Title:
Fluid Dynamics Assessment of Transcatheter Aortic Valve Replacement Performance

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Author(s)
Ncho, Beatrice Enanga Eya
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Yoganathan, Ajit P.
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Abstract
Transcatheter aortic valve replacement (TAVR) an alternative therapy to standardized surgical aortic valve replacement (SAVR) in the treatment of severe symptomatic aortic stenosis has evolved greatly in the last decade based on results from successful clinical trials. These trials revealed evidence of equivalence or superiority of TAVR to SAVR in low, intermediate, or high surgical risk patients, and these results have led to an expansion of TAVR guideline recommendations to accommodate more patients. The long-term success of this therapy is however threatened by some complications, one of which is leaflet thrombosis. In clinical practice, leaflet thrombosis has reported incidence rates ranging from 4.5 to 40% in different study populations. Although its causes are not clearly defined, studies indicate a combination of the TAV device, intra-procedural, and patient anatomical factors contribute to its occurrence. Mechanistic studies revealed that the unique ‘neo-sinus’ created by the device, patient anatomy, and the local flow characteristics surrounding the device are critical to the development of thrombosis. In addition, patient-specific flow studies confirmed a predictive link between neo-sinus flow stasis and severity of TAV leaflet thrombosis. The work presented in this dissertation aims to provide an improved understanding of the flow characteristics within the TAV neo-sinus and its surrounding, and elucidate device specific factors, and intra-procedural strategies that may contribute to minimizing flow stasis and reducing the risk of leaflet thrombosis. The flow phenomena will be quantified using two-dimensional particle image velocimetry techniques. Findings will promote the development of improved next generation valve replacement devices and provide support for intra-procedural strategies that could minimize flow stasis. Additionally, the experimental data will provide a reliable database necessary for verification and validation of computational simulations.
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Date Issued
2021-05-01
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Dissertation
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