Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-03-06T14:57:14Z No. of bitstreams: 1 gustavomontesnovaes.pdf: 4933394 bytes, checksum: d1148020d41a74584cee8821c8f26603 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-06T20:25:13Z (GMT) No. of bitstreams: 1 gustavomontesnovaes.pdf: 4933394 bytes, checksum: d1148020d41a74584cee8821c8f26603 (MD5) / Made available in DSpace on 2017-03-06T20:25:13Z (GMT). No. of bitstreams: 1 gustavomontesnovaes.pdf: 4933394 bytes, checksum: d1148020d41a74584cee8821c8f26603 (MD5) Previous issue date: 2015-07-10 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A hipertensão é uma doença crônica que está relacionada com o aumento da pressão exercida pelo sangue nas paredes dos vasos sanguíneos. Seu surgimento está relacionado a síndromes metabólicas e, frequentemente, á obesidade. Entre o período de 2000 e 2011, esta patologia foi considerada a maior causa de morte no mundo devido à complicações inerentes a sua disfunção, como por exemplo acidente vascular cerebral e o infarto do miocárdio. Diversos estudos vêm sendo realizados com o objetivo de compreender melhor os mecanismos que estão relacionados ao surgimento da hipertensão bem como as disfunções causadas pela doença. Dentre estas disfunções, existem as alterações fisiológicas que ocorrem no coração sendo que as principais alterações ocorrem na atividade elétrica e mecânica do órgão cardíaco. A modelagem computacional se mostra como uma ferramenta muito eficaz no auxílio de tais estudos. A possibilidade de simular as disfunções causadas pela hipertensão no coração permitiria realizar experimentos prévios com baixo custo e em um pequeno intervalo de tempo. Assim este trabalho tem por principal objetivo apresentar modelos computacionais capazes de reproduzir a atividade eletromecânica transmural do miócito de ratos normotensos e hipertensos. Para isto, é proposto um novo modelo matemático/computacional resultado de um acoplamento de outros dois presentes na literatura. O modelo computacional proposto obteve resultados bastante satisfatórios visto que foi capaz de reproduzir as alterações fisiológicas ocorridas em miócitos de ratos, tanto para células de origem do epicárdio quanto para células de origem do endocárdio, nas principais variáveis associadas ao batimento cardíaco: potencial de ação, transiente intracelular de cálcio e o encurtamento do sarcômero. / The hypertension is a chronic disease that is related to an increased in the pressure exerted by the blood on the walls of blood vessels. Its appearance is related to the metabolic syndrome and often with obesity. Between the years 2000 and 2011, this condition was considered the leading cause of death worldwide due to the complications inherent to its dysfunction, such as stroke and myocardial infarction. Several studies have been conducted in order to better understand the mechanisms that are related to the onset of hypertension and the dysfunctions caused by this disease. Among these disorders, there are the physiological changes that occur in the heart with the main changes occuring in electrical and mechanical activity of the heart organ. The Computational modeling can become a very effective tool in aid of such studies. The possibility of simulating the dysfunctions caused by hypertension in the heart would results in a possibility to do previous in silico experiments with low cost and in a short period of time. So this work is primarily engaged to present computational models capable of reproducing the transmural electromechanical activity of myocyte of normotensive and hypertensive rats. For this, a new mathematical / computational model was proposed resulted from a coupling of two others models presented in the literature. The proposed computational model obtained satisfactory results since it was able to reproduce the physiological changes in myocytes of rats, both for epicardial origin of cells and for endocardial cells of origin, the main variables associated with the heartbeat: the action potential, calcium intracellular transient and the shortening of the sarcomere.

