Trigger versus Substrate: Multi-Dimensional Modulation of QT-Prolongation Associated Arrhythmic Dynamics by a hERG Channel Activator

Background: Prolongation of the QT interval of the electrocardiogram (ECG), underlain by prolongation of the action potential duration (APD) at the cellular level, is linked to increased vulnerability to cardiac arrhythmia. Pharmacological management of arrhythmia associated with QT prolongation is typically achieved through attempting to restore APD to control ranges, reversing the enhanced vulnerability to Ca²⁺-dependent afterdepolarisations (arrhythmia triggers) and increased transmural dispersion of repolarisation (arrhythmia substrate) associated with APD prolongation. However, such pharmacological modulation has been demonstrated to have limited effectiveness. Understanding the integrative functional impact of pharmacological modulation requires simultaneous investigation of both the trigger and substrate. Methods: We implemented a multi-scale (cell and tissue) in silico approach using a model of the human ventricular action potential, integrated with a model of stochastic 3D spatiotemporal Ca²⁺ dynamics, and parameter modification to mimic prolonged QT conditions. We used these models to examine the efficacy of the hERG activator MC-II-157c in restoring APD to control ranges, examined its effects on arrhythmia triggers and substrates, and the interaction of these arrhythmia triggers and substrates. Results: QT prolongation conditions promoted the development of spontaneous release events underlying afterdepolarisations during rapid pacing. MC-II-157c applied to prolonged QT conditions shortened the APD, inhibited the development of afterdepolarisations and reduced the probability of afterdepolarisations manifesting as triggered activity in single cells. In tissue, QT prolongation resulted in an increased transmural dispersion of repolarisation, which manifested as an increased vulnerable window for uni-directional conduction block. In some cases, MC-II-157c further increased the vulnerable window through its effects on INa. The combination of stochastic release event modulation and transmural dispersion of repolarisation modulation by MC-II-157c resulted in an integrative behavior wherein the arrhythmia trigger is reduced but the arrhythmia substrate is increased, leading to variable and non-linear overall vulnerability to arrhythmia. Conclusion: The relative balance of reduced trigger and increased substrate underlies a multi-dimensional role of MC-II-157c in modulation of cardiac arrhythmia vulnerability associated with prolonged QT interval

Tissue engineering of the human atrium : approaching mechanisms of genesis and control of atrial fibrillation

Cardiovascular disease is prevalent across the western world and is a major cause of morbidity and mortality, accounting for approximately a third of all fatalities. Investigating the heart by simulating its electrophysiology via the aid of mathematical models has advanced significantly over the past 60 years and is now a well established field. While much of the research focus is placed on the ventricles, the study of the atria is in comparison neglected. Therefore this Thesis is focused on the genesis and maintenance of atrial fibrillation (AF). A series of case studies are performed whereby established biophysically detailed mathematical models are implemented and modified to incorporate electrophysical alterations of atrial cells resulting from a variety of external conditions. The opening section of this Thesis is dedicated to developing a background to the field, including a discussion into the clinical aspect of the diagnosis and management of AF. The suitability of two atrial cell models is discussed and the development of single cell, 1D, 2D, and 3D multi-scale simulation protocols are described in detail. In addition measurements taken to quantify the arrhythmogenic properties of the cells susceptibility to AF are outlined. The second section is focused on the incorporation of conditions thought to enhance atrial tissues ability to initiate and maintain the genesis of AF. Included is a case study into the missence S140G gene mutation, and elevated physiological levels of the hormone Homocystein. The third section investigates the effectiveness of well established and widely used pharmacological treatments such as Beta-Blockers. In addition possible avenues of investigations for the development of atrial specific drugs are explored. These include blocking of the ultra rapid potassium channel and a more novel target for therapy via the targeting of 5HT4 receptors; which is transcribed solely in the atria and alters the electrophysical properties of the L-type Calcium current. The final part of this Thesis is dedicated to the development of a 2D atrial sheet model which includes electrical and spatial heterogeneities via the inclusion of multiple cell types and basic fiber orientation respectively. This allows for an investigation into the role that heterogeneities play in role genesis and maintenance of AF. The main finding of this Thesis is that alterations to the electrophysiology of atrial cells, due to external factors, can be successfully simulated via the implementation of mathematically detailed atrial cell models. It is concluded that simulations of the KENQ1 mutation and elevated levels of Homocystein successfully reproduce conditions which increase the onset of AF. Established treatments such as Beta-Blockers are found to have limited effectiveness. Possible theoretical treatments, such as the blocking of IKur, are found to provide a small amount of therapeutic benefit. In contrast, investigations into the effects of Serotonin were inconclusive. The study into the 2D atria indicated the importance that heterogeneities play in atria. The conclusions show that models provide a powerful tool when investigating how changes to electrophysiology of cells are manifested at a multi-scale level. The models also have their limitations and require further advancement to improve their accuracy.EThOS - Electronic Theses Online ServiceEPSRCGBUnited Kingdo

