A fast in silico model for preoperative risk assessment of paravalvular leakage

Michelle Spanjaards, Finja Borowski, Laura Supp, René Ubachs, Valentina Lavezzo, Olaf van der Sluis (Corresponding author)

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In silico simulations can be used to evaluate and optimize the safety, quality, efficacy and applicability of medical devices. Furthermore, in silico modeling is a powerful tool in therapy planning to optimally tailor treatment for each patient. For this purpose, a workflow to perform fast preoperative risk assessment of paravalvular leakage (PVL) after transcatheter aortic valve replacement (TAVR) is presented in this paper. To this end, a novel, efficient method is introduced to calculate the regurgitant volume in a simplified, but sufficiently accurate manner. A proof of concept of the method is obtained by comparison of the calculated results with results obtained from in vitro experiments. Furthermore, computational fluid dynamics (CFD) simulations are used to validate more complex stenosis scenarios. Comparing the simplified leakage model to CFD simulations reveals its potential for procedure planning and qualitative preoperative risk assessment of PVL. Finally, a 3D device deployment model and the efficient leakage model are combined to showcase the application of the presented leakage model, by studying the effect of stent size and the degree of stenosis on the regurgitant volume. The presented leakage model is also used to visualize the leakage path. To generalize the leakage model to a wide range of clinical applications, further validation on a large cohort of patients is needed to validate the accuracy of the model’s prediction under various patient-specific conditions.
Originele taal-2Engels
Pagina's (van-tot)959-985
Aantal pagina's27
TijdschriftBiomechanics and Modeling in Mechanobiology
Nummer van het tijdschrift3
Vroegere onlinedatum11 feb. 2024
StatusGepubliceerd - jun. 2024


The authors would like to thank the European Union’s Horizon 2020 research and innovation program for the financial support under grant agreement No 101017578 (SIMCor) and the German institute of computer-assisted cardiovascular medicine, Charité, for providing the synthetic aortic root geometries.

Horizon 2020 Framework Programme101017578


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