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In Silico Modelling of Aortic Valve Implants – Predicting In Vitro Performance using Finite Element Analysis
- Publication Year :
- 2021
- Publisher :
- Open Engineering Inc, 2021.
-
Abstract
- The competing structural and hemodynamic considerations in valve design generally require a large amount of in vitro hydrodynamic and durability testing during development, often resulting in inefficient “trial-and-error” prototyping. While in silico modelling through Finite Element Analysis (FEA) has been widely used to inform valve design by optimizing structural performance, few studies have exploited the potential insight FEA could provide into critical hemodynamic performance characteristics of the valve. The objective of this study is to demonstrate the potential of FEA to predict the hydrodynamic performance of aortic valve implants obtained during development through in vitro testing. Several variations of surgical tri-leaflet aortic valves were de-signed and manufactured using a synthetic polymer and hydrodynamic testing carried out using a pulsatile flow rig according to ISO 5840, with bulk hydro-dynamic parameters measured. In silico models were developed in tandem and suitable surrogate measures were investigated as predictors of the hydro-dynamic parameters. Through regression analysis, the in silico parameters of leaflet coaptation area, geometric orifice area and opening pressure were found to be suitable indicators of experimental in vitro hydrodynamic param-eters: regurgitant fraction, effective orifice area and transvalvular pressure drop performance, respectively.
- Subjects :
- engrXiv|Engineering
engrXiv|Engineering|Biomedical Engineering and Bioengineering
bepress|Engineering
engrXiv|Engineering|Biomedical Engineering and Bioengineering|Biomedical Devices and Instrumentation
bepress|Engineering|Biomedical Engineering and Bioengineering
bepress|Engineering|Biomedical Engineering and Bioengineering|Biomedical Devices and Instrumentation
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....4c1be687bcd0b86a3d29c8060209a3f1
- Full Text :
- https://doi.org/10.31224/osf.io/nzqu2