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dc.contributor.authorRuss, Christoph-
dc.contributor.authorHopf, Raoul-
dc.contributor.authorSündermann, Simon H.-
dc.contributor.authorBorn, Silvia-
dc.contributor.authorHirsch, Sven-
dc.contributor.authorFalk, Volkmar-
dc.contributor.authorSzékely, Gábor-
dc.contributor.authorGessat, Michael-
dc.date.accessioned2018-12-07T07:35:10Z-
dc.date.available2018-12-07T07:35:10Z-
dc.date.issued2014-
dc.identifier.isbn978-3-319-12056-0de_CH
dc.identifier.isbn978-3-319-12057-7de_CH
dc.identifier.issn0302-9743de_CH
dc.identifier.issn1611-3349de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/13625-
dc.description.abstractTranscatheter aortic valve implantation (TAVI) is a minimally invasive procedure to treat severe aortic stenosis in patients with a high risk for conventional surgery. In-silico experiments of stent deployment within patient-specific models of the aortic root have created an opportunity to predict stent behavior during the intervention. Current limitations in procedure planning are a primary motivator for these simulations. The virtual stent placement preceding the deployment phase of such experiments has major influence on the outcome of the simulation, but only received little attention in literature up to now. This work presents a methodical approach to patient-specific planning of placement of self-expanding stent models by analyzing experimental outcomes of different sets of boundary conditions constraining the stent. As a results, different paradigms for automated or expert guided stent placement are evaluated, which demonstrate the benefits of virtual stent deployment for intervention planning. To build a predictive planning pipeline for TAVI we use an automatic segmentation of the aorta, aortic root and left ventricle, which is converted to a finite element mesh. The virtual stent is then placed along a guide wire model and deployed at multiple locations around the aortic root. The simulation has been evaluated using pre- and post-interventional CT scans with an average relative circumferential error of 4.0% (±2.5%), which is less than half of the average difference in circumference between individual stent sizes (8.6%). Our methods are therefore enabling patient-specific planning and provide better guidance during the intervention.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofseriesLecture Notes in Computer Sciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc617: Chirurgiede_CH
dc.titleComputational stent placement in transcatheter aortic valve implantationde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-319-12057-7_11de_CH
zhaw.conference.details6th International Symposium ISBMS 2014, Strasbourg, France, 16-17 October 2014de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end105de_CH
zhaw.pages.start95de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number8789de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsBiomedical Simulationde_CH
zhaw.webfeedBiomedical Simulationde_CH
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Russ, C., Hopf, R., Sündermann, S. H., Born, S., Hirsch, S., Falk, V., Székely, G., & Gessat, M. (2014). Computational stent placement in transcatheter aortic valve implantation [Conference paper]. Biomedical Simulation, 95–105. https://doi.org/10.1007/978-3-319-12057-7_11
Russ, C. et al. (2014) ‘Computational stent placement in transcatheter aortic valve implantation’, in Biomedical Simulation. Cham: Springer, pp. 95–105. Available at: https://doi.org/10.1007/978-3-319-12057-7_11.
C. Russ et al., “Computational stent placement in transcatheter aortic valve implantation,” in Biomedical Simulation, 2014, pp. 95–105. doi: 10.1007/978-3-319-12057-7_11.
RUSS, Christoph, Raoul HOPF, Simon H. SÜNDERMANN, Silvia BORN, Sven HIRSCH, Volkmar FALK, Gábor SZÉKELY und Michael GESSAT, 2014. Computational stent placement in transcatheter aortic valve implantation. In: Biomedical Simulation. Conference paper. Cham: Springer. 2014. S. 95–105. ISBN 978-3-319-12056-0
Russ, Christoph, Raoul Hopf, Simon H. Sündermann, Silvia Born, Sven Hirsch, Volkmar Falk, Gábor Székely, and Michael Gessat. 2014. “Computational Stent Placement in Transcatheter Aortic Valve Implantation.” Conference paper. In Biomedical Simulation, 95–105. Cham: Springer. https://doi.org/10.1007/978-3-319-12057-7_11.
Russ, Christoph, et al. “Computational Stent Placement in Transcatheter Aortic Valve Implantation.” Biomedical Simulation, Springer, 2014, pp. 95–105, https://doi.org/10.1007/978-3-319-12057-7_11.


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