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DTSTAMP:20191206T142455Z
LOCATION:Panorama 1
DTSTART;TZID=Europe/Stockholm:20180627T090000
DTEND;TZID=Europe/Stockholm:20180627T093000
UID:isc_hpc_ISC High Performance 2018_sess171_inv_sp138@linklings.com
SUMMARY:Investigation of Different Deployment Positions of a Generic Trans
 catheter Self-expandable Heart Valve Frame Using the Living Heart Model
DESCRIPTION:Focus Session\n\nInvestigation of Different Deployment Positio
 ns of a Generic Transcatheter Self-expandable Heart Valve Frame Using the 
 Living Heart Model\n\nDegel\n\nThe purpose of this work is to analyze the 
 influence of the deployment position of a typical generic Nitinol aortic h
 eart valve frame on the cyclic loading conditions of the frame using the L
 iving-Heart model. Such a heart valve frame is typically loaded into a cat
 heter prior to the surgery and is deployed in the region of the aortic roo
 t and the ascending aorta. The poor radiopacity of Nitinol makes the deplo
 yment procedure very challenging for the physician and could lead to a sub
 optimal positioning.\nThe simulation includes the full crimping and deploy
 ment process and several heart beatings to show the influence of the deplo
 yment position and the valve leaflets on the loading conditions and thus o
 n the fatigue behavior of the frame. This approach would not only allow to
  optimize the frame design with respect to the fatigue behavior but it wou
 ld also be possible to find the optimal deployment position with respect t
 o the loading conditions (radial force, cyclic loading) in a patient speci
 fic model prior to the implantation. \nSince the mesh of the frame must be
  fine enough to resolve the stress and strain field appropriately, the tim
 e step of the explicit time Integration scheme is strongly reduced by the 
 small elements of the frame. Thus, HPC is used to solve the simulation in 
 reasonable times. As side study, the influence of the number of CPU's on t
 he solving time is also investigated.\n\nPasses: Conference Pass, Personal
 ized Medicine\n\nTag: Conference Pass, Personalized Medicine
URL:https://2018.isc-program.com/presentation/?id=inv_sp138&sess=sess171
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