• Computational Fluid Dynamics
• Medical Imaging

Background:

• Simulating blood flow around endovascular devices (coils, stents) presents geometric challenges.
• Traditional computational fluid dynamics (CFD) methods struggle with patient-specific modeling of cerebral aneurysm treatments due to complex grid generation.

Purpose of the Study:

• To apply an adaptive grid embedding technique for simulating blood flow around endovascular devices.
• To overcome the limitations of traditional CFD in patient-specific modeling of endovascular procedures.

Main Methods:

• A hybrid approach combining body-conforming grids for vessel walls and adaptive mesh embedding for endovascular devices.
• Utilizing image-based computational fluid dynamics for patient-specific modeling.

Main Results:

• Successfully applied adaptive grid embedding to simulate blood flow around endovascular devices.
• Developed a hybrid methodology for improved CFD simulations in endovascular applications.

Conclusions:

• The adaptive mesh embedding technique offers a viable solution for simulating blood flow around complex endovascular devices.
• This methodology facilitates personalized endovascular procedures and exploration of therapeutic options.