{"title":"Towards a reduced order model for EVAR planning and intra-operative navigation","authors":"Monica Emendi , Eirini Kardampiki , Karen-Helene Støverud , Antonio Martinez Pascual , Leonardo Geronzi , Sigrid Kaarstad Dahl , Victorien Prot , Paal Skjetne , Marco Evangelos Biancolini","doi":"10.1016/j.medengphy.2024.104229","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><p>The pre-operative planning and intra-operative navigation of the endovascular aneurysm repair (EVAR) procedure are currently challenged by the aortic deformations that occur due to the insertion of a stiff guidewire. Hence, a fast and accurate predictive tool may help clinicians in the decision-making process and during surgical navigation, potentially reducing the radiations and contrast dose. To this aim, we generated a reduced order model (ROM) trained on parametric finite element simulations of the aortic wall-guidewire interaction.</p></div><div><h3>Method</h3><p>A Design of Experiments (DOE) consisting of 300 scenarios was created spanning over seven parameters. Radial basis functions were used to achieve a morphological parametrization of the aortic geometry. The ROM was built using 200 scenarios for training and the remaining 100 for validation.</p></div><div><h3>Results</h3><p>The developed ROM estimated the displacement of aortic nodes with a relative error below 5.5% for all the considered validation cases. From a preliminary analysis, the aortic elasticity, the stiffness of the guidewire and the tortuosity of the cannulated iliac artery proved to be the most influential parameters.</p></div><div><h3>Conclusions</h3><p>Once built, the ROM provided almost real-time and accurate estimations of the guidewire-induced aortic displacement field, thus potentially being a promising pre- and intra-operative tool for clinicians.</p></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"131 ","pages":"Article 104229"},"PeriodicalIF":1.7000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1350453324001309/pdfft?md5=e31c28cf4d82238e7951b8a62951ea41&pid=1-s2.0-S1350453324001309-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Engineering & Physics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1350453324001309","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
The pre-operative planning and intra-operative navigation of the endovascular aneurysm repair (EVAR) procedure are currently challenged by the aortic deformations that occur due to the insertion of a stiff guidewire. Hence, a fast and accurate predictive tool may help clinicians in the decision-making process and during surgical navigation, potentially reducing the radiations and contrast dose. To this aim, we generated a reduced order model (ROM) trained on parametric finite element simulations of the aortic wall-guidewire interaction.
Method
A Design of Experiments (DOE) consisting of 300 scenarios was created spanning over seven parameters. Radial basis functions were used to achieve a morphological parametrization of the aortic geometry. The ROM was built using 200 scenarios for training and the remaining 100 for validation.
Results
The developed ROM estimated the displacement of aortic nodes with a relative error below 5.5% for all the considered validation cases. From a preliminary analysis, the aortic elasticity, the stiffness of the guidewire and the tortuosity of the cannulated iliac artery proved to be the most influential parameters.
Conclusions
Once built, the ROM provided almost real-time and accurate estimations of the guidewire-induced aortic displacement field, thus potentially being a promising pre- and intra-operative tool for clinicians.
导言血管内动脉瘤修补术(EVAR)的术前规划和术中导航目前面临着因插入坚硬导丝而导致主动脉变形的挑战。因此,快速准确的预测工具可以帮助临床医生在决策过程和手术导航过程中减少辐射和造影剂剂量。为此,我们在主动脉壁与导丝相互作用的参数化有限元模拟基础上建立了一个经过训练的低阶模型(ROM)。使用径向基函数对主动脉几何形状进行形态参数化。结果在所有考虑的验证案例中,所开发的 ROM 估算的主动脉节点位移的相对误差低于 5.5%。从初步分析来看,主动脉的弹性、导丝的硬度和插管髂动脉的迂曲度被证明是影响最大的参数。结论ROM一旦建立,几乎可以实时准确地估计导丝引起的主动脉位移场,因此有可能成为临床医生的术前和术后工具。
期刊介绍:
Medical Engineering & Physics provides a forum for the publication of the latest developments in biomedical engineering, and reflects the essential multidisciplinary nature of the subject. The journal publishes in-depth critical reviews, scientific papers and technical notes. Our focus encompasses the application of the basic principles of physics and engineering to the development of medical devices and technology, with the ultimate aim of producing improvements in the quality of health care.Topics covered include biomechanics, biomaterials, mechanobiology, rehabilitation engineering, biomedical signal processing and medical device development. Medical Engineering & Physics aims to keep both engineers and clinicians abreast of the latest applications of technology to health care.