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

K Spranger,Y Ventikos,C Capelli,S Schievano,G.M Bosi

doi:10.1016/j.cma.2015.03.022

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.

Highlights

Endovascular devices are widely adopted for restoring the patency of arteries and veins
This study focuses on the analysis of a novel numerical fast method (FM) to simulate the process of stent expansion, as compared to detailed Finite Element (FE) analysis
Results of FM simulations are presented as the snapshots of the obtained stent configuration after a certain number of iterations, while finite element (FE) analyses are shown throughout the simulation (30 s)

Summary

Introduction

Endovascular devices (stents, stent grafts, flow diverters) are widely adopted for restoring the patency of arteries and veins. Materials and surface processing allowed the use of stents for treating a wide variety of conditions, including stenosis and aneurysms of coronary [2], carotid [3], cerebral [4], thoracic [5] and peripheral arteries [6] and, more recently, cardiac valve dysfunction [7,8]. Interventional cardiologists currently have an extensive range of products at their disposal that enable them to reach complex cardiovascular districts from different access sites.

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Methods

Results

Conclusion