The lack of long term patency of small diameter synthetic vascular grafts currently available on the market has directed research towards improving the performance of these grafts. Improved radial compliance matching and appropriate tissue ingrowth into the graft structure are main goals for an ideal vascular graft. In addition, the use of biodegradable materials offers the promising prospect of leaving behind a near native vessel with no synthetic material remaining. Tissue ingrowth into grafts alters their mechanics. This, combined with a loss of mechanical integrity over time, in the case of biodegradable scaffolds, brings the need to investigate how these changes play out and how to tailor them for optimal graft healing. This project set out to investigate the mechanics of electrospun Pellethane® 2363-80AE (Dow Chemicals) and DegraPol® (ab medica S.p.A) biostable DegraPol® DP0 and biodegradable DegraPol® DP30 scaffolds during in vivo animal studies. DegraPol® DP30 findings were used to investigate the scaffolds' potential use for vascular grafts by means of a finite element graft model. Porous, electrospun scaffolds were manufactured and implanted into two subcutaneous and one circulatory rat models. All studies consisted of four time points, namely 0, 7, 14 and 28 days. Scaffold morphology was characterised, and tissue ingrowth was quantified by histological analysis of explanted samples. Orthogonal, uni-axial tensile testing measured scaffold mechanical response of in-fibre and cross-fibre deformation. Tissue ingrowth brought about considerable changes in biostable DegraPol® DP0 scaffold mechanics. Tensile testing of degradable DegraPol® DP30 scaffolds in their load bearing circumferential direction showed a balance between a loss in mechanical strength and an increase in strength by tissue ingrowth. This resulted in constant radial compliance of 4.47 ± 0.14%/100 mmHg between 80 and 120 mmHg for the four week period predicted with the numerical models. The finite element model based on DegraPol® DP30 scaffold mechanics for 6 mm grafts showed better, i.e. higher, radial compliance than current grafts used clinically (polyethylene terephthalate and expanded polytetrafluoroethylene grafts). This stability in compliance, coupled with good tissue ingrowth is of scientific importance as it shows that highly aligned, porous electrospun DegraPol® DP30 scaffolds are a viable option for vascular grafting to achieve long term graft patency

Cardiovascular diseases account for one third of all deaths worldwide, more than 33% of which are related to ischemic heart disease, including myocardial infarction (MI). This thesis seeks to provide insight and understanding of mechanisms during different stages of MI by utilizing finite element (FE) modelling. Three-dimensional biventricular rat heart geometries were developed from cardiac magnetic resonance images of a healthy heart and a heart with left ventricular (LV) infarction two weeks and four weeks after infarct induction. From these geometries, FE models were established. To represent the myocardium, a structure-based constitutive model and a rule-based myofibre distribution were developed to simulate both passive mechanics and active contraction.

Endovascular aortic repair (EVAR) is a minimally invasive alternative to open surgery for the treatment of aortic aneurysms (AA). However, standard EVAR is not applicable to complex AA with involvement of vital branches, which could be occluded by the endograft. As an emerging technique, the concept of multiple overlapping uncovered stents (MOUS) have been proposed to manage complex lesions. MOUS was used to modulate the flow pattern inside the aneurysm sac, and promote the thrombus formation followed by the aneurysm shrinkage. In this dissertation, we sought to investigate the mechanism of MOUS-induced flow modulation and key factors associated with the success of this novel technique: - The mechanical behaviour of AA was characterised by uniaxial material tests (Chapter 4). A Bayesian framework was proposed for material constants identification. They were found correlated to the microstructure of tissue fibre network and were capable in differentiating tissue types. - Solid-to-solid interaction and one-way fluid-solid interaction (FSI) analysis was performed based on patient-specific computer tomography angiography (Chapters 5&6). Structural stress concentrations were observed within the landing zones, which increased with the number of stents deployed. In the parameter studies (Chapter 6), the overall porosity was identified as the dominant factor of the flow-diverting outcome, while cross-stent structures of MOUS had limited influence. - The pathological effect of structural stress concentration induced by an implanted device was further studied in rabbit models (Chapter 7). The wall structural stress and fluid shear stress were obtained from FSI analysis based on magnetic resonance imaging (MRI), and correlated to plaque characteristics. Both high structural stress and low fluid shear stress were found correlated to plaque initialisation and increased inflammation. Overall, MOUS modulates the blood flow with robust performance under different overlapping patterns. Image-based biomechanical analysis can optimise MOUS design and can contribute to personalised pre-surgery planning.

