| Summary: | As life expectancy increases, there are more and more cases of age-related disease presenting to medical attention. Aortic stenosis (AS) is a common age-related heart condition in which there is a thickening and distortion of the valve leaflets together with calcium deposition in the aortic root and valve. Surgical valve replacement (SVR) of the calcified valve is the current default treatment for AS. However, due to the invasive nature of the procedure, a large population of patients are deemed too high risk to undergo SVR. Transcatheter aortic valve implantation (TAVI) was developed as a percutaneous alternative to SVR. TAVI is a purely mechanical process beyond the initial positioning of the device, that is, there is no decision making. As a result it can be computationally modelled using finite element analysis (FEA). This thesis describes how FEA has been used to analyse the stresses within the prosthetic leaflets during and post-deployment. Further, the application of patient-specific deployment simulation for predicting adverse effects post TAVI was explored. FEA simulation of TAVI deployment is challenging as a realistic aortic root model must be developed. This was accomplished by extracting data from patient specific medical images. The TAVI device itself, in particular the leaflets, are subjected to elevated stresses and deformation during deployment. Creating an FEA model robust enough to withstand the deployment process was achieved by modelling the leaflets in a planar orientation, then using a preliminary simulation to manipulate the leaflets into a functional position while maintaining a highly regular mesh. The key findings in this thesis concern device orientation and how it influences the operating stress of the valve. Sub-optimal device orientation can result in an average stress increase of 25%, which could potentially reduce the lifespan of the device. Patient-specific deployment simulations were also shown to have application outside of device orientation assessment as regions of potential paravalvular aortic regurgitation were identifiable.
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