Studies on the dynamics of chaotic multi-wavelet reentrant propagation using a hybrid cellular automaton model of excitable tissue

There is a compelling body of evidence implicating continuous propagation (reentry) sustained by multiple meandering wavelets in the pathology of advanced human atrial fibrillation (AF). This forms the basis for many current therapies such as the Cox MAZE procedure and its derivatives, which aim to create non-conducting lesions in order to "transect" these circuits before they form. Nevertheless, our ability to successfully treat persistent and permanent AF using catheter ablation remains inadequate due to current limitations of clinical mapping technology as well as an incomplete understanding of how to place lesions in order to maximize circuit transection and, more importantly, minimize AF burden. Here, we used a hybrid cellular automaton model to study the dynamics of chaotic, multi-wavelet reentry (MWR) in excitable tissue. First, we used reentry as an exemplar to investigate a hysteretic disease mechanism in a multistable nonlinear system. We found that certain interactions with the environment can cause persistent changes to system behavior without altering its structure or properties, thus leading to a disconnect between clinical symptoms and the underlying state of disease. Second, we developed a novel analytical method to characterize the spatiotemporal dynamics of MWR. We identified a heterogeneous spatial distribution of reentrant pathways that correlated with the spatial distribution of cell activation frequencies. Third, we investigated the impact of topological and geometrical substrate alterations on the dynamics of MWR. We demonstrated a multi-phasic relationship between obstacle size and the fate of individual episodes. Notably, for a narrow range of sizes, obstacles appeared to play an active role in rapidly converting MWR to stable structural reentry. Our studies indicate that reentrant-pathway distributions are non-uniform in heterogeneous media (such as the atrial myocardium) and suggest a clinically measurable correlate for identifying regions of high circuit density, supporting the feasibility of patient-specific targeted ablation. Moreover, we have elucidated the key mechanisms of interaction between focal obstacles and MWR, which has implications for the use of spot ablation to treat AF as some recent studies have suggested

The role of cardiac MRI in the management of ventricular arrhythmias in ischaemic and non-ischaemic dilated cardiomyopathy

Ventricular tachycardia (VT) and VF account for the majority of sudden cardiac deaths worldwide. Treatments for VT/VF include anti-arrhythmic drugs, ICDs and catheter ablation, but these treatments vary in effectiveness and carry substantial risks and/or expense. Current methods of selecting patients for ICD implantation are imprecise and fail to identify some at-risk patients, while leading to others being overtreated. In this article, the authors discuss the current role and future direction of cardiac MRI (CMRI) in refining diagnosis and personalising ventricular arrhythmia management. The capability of CMRI with gadolinium contrast delayed-enhancement patterns and, more recently, T1 mapping to determine the aetiology of patients presenting with heart failure is well established. Although CMRI imaging in patients with ICDs can be challenging, recent technical developments have started to overcome this. CMRI can contribute to risk stratification, with precise and reproducible assessment of ejection fraction, quantification of scar and ‘border zone’ volumes, and other indices. Detailed tissue characterisation has begun to enable creation of personalised computer models to predict an individual patient’s arrhythmia risk. When patients require VT ablation, a substrate-based approach is frequently employed as haemodynamic instability may limit electrophysiological activation mapping. Beyond accurate localisation of substrate, CMRI could be used to predict the location of re-entrant circuits within the scar to guide ablation

Theroetical Analysis of Autonomic Nervous System Effects on Cardiac Elestrophysiology and its Relationship with Arrhythmic Risk