Cette thèse de doctorat est consacrée à l'étude des problèmes directe et inverse en électrophysiologie cardiaque. Comme les équations qui décrivent l'activité électrique du coeur peuvent être très couteuses en temps de calcul, une attention particulière est apportée aux méthodes d'ordre réduit et à leur applications aux modèles de l'électrophysiologie.Dans un premier temps, nous introduisons les modèles mathématiques et numériques de l'électrophysiologie cardiaque. Ces modèles nous permettent de réaliser des simulations numériques que nous validons à l'aide de plusieurs critères qualitatifs et quantitatifs trouvés dans la littérature médicale. Comme notre modèle prend en compte les oreillettes et les ventricules, nous sommes capables de reproduire des cycles complets d'électrocardiogrammes (ECG) à la fois dans des conditions saines et dans des cas pathologiques.Ensuite, plusieurs méthodes d'ordre réduit sont étudiées pour la résolution des équations de l'électrophysiologie. La méthode Proper Orthogonal Decomposition (POD) est appliquée pour la discrétisation des équations de l'électrophysiologie dans plusieurs configurations, comme par exemple la simulation d'un infarctus du myocarde. De plus, cette méthode est utilisée pour résoudre quelques problèmes d'identification de paramètres comme localiser un infarctus à partir de mesures d'un électrocardiogramme ou simuler une courbe de restitution. Pour contourner les limitations de la POD, une nouvelle méthode basée sur des couples de Lax approchés (Approximated Lax Pairs, ALP) est utilisée. Cette méthode est appliquée aux problèmes directe et inverse. Pour finir, un nouvel algorithme, basé sur les méthodes ALP et l'interpolation empirique discrète, est proposé. Cette nouvelle approche améliore significativement l'efficacité de l'algorithme original ALP et nous permet de considérer des modèles plus complexes utilisés en électrophysiologie cardiaque. / This PhD thesis is dedicated to the investigation of the forward and the inverse problem of cardiac electrophysiology. Since the equations that describe the electrical activity of the heart can be very demanding from a computational point of view, a particular attention is paid to the reduced order methods and to their application to the electrophysiology models. First, we introduce the mathematical and numerical models of electrophysiology and we implement them to provide for simulations that are validated against various qualitative and quantitative criteria found in the medical literature. Since our model takes into account atria and ventricles, we are able to reproduce full cycle Electrocardiograms (ECG) in healthy configurations and also in the case of several pathologies. Then, several reduced order methods are investigated for the resolution of the electrophysiology equations. The Proper orthogonal Decomposition (POD) method is applied for the discretization of the electrophysiology equations in several configurations, as for instance the simulation of a myocardial infarction. Also, the method is used in order to solve some parameters identification problems such as the identification of an infarcted zone using the Electrocardiogram measures and for the efficient simulation of restitution curves. To circumvent some limitations of the POD method, a new reduced order method based on the Approximated Lax Pairs (ALP) is investigated. This method is applied to the forward and inverse problems. Finally, a new reduced order algorithm is proposed, based on the ALP and the Discrete Empirical Interpolation methods. This new approach significantly improves the efficiency of the original ALP algorithm and allow us to consider more complex models used in electrophysiology.

No description available.

