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    Simplified Multistage Computational Approach to Assess the Fatigue Behavior of a Niti Transcatheter Aortic Valve During In Vitro Tests: A Proof-of-Concept Study

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    Date
    2017
    Author
    Petrini, Lorenza
    Dordoni, Elena
    Allegretti, Dario
    Pott, Desiree
    Kütting, Maximilian
    Migliavacca, Francesco
    Pennati, Giancarlo
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    Abstract
    Nowadays, transcatheter aortic valve (TAV) replacement is an alternative to surgical therapy in selected high risk patients for the treatment of aortic stenosis. However, left ventricular contraction determines a severe cyclic loading for the implanted stent-frame, undermining its long-term durability. Technical standards indicate in vitro tests as a suitable approach for the assessment of TAV fatigue behavior: generally, they do not specify test methods but require to test TAV in the worst loading conditions. The most critical conditions could be different according to the specific valve design, hence the compartment where deploying the valve has to be properly identified. A fast and reliable computational methodology could significantly help to face this issue. In this paper, a numerical approach to analyze Nickel-Titanium TAV stent-frame behavior during in vitro durability tests is proposed. A simplified multistage strategy was adopted where, in each stage, only two of the three involved components are considered. As a proof-of-concept, the method was applied to a TAV prototype. Despite its simplifications, the developed computational framework gave useful insights into the stent-frame failures behavior during a fatigue test. Numerical results agree with experimental findings. In particular, the most dangerous condition was identified among a number of experimental tests, where different compartments and pressure gradients were investigated. The specific failure location was also correctly recognized. In conclusion, the presented methodology provides a tool to support the choice of proper testing conditions for the in vitro assessment of TAV fatigue behavior.
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    http://138.201.223.254:8080/yetl1/handle/yetl/4235216
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