Las enfermedades cardiovasculares representan la principal causa de mortalidad y morbilidad en las sociedades industrializadas. Un porcentaje significativo de las muertes asociadas a estas enfermedades está relacionado con el desarrollo de arritmias cardíacas, siendo éstas definidas como anomalías en el funcionamiento eléctrico del corazón.Tres son los elementos principales que están involucrados en el desarrollo de las arritmias: un sustrato arritmogénico, un desencadenante y factores de modulación. El Sistema Nervioso Autónomo (SNA) es el más relevante de estos factores moduladores.El SNA está compuesto por dos ramas, simpática y parasimpática, que encierta medida actúan de forma antagónica entre sí. La posibilidad de revelar cómo el sistema nervioso simpático modula la actividad ventricular y participa en el desarrollo de arritmias, tal y como se ha observado experimentalmente, podría ser crucial para avanzar en el diseño de nuevas terapias clínicas dirigidas a prevenir o tratar estas anomalías rítmicas.Esta tesis investiga y analiza la variabilidad espacio-temporal de la repolarización ventricular humana, su modulación por el sistema nervioso simpático, los mecanismos que subyacen a incrementos notables en dicha variabilidad y la relación que existe con la generación de arritmias ventriculares. Para ello, se proponen metodología que combinan el procesado de señales ventriculares y el modelado in silico de miocitos ventriculares humanos. Los modelos in silico desarrollados incluyen descripciones teóricas acopladas de la electrofisiología, la dinámica del calcio, el estiramiento mecánico y la señalización -adrenérgica. Para tener en cuenta la variabilidad temporal(latido a latido) de la repolarización, se añade estocasticidad en las ecuaciones que definen la apertura y cierre de los canales iónicos de las principales corrientes activas durante la fase de repolarización del potencial de acción (AP), es decir, durante el retorno de la célula al estado de reposo después de una excitación. Por otro lado, para tener en cuenta la variabilidad espacial (célula a célula) de la repolarización, se construye y calibra una población de modelos representativos de diferentes características celulares utilizando para ellos datos experimentales disponibles. La investigación teórica y computacional de este estudio, combinada con el procesado de señales ventriculares tanto clínicas como experimentales, sienta las bases para futuros estudios que tengan como objetivo mejorar los métodos de estratificación del riesgo arrítmico y guiar la búsqueda de terapias antiarrítmicas más eficaces.En el Capítulo 2, se construye una población de modelos computacionales estocásticos representativos de células ventriculares humanas, los cuales se calibran experimentalmente.Estos modelos combinan la electrofisiología, la mecánica y la señalización-adrenérgica y se utizan para caracterizar de modo teórico la variabilidadespacio-temporal. La calibración de los modelos se basa en rangos experimentales de una serie de marcadores derivados del AP que describen su duración, amplitud y morfología.Mediante el uso de esta población de modelos estocásticos de AP se reproducenlas interacciones descritas experimentalmente entre un tipo particular de variabilidad temporal, asociada con las oscilaciones de baja frecuencia (LF) de la duración del AP (APD), y la variabilidad global latido a latido de la repolarización (BVR) en respuesta a un incremento de la actividad simpática. Además en este capítulo, se han estudiado los mecanismos iónicos que esán detrás de los incrementos simultáneos de ambos fenómenos y se ha demostrado que dichos mecanismos están asociados con la disminución de las corrientes rectificadora de entrada y rectificadora retardada rápida de K+ y a su vez de la corriente de Ca2+ tipo-L. Finalmente, se ha probado que niveles elevados de oscilaciones de baja frecuencia del APD y de BVR en ventrículos enfermosconducen a inestabilidades eléctricas y al desarrollo de eventos arritmogénicos.En el Capítulo 3, se investiga el retardo necesario para la manifestación de las oscilaciones LF del APD, como una forma particular de variabilidad de repolarización, en los miocitos ventriculares en respuesta a la provocación simpática. Mediante el uso de una población calibrada experimentalmente de modelos de AP ventriculares humanos, como en el Capítulo 2, se ha demostrado que esta latencia oscilatoria está asociada con la cinética lenta de fosforilación de la corriente rectificadora retardada lenta de K+ (IKs) en respuesta a la estimulación -adrenérgica. La estimulación previa de los receptores reduce sustancialmente el tiempo requerido para el desarrollo de oscilaciones de LF. Además, se ha demostrado que lapsos de tiempo cortos están íntimamente relacionados con mayores magnitudes oscilatorias del APD, medidas en elCapítulo 3, particularmente en células susceptibles de desarrollar eventos arritmogénicos en respuesta a la estimulación simpática.La calibración experimental de la población de modelos utilizados en los Capítulos 2 y 3 no garantiza que cada modelo de la población construida represente las medidas de un cardiomiocito ventricular humano individual. Es por esta razón que en el Capítulo 4 se desarrolla