The role of T-type calcium channels (TTCCs) in the heart is unclear. TTCCs are transiently expressed throughout the neonatal heart during a period of rapid cardiac development. A few weeks postnatally, TTCCs are no longer found in ventricular myocytes (VMs) and calcium influx via TTCCs (ICa,T) is only detected in the SA node and Purkinje system. However, pathologic cardiac stress is associated with re-expression of TTCCs in VMs. Whether ICa,T in this setting promotes cardiac growth or exacerbates cardiac function is a topic of debate. The focus of this thesis work was to examine the effect of TTCC re-expression in the normal and diseased myocardium. Our experiments were performed in a transgenic mouse model with inducible, cardiac-specific expression of α1G TTCCs. While both the α1G and α1H TTCC subtypes re-appear during cardiac disease, we specifically evaluated the effects of α1G TTCCs since mRNA levels of this TTCC subtype are markedly elevated during cardiac pathology. We found that transgenic mice with α1G overexpression had robust ICa,T with biophysical properties similar to those published in previous studies. α1G mice had a small increase in cardiac function and showed no evidence of cardiac histopathology or increased mortality. These findings were in contrast to the phenotype of transgenic mice with augmented L-type calcium channel (LTCC) activity secondary to overexpression of the β2a regulatory subunit. While the magnitude of calcium influx in α1G and β2a VMs was similar, we found that cardiac contractility of β2a mice was significantly greater than α1G mice. Also, β2a mice had significant cardiac fibrosis, myocyte death, and premature lethality compared to the benign phenotype of α1G mice. We showed that the phenotypic differences are likely related to the differential spatial localization of T- and LTCCs. Whereas α1G TTCCs were principally localized to the surface sarcolemma, LTCCs were primarily found in the transverse tubules in close proximity to the sites of sarcoplasmic reticulum calcium release. We evaluated the effect of TTCC expression during cardiac disease by inducing myocardial infarction (MI) in α1G mice. Acutely (1-week post MI), α1G mice showed similar worsening of cardiac function and mortality rates compared to control post-infarct mice. However, α1G hearts had smaller infarct sizes which correlated with increased Akt and NFAT activation in α1G than control hearts. After chronic heart failure, i.e. 7- weeks post-infarction, α1G hearts had significant hypertrophic response as determined by increased HW/BW ratio, myocyte cross-sectional area, as well as NFAT and Akt activity. Finally, α1G mice had a small survival benefit than control mice, which while statistically non-significant, suggests that TTCC re-expression does not exacerbate cardiac function as hypothesized by some investigators. We conclude that TTCCs play a minimal role in cardiac function and activate pro-survival signaling pathways in the myocardium. / Physiology

This thesis investigates the high-order hierarchical finite element method, also known as the finite element p-version, as a computationally-efficient technique for generating numerical solutions to the cardiac monodomain equation. We first present it as a uniform-order method, and through an a priori error bound we explain why the associated cardiac cell model must be thought of as a PDE and approximated to high-order in order to obtain the accuracy that the p-version is capable of. We perform simulations demonstrating that the achieved error agrees very well with the a priori error bound. Further, in terms of solution accuracy for time taken to solve the linear system that arises in the finite element discretisation, it is more efficient that the state-of-the-art piecewise linear finite element method. We show that piecewise linear FEM actually introduces quite significant amounts of error into the numerical approximations, particularly in the direction perpendicular to the cardiac fibres with physiological conductivity values, and that without resorting to extremely fine meshes with elements considerably smaller than 70 micrometres, we can not use it to obtain high-accuracy solutions. In contrast, the p-version can produce extremely high accuracy solutions on meshes with elements around 300 micrometres in diameter with these conductivities. Noting that most of the numerical error is due to under-resolving the wave-front in the transmembrane potential, we also construct an adaptive high-order scheme which controls the error locally in each element by adjusting the finite element polynomial basis degree using an analytically-derived a posteriori error estimation procedure. This naturally tracks the location of the wave-front, concentrating computational effort where it is needed most and increasing computational efficiency. The scheme can be controlled by a user-defined error tolerance parameter, which sets the target error within each element as a proportion of the local magnitude of the solution as measured in the H^1 norm. This numerical scheme is tested on a variety of problems in one, two and three dimensions, and is shown to provide excellent error control properties and to be likely capable of boosting efficiency in cardiac simulation by an order of magnitude. The thesis amounts to a proof-of-concept of the increased efficiency in solving the linear system using adaptive high-order finite elements when performing single-thread cardiac simulation, and indicates that the performance of the method should be investigated in parallel, where it can also be expected to provide considerable improvement. In general, the selection of a suitable preconditioner is key to ensuring efficiency; we make use of a variety of different possibilities, including one which can be expected to scale very well in parallel, meaning that this is an excellent candidate method for increasing the efficiency of cardiac simulation using high-performance computing facilities.

