Miloš Anić, M. Milošević, D. Nikolić, B. Milićević, Vladimir Geroski, M. Kojic, Gordana R. Jovicic, N. Filipovic
{"title":"Computational Modeling for Mechanical Testing of Bioresorbable Stents","authors":"Miloš Anić, M. Milošević, D. Nikolić, B. Milićević, Vladimir Geroski, M. Kojic, Gordana R. Jovicic, N. Filipovic","doi":"10.58245/ipsi.tir.22jr.07","DOIUrl":null,"url":null,"abstract":"Development of plaques compositions caused by atherosclerosis inside of coronary arteries is known as coronary artery disease. Its treatment includes the possibility of stent deployment through operation called percutaneous transluminal coronary angioplasty. In this procedure stent is delivered using a balloon catheter and then inserted across the lesion. The new stent design development or optimization of existing ones requires the performance of many expensive mechanical tests which are always followed by their time-consuming analysis. Thus, the possibility of those tests to be performed on computer, i.e., in-silico, instead of in reality, i.e. invitro could remove the necessity of a greater number of in-vitro tests. With in-silico mechanical testing the analysis of all mechanical characteristics could be performed which would drastically decrease both the time and the expenses of the process and even gives the possibility to compare two or more designs. In this study, recently introduced material model of PolyL-Lactic Acid (PLLA) fully bioresorbable vascular scaffold and recently accredited numerical InSilc platform were used to perform in-silico mechanical tests on different stent designs that have different geometrical and material characteristics. In-silico tests include radial compression (RCI), inflation, three-point bending and two plate crush test whose results could provide well-grounded conclusions and thus a notable contribution in stent design and optimization.","PeriodicalId":41192,"journal":{"name":"IPSI BgD Transactions on Internet Research","volume":"24 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IPSI BgD Transactions on Internet Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58245/ipsi.tir.22jr.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Development of plaques compositions caused by atherosclerosis inside of coronary arteries is known as coronary artery disease. Its treatment includes the possibility of stent deployment through operation called percutaneous transluminal coronary angioplasty. In this procedure stent is delivered using a balloon catheter and then inserted across the lesion. The new stent design development or optimization of existing ones requires the performance of many expensive mechanical tests which are always followed by their time-consuming analysis. Thus, the possibility of those tests to be performed on computer, i.e., in-silico, instead of in reality, i.e. invitro could remove the necessity of a greater number of in-vitro tests. With in-silico mechanical testing the analysis of all mechanical characteristics could be performed which would drastically decrease both the time and the expenses of the process and even gives the possibility to compare two or more designs. In this study, recently introduced material model of PolyL-Lactic Acid (PLLA) fully bioresorbable vascular scaffold and recently accredited numerical InSilc platform were used to perform in-silico mechanical tests on different stent designs that have different geometrical and material characteristics. In-silico tests include radial compression (RCI), inflation, three-point bending and two plate crush test whose results could provide well-grounded conclusions and thus a notable contribution in stent design and optimization.