ABSTRACT

Carotid stenosis is the narrowing of the carotid artery. This can cause a blood clot and a potential stroke.

The purpose of this project was to determine factors that may help in predicting the likelihood of patients with carotid stenosis experiencing a stroke. This was done by creating patient models of stroke and non-stroke patients and determining factors that are different between them. Through an image-based simulation software, Simvascular, 14 models were created by building a path, segmenting arterial walls and meshing them for an accurate representation of the artery. Simulations were created and uploaded to a supercomputer to be run. The simulation files were transferred to Paraview software for data analysis. Clips of various regions of the artery and its factors such as velocity, shear stress, etc were collected for analysis. After obtaining data in each of these regions, a two sided t-test was used to see if the differences were statistically significant. The analysis indicated that stroke patients have a higher mean velocity in the external carotid artery than non stroke patients. This data can be further analyzed and used as a diagnostic factor for stroke in patients with carotid stenosis.