Cardiovascular disease is the primary cause of death globally. Although this group encompasses a heterogeneous range of conditions, many of these diseases are associated with abnormalities in the cardiac electrical propagation. In these conditions, structural abnormalities in the form of scars and fibrotic tissue are known to play an important role, leading to a high individual variability in the exact disease mechanisms. Because of this, clinical interventions such as ablation therapy and CRT that work by modifying the electrical propagation should ideally be optimized on a patient specific basis. As a tool for optimizing these interventions, computational modelling and simulation of the heart have become increasingly important. However, in order to construct these models, a crucial step is the estimation of tissue conduction properties, which have a profound impact on the cardiac activation sequence predicted by simulations. Information about the conduction properties of the cardiac tissue can be gained from electrophysiological data, obtained using electroanatomical mapping systems. However, as in other clinical modalities, electrophysiological data are often sparse and noisy, and this results in high levels of uncertainty in the estimated quantities. In this dissertation, we develop a methodology based on Bayesian inference, together with a computationally efficient model of electrical propagation to achieve two main aims: 1) to quantify values and associated uncertainty for different tissue conduction properties inferred from electroanatomical data, and 2) to design strategies to optimise the location and number of measurements required to maximise information and reduce uncertainty. The methodology is validated in several studies performed using simulated data obtained from image-based ventricular models, including realistic fibre orientation and conduction heterogeneities. Subsequently, by using the developed methodology to investigate how the uncertainty decreases in response to added measurements, we derive an a priori index for placing electrophysiological measurements in order to optimise the information content of the collected data. Results show that the derived index has a clear benefit in minimising the uncertainty of inferred conduction properties compared to a random distribution of measurements, suggesting that the methodology presented in this dissertation provides an important step towards improving the quality of the spatiotemporal information obtained using electroanatomical mapping.

Improving imaging hardware, computational power, and algorithmic design are driving advances in interventional medical imaging. We lay the groundwork here for more effective use of machine learning and image registration in clinical electrophysiology. To achieve identification of atrial fibrosis using image data, we registered the electroanatomic map (EAM) data of atrial fibrillation (AF) patients undergoing pulmonary vein isolation (PVI) with MR (n = 16) or CT (n = 18) images. The relationship between image features and bipolar voltage was evaluated using single-parameter regression and random forest models. Random forest performed significantly better than regression, identifying fibrosis with area under the receiver operating characteristic curve (AUC) 0.746 (MR) and 0.977 (CT). This is the first evaluation of voltage prediction using image data. Next, we compared the character of native atrial fibrosis with ablation scar in MR images. Fourteen AF patients undergoing repeat PVI were recruited. EAM data from their first PVI was registered to the MR images acquired before the first PVI (‘pre-operative’) and before the second PVI ('post-operative' with respect to the first PVI). Non-ablation map points had similar characteristics in the two images, while ablation points exhibited higher intensity and more heterogeneity in post-operative images. Ablation scar is more strongly enhancing and more heterogeneous than native fibrosis. Finally, we addressed myocardial measurement in 3-D echocardiograms. The circular Hough transform was modified with a feature asymmetry filter, epicardial edges, and a search constraint. Manual and Hough measurements were compared in 5641 slices from 3-D images. The enhanced Hough algorithm was more accurate than the unmodified version (Dice coefficient 0.77 vs. 0.58). This method promises utility in segmentation-assisted cross-modality registration. By improving the information that can be extracted from medical images and the ease with which that information can be accessed, this progress will contribute to the advancing integration of imaging in electrophysiology.

