Computational modeling of parametric stent desing in human atherosclerotic arteries (Master thesis)
The biomechanical behaviour of coronary stents after their implantation is of great interest to interventional cardiologists and biomedical engineers, since in-stent restenosis (ISR), which is related to the arterial wall injury, is a serious adverse event. Several factors can affect ISR, such as the stent design and the materials used for the stent scaffold, therefore various research teams have been investigating the mechanical performance of stents through the utilisation of computational approaches. The interest of the researchers has been initially focused on examining the free-stent expansion, investigating the stent behavior during and after deployment, ignoring the presence of other components, such as the surrounding arterial wall. Among the parameters, which were examined, were the stent foreshortening, the dogboning, the recoil and the stent diameter , . The effect of stent design was also examined, in terms of number, width and length of individual stent cells for different commercially available stent designs , , . Later, the arterial wall was also included in the analysis towards investigating the stent and arterial wall response. However, those studies have been mostly accounted on the utilisation of idealised geometries for the arterial wall. These studies have analysed the mechanical behavior of the stent, in terms of deformation, stress and strain, while for the new generation of stents, additional parameters were included, such as the behavior of the stent coating , the drug-release and degradation mechanisms. The arterial wall was modelled as an idealised cylindrical vessel, while the plaque had a parabola-shape. The arterial wall was assumed to be straight or curved, while stent expansion was achieved either as a pressure- or a displacement driven approach , , . Different types of stent materials were used in the computational analysis and were compared in terms of stresses and strain , , , . The effect of stent design was also investigated. Specifically, the stent diameter , the geometry of the bridges , the strut spacing  and the thickness , the stent angle and length , , the shape of the circumferential rings and links  were examined. Even if those simplified approaches have assisted in understanding the stenting mechanics, there was an imperative need in modeling the 3D arterial morphology in a more realistic way and including the patient-specific characteristics. To accomplish this, information from different imaging modalities (MRI, angio, IVUS, OCT) of a particular patient’s vasculature were used . Those studies shed the light on the importance of representing the arterial wall and plaque components, not as a single layer structures , , , but taking into consideration the composition of the tissue. In such studies, different parameters were investigated, such as the stent material properties , the stent design , , the stent-balloon interaction , stent design and the tissue material properties. To achive stent implantation success, scientific discoveries and technologies should be translated into practical applications. It is evident that in interventional cardiology, percutaneous cardiovascular intervention has been transformed from a quirky experimental procedure to a therapeutic approach for patients with cardiovascular disease. Inherent in the application of stent technology is the preclinical testing using animal and the clinical testing with humans. However, a further understanding could be achieved through the complementary information from in silico experiments. This thesis aims to investigate and evaluate the effect of stent design and materials through the utilization of realistic and patient specific arterial geometries. It is an attempt to provide insight on the key factors that could affect the success of the interventional process through the analysis of the design and material parameters that play a significant role. This is achived through the creation of five different in silico models that are compared in terms of stress and deformation distribution in the arterial wall and stent components. Three different materials for the stent scaffold (CoCr, SS316L, PtCr) and two stent designs (stent with thick vs stent with thin struts) are used in the in silico experiments. The innovation of the current study lays on the inclusion and incorporation of patient specific characteristics and arterial morphology that enables the replication and reproduction real clinical scenarios. In detail, eight chapters are included: Chapter 1 provides an overview of cardiovascular disease, atherosclerosis and treatment options focusing on stenting. The evolution of coronary stenting and the main considerations during this interventional procedure, the mechanisms and the pathophysiology implicated in ISR and thrombosis are described. Chapter 2 presents an analysis of the stent market, the key players in the coronary stent industry as well as the predictions for the market potential. Details on the stents desirable characteristics and on the properties from the materials perspective are provided