Conference paper Open Access

Non-parametric statistical shape modelling for in silico trials of TAVI

Verstraeten, Sabine; Suasso de Lima de Prado, Damián; Hoeijmakers, Martijn; Van de Vosse, Frans; Huberts, Wouter

In silico clinical trials are a promising method to increase efficacy and safety of trans-catheter aortic valve implantation (TAVI) devices. Synthetic aortic stenosis (AS) valve geometries for in silico trials can be created by using a Statistical Shape Model (SSM). SSM methods used in previous studies, have two disadvantages: (1) They require consistent inter-patient topology; (2) These methods do not consider the relation between shape features and outputs of interest. By considering output related features, the geometries may be described with fewer parameters. Therefore, the aim of this study was to set up a non-parametric SSM for AS valve geometries and take into account the output of interest: the pressure drop across the aortic valve (Δp).

This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101017578 (SIMCor - In-Silico testing and validation of Cardiovascular IMplantable devices).
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