una metodología novedosa para construir poblaciones computacionales de modelos celulares ventriculares humanos que recapitulen más fielmente las evidencias experimentales disponibles. La metodología propuesta se basa en la formulación de representaciones estado-espacio no lineales y en el uso del filtro de Kalman (UKF) para la estimación de los parámetros y las variables de estado de un modelo AP estocástico subyacente para cada señal de potencial dada como entrada.Las pruebas realizadas sobre series de potencial sintéticas y experimentales demuestran que esta metodología permite establecer una correspondencia entre las trazas AP de entrada y los conjuntos de parámetros del modelo (conductancias de corriente iónicas) y las variables de estado (variables relacionadas con la apertura/cierre de los canales iónicos y concentraciones iónicas intracelulares). A su vez, se ha demostrado que la metodología propuesta es robusta y adecuada para la investigación de la variabilidad espacio-temporal en la repolarización ventricular humana.En el Capítulo 5 se proponen varias mejoras a la metodología desarrollada en elCapítulo 4 para estimar con mayor precisión los parámetros y las variables de estado de los modelos estocásticos de células ventriculares humanas a partir de señales individuales de AP dadas como entradas, y a su vez para reducir el tiempo de convergencia a fin de proporcionar una estimación más rápida. Las mejoras se han basado en el uso combinado del método UKF, presentado en el Capítulo 4, junto con el método Double Greedy Dimension Reduction (DGDR) con generación automática de biomarcadores.Además de estimar las conductancias de las corrientes iónicas en condiciones basales, el enfoque presentado en este capítulo también proporciona el conjunto de niveles de fosforilación inducidos por la estimulación -adrenérgica, contribuyendo así al análisis de patrones de repolarización espacio-temporal con y sin modulación autonómica.En conclusión, esta tesis presenta novedosas metodologías enfocadas hacia lacaracterización de la variabilidad espacio-temporal de la repolarización ventricular humana, el análisis de sus mecanismos subyacentes y la determinaci´ón de la relación entre aumentos en la variabilidad y el mayor riesgo de sufrir arritmias ventriculares y muerte súbita cardíaca. Se desarrollan conjuntos de modelos computacionales estocásticos celulares humanos con representación de la electrofisiología ventricular, la mecánica y la señalización -adrenérgica para analizar la variabilidad global de larepolarización, latido a latido y célula a célula, así como de un tipo particular de variabilidad en forma de oscilaciones de baja frecuencia. Para reproducir fielmente los patrones de variabilidad medidos experimentalmente de manera individual, se proponen metodologías para construir poblaciones de modelos AP ventriculares humanos donde los parámetros y las variables de estado de cada modelo se estiman a partir de una serie de potencial de entrada dada. Estos modelos personalizados abren la puerta a una investigación más robusta de las causas y consecuencias de la variabilidad espacio-temporal de la repolarización ventricular humanCardiovascular diseases represent the main cause of mortality and morbidity in industrialized societies. A significant percentage of deaths associated with these diseases is related to the generation of cardiac arrhythmias, defined as abnormalities in the electrical functioning of the heart. Three major elements are involved in the development of arrhythmias, which include an arrhythmogenic substrate, a trigger and modulating factors. The Autonomic Nervous System (ANS) is the most relevant of these modulators. The ANS is composed of two branches, sympathetic and parasympathetic, which to a certain extent act antagonistically to each other. The possibility of revealing how the sympathetic nervous system modulates the activity of the ventricles (lower heart chambers) and participates in the development of arrhythmias, as reported experimentally, could be crucial to advance in the design of new clinical therapies aimed at preventing or treating these rhythm abnormalities. This thesis investigates spatio-temporal variability of human ventricular repolarization, its modulation by the sympathetic nervous system, the mechanisms behind highly elevated variability and the relationship to the generation of ventricular arrhythmias. To that end, methodologies combining signal processing of ventricular signals and in silico modeling of human ventricular myocytes are proposed. The developed in silico models include coupled theoretical descriptions of electrophysiology, calcium dynamics, mechanical stretch and -adrenergic signaling. To account for temporal (beat-to-beat) repolarization variability, stochasticity is added into the equations defining the gating of the ion channels of the main currents active during action potential (AP) repolarization, i.e. during the return of the cell to the resting state after an excitation. To account for spatial (cell-to-cell) repolarization variability, a population of models representative of different cellular characteristics are constructed and calibrated based on available experimental data. The theoretical computational