in Chapter 3. A categorization of the stents based on the geometry and the two main categories of stents available in the market are also presented. Chapter 4 presents the process of stent evaluation, that is currently followed, describing the regulatory framework, the approval process, the in vitro mechanical testing, the animal and the finally the clinical studies. Chapter 5 provides a comprehensive literature review of the computational approaches in coronary stent modeling. More specifically, modeling studies on stent free expansion and expansion in idealized and patient specific arterials segments are analysed. Chapter 6 describes the main steps that were followed to create the Finite Element Models (FEM) that were used in the current analysis. Specifically, information on the stent design and the 3D arterial reconstruction are presented accompanied with the method for the meshing approach. The boundary conditions and the loading which are used as well as the governing equations are presented. Then the two main approaches; the creation of the FEM models with different stent design and materials is performed and the relevant results are presented in terms of deformation and stress distribution in the stent scaffold and in the vascular tissue. Chapter 7 presents the conclusions obtained from the analysis and the comparison of the representative stent materials (Model A, Model B and Model C) and the representative stent designs (Model D and Model E). The analysis focuses on assessing the effect of design and material on stent expansion, stress distribution and occurred arterial stresses during the deployment process inside a reconstructed diseased arterial segment. It is revealed that the stent of Model A exhibits higher arterial stresses in the arterial wall followed by Model B and Model C. For all models (Model A, Model B, Model C), stent expansion affects the inner arterial layer. As far as the distribution of the arterial stress in different stress ranges is concerned, it is demonstrated that: (i) the percentage of arterial stress in the stress range of 0-0.15MPa is higher for the arterial wall of Model B, (ii) the percentage of arterial stress in the stress range of 0.15-0.30MPa is slightly higher for the arterial wall of Model C, (iii) the percentage of arterial stress in the stress range over 0.3 is higher for Model A. In addition: (i) the percentage of the von Mises stress for the stent of Model B in the stress range of 0-200MPa is higher compared to Μodel A and Μodel C, (ii) the percentage of the von Mises stress for the stent of Model C in the stress range of 200-400MPa is higher followed by the stent of Model B and the stent of Model A, (iii) the percentage of the von Mises stress for the stent of Model A in the stress range over 400MPa is higher compared to the stent of Model B and the stent of Model C. Model D (Model_thin) and Model E (Model_thick) have been designed with a strut thickness of 0.0702 mm and 0.0774 mm respectively. The Principal stresses for the inner arterial wall are depicted for Model_thin and Model_thick in different views. Higher arterial stresses are located behind the region where the stent was expanded and more specifically in the region of stenosis. The slightly highest stresses in the arterial wall are observed for Model_thick compared to Model_thick. However, from the different views, it is evident that the areas of the inner arterial wall affected from higher stresses are more in the model with the thick struts. Specifically, it is demonstrated that: (i) the percentage of arterial principal stress in the stress range of 0-0.3 MPa is higher for Model D (67.5%) compared to Model E (66.5%), whereas the percentage of arterial principal stress in the stress range over 0.3MPa is higher for Model E with the thicker struts compared to Model D with the thinner struts. Both stent models follow the same deformation pattern, while for all pressures, in Model D (thin struts) higher von Mises stresses occur compared to Model E (thick struts). Regarding the percentage volume of each stent model belonging to different stress ranges: (i) 62.5% percentage of the total von Mises stress belongs to the stress range of 0-200MPa for Model D and 71.28% for Model E respectively, (ii) the highest percentage in the stress range over 200MPa belongs to Model D (37.5%). Chapter 8 provides an overview of the limitations of the current thesis in terms of the materials properties used, the assumption of the homogeneity of the arterial wall and the lack of the direct experimental validation of the computational results.
|Institution and School/Department of submitter:||Πανεπιστήμιο Ιωαννίνων. Πολυτεχνική Σχολή. Τμήμα Μηχανικών Επιστήμης Υλικών|
|Subject classification:||Computational modeling|
|Keywords:||Υπολογιστική μοντελοποίηση,Στεφανιαία ενδοπρόθεση,Παραμετρική ανάλυση,Πεπερασμένα στοιχεία,Computational moddelling,Finite element analysis,Pavametric analysis|
|Appears in Collections:||Διατριβές Μεταπτυχιακής Έρευνας (Masters)|
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|Μ.Ε. ΚΑΡΑΝΑΣΙΟΥ ΓΕΩΡΓΙΑ 2018.pdf||8.28 MB||Adobe PDF||View/Open|
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