Title:
Computational optimization of transcatheter aortic valve leaflet design
Computational optimization of transcatheter aortic valve leaflet design
Author(s)
Murdock, Kyle
Advisor(s)
Sun, Wei
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Abstract
Transcatheter aortic valve (TAV) replacement is now the standard of care treatment for aortic stenosis in high-risk patients. There has been a recent push in the industry to develop smaller profile TAVs to make this treatment a safe and effective alternative to valve surgery in an even wider spectrum of patients. Smaller devices requiring thinner leaflets may come with the tradeoff of reduced durability. However, the impacts of different TAV leaflet materials and valve designs on TAV function and durability, particularly under non-ideal deployment conditions, have not been thoroughly assessed. By combining material modeling and geometric parameterization of valve leaflets, performance and safety of TAV devices can be comprehensively evaluated. The objectives of this study were to employ constitutive modeling tools to describe the material properties of pericardial tissues, and then to implement them in the development of a computational framework for exploring the impacts of leaflet material and design on TAV function. The mechanical properties of pericardial tissue have not been well characterized, particularly under flexure, which is an important mode of deformation for native and bioprosthetic heart valves. Pericardia material models were implemented in finite element simulations of valve deformation and directly compared. The impact of TAV leaflet material and geometry on mechanical stress was closely examined and fundamental relationships between design characteristics and leaflet deformation were established. Eccentric TAV expansion was modeled and optimization tools were employed to identify leaflet geometries which minimize stress during mechanical loading to increase durability. The results from these studies may offer scientific rationale for the design of durable and robust next-generation TAV devices.
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Date Issued
2016-07-21
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Resource Type
Text
Resource Subtype
Thesis