La modélisation de l’électrophysiologie in silico a été un sujet de recherche important ces dernières décennies. Afin de pouvoir utiliser ces progrès importants dans les applications cliniques, il faut mettre en place des modèles macroscopiques qui peuvent être utilisés pour la planification et le guidage des procédures cliniques.L’objectif de cette thèse est de construire de tels modèles macroscopiques spécifiques à chaque patient pour le diagnostic et la prévision, dans le but d’améliorer la planification et le guidage de l’ablation par radio-fréquence (ARF) des patients souffrant de tachycardie ventriculaire (TV) après infarctus. Dans ce travail, nous avons proposé un cadre pour la personnalisation d’un modèle cardiaque 3D, le modèle de Mitchell-Schaeffer (MS), et nous avons évalué sa puissance prédictive dans plusieurs configurations de stimulation. Ceci a été réalisé sur des données ex vivo de cœurs porcins à l’aide d’images médicales et de données cartographiques optiques de l’épicarde. Ce cadre a ensuite été appliqué à un ensemble de données cliniques provenant d’imagerie hybride XMR et d’une procédure de cartographie électrophysiologique sur un patient souffrant d’insuffisance cardiaque.Ensuite, le modèle 3D MS a également été adapté pour simuler le comportement macroscopique structural de la fibrose près des cicatrices. La simulation d’une étude in silico de stimulation de TV en utilisant le modèle adapté personnalisé MS a été réalisée pour quantifier le risque de TV en termes de cartes d’inductibilité, de réentrées des modèles et de cartes de points de sortie. Une approche de modélisation pour l’ablation par RF fondée sur l’état de l’art a été proposée. Enfin, l’étude in silico de stimulation de TV a été appliquée aux données in vivo personnalisées des patients, qui ont suivi ce protocole. Ceci a permis une validation de la prévision in silico de TV post-infarctus par comparaison avec la TV clinique induite. Ler ôle de l’hétérogénéité spatiale des propriétés des tissus cardiaques estimés dans la genèse de TV ischémique a été évalué, ainsi que les caractéristiques des points de sortie, qui sont les candidats potentiels à l’ablation par RF. / Modelling cardiac electrophysiology for arrhythmias in silico has been an important research topic for the last decades. In order to translate this important progress into clinical applications, there is a requirement to make macroscopic models that can be used for the planning and guidance of clinical procedures. The objective of this thesis was to construct such macroscopic EP models specifict o each patient for study and prediction, in order to improve the planning and guidance of radio frequency ablation (RFA) the rapieson patients suffering from post infarction Ventricular Tachycardia (VT). In this work, we proposed a framework for the personalisation of a 3D cardiac EP model, the Mitchell-Schaeffer (MS) model, an devaluated its volumetric predictive power under various pacing scenarios.This was performed on ex vivo large porcine healthy heart susing Diffusion Tensor MRI (DT-MRI) and dense optical mapping data of the epicardium. This framework was then also applied to a clinical dataset derived from a hybrid XMR imaging and sparse electroanatomical mapping on a patient with heart failure. Next, the 3DMS model was also adapted to simulate the macroscopic structural behaviour of fibrosis near the scars. The simulation of an in silico VT stimulation study using the personalised adapted MS model was then performed, to quantify VT risk in terms of inducibility maps, re-entry patterns and exit point maps. A rule-based modelling approach for RF ablation lesions based on state of the art studies was proposed. Lastly, the in silico VT stimulation study was applied to in vivo personalised data of patients who underwent a clinical VT stimulation study. A validation of the in silico post-infarct VT prediction was performed against the clinically induced VT. Therole of spatial heterogeneity of the estimated patient’s cardiac tissue properties in the genesis of ischemic VT was learnt, along with their characteristics for entry/exit points, which are the potential candidates for RF ablation.

Scientific research is propelled by two objectives: Understanding and recognizing the essential biology of life, and deciphering this to uncover possible therapeutics in order to improve quality of life as well as relieve pain from disease. The aim of the work described in this thesis was to dissect the fundamental requirements of induced pluripotent stem cells both in pluripotency and differentiation with a particular focus on atrial specificity. Drug targeting of atrial-specific ion channels has been difficult because of lack of availability of appropriate cardiac cells, and preclinical testing studies have been carried out in non-cardiac cell lines, heterogeneous cardiac populations or animal models that have been unable to accurately represent human cardiomyocyte physiology. Therefore, we sought out to develop a preparation of cardiomyocytes showing an atrial phenotype with adult characteristics from human induced-pluripotent stem cells. A culture programme involving the use of Gremlin 2 allowed differentiation of cardiomyocytes with an atrial phenotype from human induced-pluripotent stem cells. When these differentiated cultures were dissociated into single myocytes a substantial fraction of cells showed a rod-shaped morphology with a single central nucleus that was broadly similar to that observed in cells isolated from atrial chambers of the heart. Immunolabelling of these myocytes for cardiac proteins (including RyR2 receptors, actinin-2, F-actin) showed striations with a sarcomere spacing of slightly less than 2um. The isolated rod-shaped cells were electrically quiescent unless stimulated to fire action potentials with an amplitude of 100 mV from a resting potential of approximately -70 mV. Proteins expressed included those for IK₁, IK_ur channels. Ca²⁺ Transients recorded from spontaneously beating cultures showed increases in amplitude in response to stimulation of adrenoceptors (both alpha and beta). With the aim of identifying key signaling mechanisms in directing cell fate, our new protocol allowed differentiation of human myocytes with an atrial phenotype and adult characteristics that show functional adrenoceptor signaling pathways and are suitable for investigation of drug effects.

