The Development of a Computational Test-Bed to Assess Coronary Stent Implantation
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The implantation behaviour of coronary stents is of great interest to clinicians and engineers alike as in-stent restenosis (ISR) remains a critical issue with the community. ISR is hypothesized to occur for reasons that include injury to the vessel wall caused by stent placement. To reduce the incidence of ISR, improved design and testing of coronary stents is needed. This research aims to facilitate more comprehensive evaluation of stents in the design phase, by generating more realistic arterial environments and corresponding stress states than have been considered heretofore, as a step towards reducing the prevalence of ISR. Furthermore, it proposes improvements to the current requirements for coronary stent computational stress analyses as set out by the Food and Drug Administration (FDA). A systematic geometric test-bed with varying levels of arterial curvature and stenosis severity is developed and used to evaluate the implantation behaviour of two stent designs using finite element analysis. A parameter study on atherosclerotic tissue behaviour is also carried out. Results are analysed using tissue damage estimates and lumen gain comparisons for each design. Results indicate that stent design does not have a major impact on lumen gain behaviour but may have an influence on the potential for tissue damage. The level of stenosis in the arterial segments is seen to have a strong impact on the results while the effects of arterial curvature appear to be design dependent. The greatest variable in any stenting analysis is the representation of the atherosclerotic tissue and this was the focus of the second phase of work. This research explores the direct stenting technique versus the predilation technique, the effects of variation of the material model for the atherosclerotic tissue matrix, the effects of inclusion of calcifications and a lipid pool and finally the effects of inclusion of the Mullins effect on the atherosclerotic tissue matrix in stenting applications. One major finding is that the stiffness of the base elasticity model and the strength of the tissue are key parameters in these analyses. In conclusion, the use of finite element modeling in this thesis to assess the biomechanics of coronary stent implantation has yielded the development of a novel computational test-bed. This work has generated considerable new insight into the mechanics of coronary stenting, and has created the basis for more effective and efficient stent design in the future.
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