Atherosclerosis is a vascular degenerative disease leading to progressive thickening in the intima of large and medium sized arteries through the formation of plaque that is very rich with cholesterol. The cholesterol is carried by LDL (low density lipoprotein) particles which pass through the endothelium and accumulate in the intima. The passage of LDL is influenced by wall shear stress which activates physiological responses of the endothelium. However, the causal relationship between the physiological responses and their effect on LDL mass transport is not fully understood. To obtain blood flow patterns in human carotid arteries, a fluid structure interaction (FSI) computational approach is employed, based on the in-vivo arterial geometry constructed from black blood magnetic resonance images (BBMRI) and flow rate boundary conditions obtained from phase contrast images (PC). Wall shear stress (WSS) on the luminal surface is computed, and this variable is related to the formation of leaky junctions, which is a major transendothelial pathway for LDL. A model for the fraction of leaky junction at a surface is incorporated into the overall computational scheme for mass transport, along with pore theory.
The theoretical model is applied to images from three human carotid arteries in which the degree of disease ranges from mild to moderate. Maximum mass flux is predicted to be in the downstream region of stenoses where WSS is low, and this result is consistent with the clinical observation of plaque progression downstream of the stenosis. The hypothesis that the majority of LDL enters into the intima through leaky junctions is supported by observation of similar distributions between the pattern of volume flux via leaky junctions and mass flux. These studies suggest that mass flux of LDL can be a predictor to indicate areas with potential for plaque formation and progression in human carotid artery disease.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/41192 |
| Date | 06 July 2011 |
| Creators | Kim, Sungho |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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