L’automatisme cardiaque est généré par un mécanisme fondamental partiellement compris et controversé, initié par des cardiomyocytes spécialisés dans le nœud sino-atrial (NSA). Ces cellules pacemaker (cNSA) présentent une phase spontanée de dépolarisation diastolique (DD), qui mène le potentiel de membrane de la fin de la repolarisation du potentiel d’action (PA) au seuil de déclenchement du PA suivant. Cette activité spontanée implique plusieurs canaux ioniques à la surface de la membrane plasmique et la dynamique calcique intracellulaire. Les cardiomyocytes contractiles du myocarde expriment majoritairement le canal calcique Cav1.2 tandis que les cNSA en expriment d’autres isoformes. Ce sont les canaux calciques de type L (LTCC) Cav1.3 et de type T (TTCC) Cav3.1, qui sont impliqués dans la DD. Les souris génétiquement modifiées pour Cav1.3 et/ou Cav3.1 ont des caractéristiques physiopathologiques et sont utilisées comme modèle d’étude des dysfonctions sinusales de l’homme. La cartographie optique du NSA isolé a permis de révéler une activité électrophysiologique intrinsèque altérée par les mutations. L’expérimentation en patch clamp et en imagerie calcique des cNSA isolées montrent que les mutations altèrent la mécanistique cellulaire du pacemaker. Le couplage de ces approches à l’utilisation d’outils pharmacologiques spécifiques a permis d’évaluer la contribution des différents éléments à cette mécanistique cellulaire et de préciser les controverses sur les fondements de l’automatisme cardiaque. Cette thématique de recherche présente des enjeux majeurs dans le domaine de la santé puisque les perspectives thérapeutiques et les stratégies pharmacologiques pour traiter les dysfonctions sinusales nécessitent une connaissance intégrale du mécanisme. / Heart automaticity is generated by a basic pacemaker mechanism not fully understood and still controversial. Pacemaker activity is initiated by specialized cardiomyocytes in the Sino-atrial node (SAN). The spontaneous phase of diastolic depolarization (DDP) characterizes SAN cells (SANc). This phase drives the membrane potential of SANc from the end of the repolarization to the threshold of the next action potential (AP). This spontaneous activity involves several ion channels on the plasma membrane and the intracellular dynamic of calcium. In terms of calcium channels, atrial and ventricular cardiomyocytes express mostly Cav1.2 whereas SANc express two additional isoforms. Specifically, in SANc are expressed Cav1.3 LTCC (L type Calcium channels) and the Cav3.1 TTCC (T type Calcium channels), which are activated during the DD. Genetically modified mice inactivated for Cav1.3, Cav3.1 and Cav1.3/Cav3.1 we generated and used as a models of study of human SAN dysfunctions. In particular, we highlighted the impairment of the pacemaker activity in these mice by optical mapping of the intact SAN, and by patch clamping and calcium imaging of isolated SANc. Coupling this approaches with pharmacological tools allowed us to evaluating the contribution of the various elements constituting to the pacemaker mechanism. This thematic of research presents major issues in terms of public health. Indeed, we need a better understanding of the pacemaker mechanism to develop pharmacological strategies against SAN dysfunction.