Variations associated with stenting systems, artery properties, and doctor skills necessitate a better understanding of coronary artery stents so as to facilitate the design of stents that are customized to individual patients. This paper presents the development of an integrated computer simulation-based design approach using engineering finite element analysis (FEA) models for capturing stent knowledge, utility theory-based decision models for representing the design preferences, and statistics-based surrogate models for improving process efficiency. Two focuses of the paper are: 1) understanding the significance of engineering analysis and surrogate models in the simulation-based design of medical devices; 2) investigating the modeling implications in the context of stent design. The study reveals that the advanced nonlinear FEA software with analysis capacities on large deformation and contact interaction has offered a platform to execute high fidelity simulations, yet the selection of appropriate analysis models is still subject to the tradeoff between cost of analysis and accuracy of solution; the cost-prohibitive simulations necessitate the employment of surrogate models in subsequent multi-objective design optimization. A detailed comparison between regression models and Kriging models suggests the importance of sampling schemes in successfully implementing Kriging methods.

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