Les simulations numériques des écoulements sanguins cardiovasculaires peuvent combler d’importantes lacunes dans les capacités actuelles de traitement clinique. En effet, elles offrent des moyens non invasifs pour quantifier l’hémodynamique dans le cœur et les principaux vaisseaux sanguins chez les patients atteints de maladies cardiovasculaires. Ainsi, elles permettent de recouvrer les caractéristiques des écoulements sanguins qui ne peuvent pas être obtenues directement à partir de l’imagerie médicale. Dans ce sens, des simulations personnalisées utilisant des informations propres aux patients aideraient à une prévision individualisée des risques. Nous pourrions en effet, disposer des informations clés sur la progression éventuelle d’une maladie ou détecter de possibles anomalies physiologiques. Les modèles numériques peuvent fournir également des moyens pour concevoir et tester de nouveaux dispositifs médicaux et peuvent être utilisés comme outils prédictifs pour la planification de traitement chirurgical personnalisé. Ils aideront ainsi à la prise de décision clinique. Cependant, une difficulté dans cette approche est que, pour être fiables, les simulations prédictives spécifiques aux patients nécessitent une assimilation efficace de leurs données médicales. Ceci nécessite la solution d’un problème hémodynamique inverse, où les paramètres du modèle sont incertains et sont estimés à l’aide des techniques d’assimilation de données.Dans cette thèse, le problème inverse pour l’estimation des paramètres est résolu par une méthode d’assimilation de données basée sur un filtre de Kalman d’ensemble (EnKF). Connaissant les incertitudes sur les mesures, un tel filtre permet la quantification des incertitudes liées aux paramètres estimés. Un algorithme d’estimation de paramètres, basé sur un filtre de Kalman d’ensemble, est proposé dans cette thèse pour des calculs hémodynamiques spécifiques à un patient, dans un réseau artériel schématique et à partir de mesures cliniques incertaines. La méthodologie est validée à travers plusieurs scenarii in silico utilisant des données synthétiques. La performance de l’algorithme d’estimation de paramètres est également évaluée sur des données expérimentales pour plusieurs réseaux artériels et dans un cas provenant d’un banc d’essai in vitro et des données cliniques réelles d’un volontaire (cas spécifique du patient). Le but principal de cette thèse est l’analyse hémodynamique spécifique du patient dans le polygone de Willis, appelé aussi cercle artériel du cerveau. Les propriétés hémodynamiques communes, comme celles de la paroi artérielle (module de Young, épaisseur de la paroi et coefficient viscoélastique), et les paramètres des conditions aux limites (coefficients de réflexion et paramètres du modèle de Windkessel) sont estimés. Il est également démontré qu’un modèle appelé compartiment d’ordre réduit (ou modèle dimension zéro) permet une estimation simple et fiable des caractéristiques du flux sanguin dans le polygone de Willis. De plus, il est ressorti que les simulations avec les paramètres estimés capturent les formes attendues pour les ondes de pression et de débit aux emplacements prescrits par le clinicien. / Cardiovascular blood flow simulations can fill several critical gaps in current clinical capabilities. They offer non-invasive ways to quantify hemodynamics in the heart and major blood vessels for patients with cardiovascular diseases, that cannot be directly obtained from medical imaging. Patient-specific simulations (incorporating data unique to the individual) enable individualised risk prediction, provide key insights into disease progression and/or abnormal physiologic detection. They also provide means to systematically design and test new medical devices, and are used as predictive tools to surgical and personalize treatment planning and, thus aid in clinical decision-making. Patient-specific predictive simulations require effective assimilation of medical data for reliable simulated predictions. This is usually achieved by the solution of an inverse hemodynamic problem, where uncertain model parameters are estimated using the techniques for merging data and numerical models known as data assimilation methods.In this thesis, the inverse problem is solved through a data assimilation method using an ensemble Kalman filter (EnKF) for parameter estimation. By using an ensemble Kalman filter, the solution also comes with a quantification of the uncertainties for the estimated parameters. An ensemble Kalman filter-based parameter estimation algorithm is proposed for patient-specific hemodynamic computations in a schematic arterial network from uncertain clinical measurements. Several in silico scenarii (using synthetic data) are considered to investigate the efficiency of the parameter estimation algorithm using EnKF. The usefulness of the parameter estimation algorithm is also assessed using experimental data from an in vitro test rig and actual real clinical data from a volunteer (patient-specific case). The proposed algorithm is evaluated on arterial networks which include single arteries, cases of bifurcation, a simple human arterial network and a complex arterial network including the circle of Willis.The ultimate aim is to perform patient-specific hemodynamic analysis in the network of the circle of Willis. Common hemodynamic properties (parameters), like arterial wall properties (Young’s modulus, wall thickness, and viscoelastic coefficient) and terminal boundary parameters (reflection coefficient and Windkessel model parameters) are estimated as the solution to an inverse problem using time series pressure values and blood flow rate as measurements. It is also demonstrated that a proper reduced order zero-dimensional compartment model can lead to a simple and reliable estimation of blood flow features in the circle of Willis. The simulations with the estimated parameters capture target pressure or flow rate waveforms at given specific locations.