Comparison and calibration of a real-time virtual stenting algorithm using Finite Element Analysis and Genetic Algorithms

Abstract

In this paper, we perform a comparative analysis between two computational methods for virtual stent deployment: a novel fast virtual stenting method, which is based on a spring–mass model, is compared with detailed finite element analysis in a sequence of in silico experiments. Given the results of the initial comparison, we present a way to optimise the fast method by calibrating a set of parameters with the help of a genetic algorithm, which utilises the outcomes of the finite element analysis as a learning reference. As a result of the calibration phase, we were able to substantially reduce the force measure discrepancy between the two methods and validate the fast stenting method by assessing the differences in the final device configurations.

Towards Predicting Patient-Specific Flow-Diverter Treatment Outcomes for Bifurcation Aneurysms: From Implantation Rehearsal to Virtual Angiograms

“…The speed of the fast deployment method comes at the cost of a number of assumptions, most significantly both linear elasticity and the representation of interwoven wires free to slide over one another as fixed and planar struts. However, errors in deployed position introduced by such assumptions have been shown to be small when compared to other simulations such as full finite element deployments 2 , 30 as well as in vitro 16 and in vivo 5 experiments.…”

“…Deformation of the strut is modeled by both linear and torsional springs connecting each node, with the stiffness of each spring related to the strut thickness and length. 30 , 31 Contact between the device and vessel wall is modeled with a no-slip condition applied to the device node when the strut makes contact with the vessel wall. Following deployment, the thickness of each device strut is then added back to the strut centerlines by sweeping a cylindrical cross-section in Blender, as shown in Fig.…”

Virtual stenting with simplex mesh and mechanical contact analysis for real-time planning of thoracic endovascular aortic repair

“…Previous 3-D computational studies targeting stent-induced aortic reshaping were based mainly on structural analysis using a finite element method which is not viable for clinical use because of its high computation requirement 38 , 39 . Although the fast VSA based on deformable simplex mesh 19 , 24 , the active contour model 25 and the spring analogy 21 have been introduced for cerebral aneurysm stenting, developing a similar VSA for aortic endovascular repair such as TEVAR is harder; the mechanical contact and equilibrium process between the stent-graft and the aortic wall cannot be neglected and the stent-induced TL reshaping is significant (for example, in the present study, the aortic diameter measurements at the diaphragm level showed up to 355% stent-induced TL expansion in successfully treated cases). A VSA like the one developed in this study that is able to mimic the considerable stent-induced deformation of the vessel wall was therefore needed to address these challenges.…”

Model reduction methodology for computational simulations of endovascular repair

“…In the current work, an efficient model reduction methodology for endovascular repair computational simulations was proposed. As well as in the other numerical methodologies that can be applied to reduce the computational cost, the SG mechanical properties, interactions and geometric aspects were also considered [16][17] [18]. These parameters changes depend on the SG's available in the market.…”