In coronary artery disease, surgical revascularization using venous bypass grafts is performed to relieve symptoms and prolong life. Coronary bypass graft surgery is performed on approximately 500,000 people every year in the United States, with graft failure rates as high as 50% within 5 years. When a vein graft is implanted in the arterial system it adapts to the high flow rate and high pressure of the arterial environment by changing composition and geometry. Hemodynamics is known to play an active role in growth and remodeling of blood vessels but the complete underlying mechanism of vein graft failure is not well understood. Experiments required to understand this phenomenon can be resource and time intensive. In order to augment the existing knowledge and to guide design and interpretation of experiments that are needed to refine our understanding of vein graft growth and remodeling, computational models of vascular growth and remodeling are used to describe and predict the response of vein grafts to changes in hemodynamic loads. Computational models of growth and remodeling have numerous parameters, and even the inputs from experiments have uncertainties associated with them. There is therefore a need for a systematic approach to estimate the parameters included in growth and remodeling models and to evaluate sensitivity of the quantities of interest to parametric variations.

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