Meshing Algorithms for Use in Cardiovascular Computational Simulations


Seminar

Date

Time

11:00 a.m.

Location

MRB 202 Conference Room

Presenter

Dr. Suzanne M. Shontz (Electrical Engineering and Computer Science & Bioengineering Program, University of Kansas)

Abstract

Generation of patient-specific models and meshes is important for accurate and efficient computational simulations of disease progression and of medical device effectiveness.  Many biomedical applications involve movement by the patient and medical device and require dynamic meshes for use in associated image-based computational simulations.  An important example of such an application is prediction of the appropriate surgical treatment for blood clot entrapment by inferior vena cava (IVC) filters.  Other biomedical applications include curved geometry and can be represented most accurately by high-order meshes with curvilinear elements.  Such meshes lead to more efficient computational simulations when coupled with high-order partial differential equation solvers.  An important example of when such meshes are appropriate is when generating meshes of the cardiac anatomy for use in computational simulations used to predict diseased regions of the heart due to a cardiac arrhythmia.  Such simulations may be useful to doctors when performing cardiac ablation surgeries on atrial fibrillation patients.

In the first part of my talk, I will present a dynamic meshing technique for virtual implantation of an IVC filter in the venous anatomy of a patient with deep vein thrombosis.  The corresponding embedded geometric models are then used to generate meshes of the implanted medical device and venous anatomy for use in computational fluid dynamics simulations of the blood flow, and ultimately, to predict device performance.  

In the second part of my talk, I will describe a direct high-order curvilinear triangular mesh generation method.  The method has been used to generate meshes of the heart, brain, and lungs for use in biomedical computational simulations.  I will conclude by discussing our plans for future work related to generation of high-order meshes of cardiac anatomies and simulations of heart arrhythmias.  

Portions of this talk represent joint work with researchers at the Penn State, Penn State Hershey Medical Center, the University of Utah, Rochester Institute of Technology, and the University of Kansas.