research of this study, combined with the processing of clinical and experimental ventricular signals, lays the ground for future studies aiming at improving arrhythmic risk stratification methods and at guiding the search for more efficient anti-arrhythmic therapies. In Chapter 2, a population of experimentally-calibrated stochastic human ventricular computational cell models coupling electrophysiology, mechanics and -adrenergic signaling are built to investigate spatio-temporal variability. Model calibration is based on experimental ranges of a number of AP-derived markers describing AP duration, amplitude and shape. By using the proposed population of stochastic AP models, the experimentally reported interactions between a particular type of temporal variability associated with low-frequency (LF) oscillations of AP duration (APD) and overall beat-to-beat variability of repolarization (BVR) in response to enhanced sympathetic activity are reproduced. Ionic mechanisms behind correlated increments in both phenomena are investigated and found to be related to downregulation of the inward and rapid delayed rectifier K+ currents and the L-type Ca2+ current. Concomitantly elevated levels of LF oscillations of APD and BVR in diseased ventricles are shown to lead to electrical instabilities and arrhythmogenic events. In Chapter 3, the time delay for manifestation of LF oscillations of APD, as a particular form of repolarization variability, is investigated in ventricular myocytes in response to sympathetic provocation. By using an experimentally-calibrated population of human ventricular AP models, as in Chapter 2, this oscillatory latency is demonstrated to be associated with the slow phosphorylation kinetics of the slow delayed rectifier K+ current IKs in response to -adrenergic stimulation. Prior stimulation of -adrenoceptors substantially reduces the time required for the development of LF oscillations. In addition, short time lapses are shown to be related to large APD oscillatory magnitudes, as measured in Chapter 2, particularly in cells susceptible to develop arrhythmogenic events in response to sympathetic stimulation. The experimental calibration of the population of models used in Chapter 2 and Chapter 3, despite ensuring that simulated population measurements lie within experimental limits, does not guarantee that each model in the constructed population represents the experimental measurements of an individual human ventricular cardiomyocyte. It is for that reason that in Chapter 4 a novel methodology is developed to construct computational populations of human ventricular cell models that more faithfully recapitulate individual available experimental evidences. The proposed methodology is based on the formulation of nonlinear state-space representations and the use of the Unscented Kalman Filter (UKF) to estimate parameters and state variables of an underlying stochastic AP model given any input voltage trace. Tests performed over synthetic and experimental voltage traces demonstrate that this methodology successfully renders a one-to-one match between input AP traces and sets of model parameters (ionic current conductances) and state variables (ionic gating variables and intracellular concentrations). The proposed methodology is shown to be robust for investigation of spatio-temporal variability in human ventricular repolarization. Chapter 5 improves the methodology developed in Chapter 4 to more accurately estimate parameters and state variables of stochastic human ventricular cell models from individual input voltage traces and to reduce the converge time so as to provide faster estimation. The improvements are based on the combined use of the UKF method of Chapter 4 together with Double Greedy Dimension Reduction (DGDR) method with automatic generation of biomarkers. Additionally, on top of estimating ionic current conductances at baseline conditions, the approach presented in this chapter also provides a set of -adrenergic-induced phosphorylation levels, thus contributing to the analysis of spatio-temporal repolarization patterns with and without autonomic modulation. In conclusion, this thesis presents novel methodologies for characterization of spatio-temporal variability of human ventricular repolarization, for dissection of its underlying mechanisms and for ascertainment of the relationship between elevated variability and increased risk for ventricular arrhythmias and sudden cardiac death. Sets of stochastic human computational cell models with representation of ventricular electrophysiology, mechanics and -adrenergic signaling are developed and used to analyze overall beat-to-beat and cell-to-cell repolarization variability as well as a particular type of variability in the form of LF oscillations. To faithfully reproduce experimentally measured variability patterns in a one-to-one manner, methodologies are proposed to construct populations of human ventricular AP models where the parameters and state variables of a model are estimated from a given input voltage trace. These personalized models open the door to more robust investigation of the causes and consequences of spatio-temporal variability of human ventricular repolarization.<br /

Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges

The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology

Development of a medium-high throughput electrophysiology method to study cellular heterogeneity in the rabbit heart

Sudden cardiac death (SCD) is a prominent cause of death worldwide today, mainly occurring as a result of coronary heart disease, cardiomyopathies, and inherited or induced arrhythmia syndromes. Survival following sudden cardiac arrest (SCA) has improved in the past decades, but the majority of cases of SCD remain unwitnessed. Although advances have been made towards the investigation of the mechanisms behind SCD, it remains a poorly understood phenomenon. Environmental factors have been identified and associated with increased arrhythmic risk, and most prominently, drug-induced arrhythmias constitute a serious hurdle to both cardiac and non-cardiac drug development. The past decade has seen pro-arrhythmic screening of new compounds become routine, and develop into a major point of interest for drug development. Specifically, the onset of drug-induced polymorphic ventricular tachycardia, such as torsade de pointes (TdP), is of particular interest to cardiac research. The concept of electrophysiological heterogeneity in cardiac muscle holds exciting potential for explaining the pathophysiology of TdP, but quantifying cellular heterogeneity using conventional methods is a challenge. This work developed and refined a fluorescence-based, medium/high-throughput electrophysiological assay to process large cell populations (~50-500 cells) from single hearts. Using this novel approach, transmural electrophysiological differences were found between regions of individual hearts, replicating published work with a 3 to 4-fold reduction in hearts sampled, and additionally providing a previously unknown quantification of cellular heterogeneity in isolated cardiomyocyte populations, in both healthy and failing rabbit hearts. Further classification of electrophysiological differences within smaller regions of the ventricle yielded evidence of repolarisation gradients across the myocardium, with vast overlap in repolarisation duration, challenging the dogma of region-specific repolarisation duration. Lastly, by specifically blocking hERG channels and L-type calcium channels in cardiac subregions (sub-epicardial apex and base) strong evidence was found for heterogeneous electrophysiology response amongst isolated cell populations. Specifically, sub-epicardial action potential shortening using nifedipine was strongly APD dependent, whereby baseline AP duration determined the extent of APD shortening via drug-induced ICa-L blockade. Sub-epicardial AP prolongation mediated via IKr block using dofetilide also produced non-homogeneous cell response in the form of two distinct population responses: (i) The majority (~85%) was made up of normal responding cells, experiencing ~20-30ms AP prolongation not dependent on baseline APD (P100ms AP prolongation, beyond the pacing cycle length (>500ms) without any evidence of early-afterdepolarisations. Large experimental samples of AP parameters gathered in this study can provide real-world data parameter space ranges for mathematical model development, showing that ion channel conductance ranges used today to predict drug responses at the organ level may be too restrictive, or inaccurate. Iterative model adjustment using large experimental datasets can help constrain models and improve their predictive power, saving time by reducing computational power required

Computer modeling and signal analysis of cardiovascular physiology

This dissertation aims to study cardiovascular physiology from the cellular level to the whole heart level to the body level using numerical approaches. A mathematical model was developed to describe electromechanical interaction in the heart. The model integrates cardio-electrophysiology and cardiac mechanics through excitation-induced contraction and deformation-induced currents. A finite element based parallel simulation scheme was developed to investigate coupled electrical and mechanical functions. The developed model and numerical scheme were utilized to study cardiovascular dynamics at cellular, tissue and organ levels. The influence of ion channel blockade on cardiac alternans was investigated. It was found that the channel blocker may significantly change the critical pacing period corresponding to the onset of alternans as well as the alternans’ amplitude. The influence of electro-mechanical coupling on cardiac alternans was also investigated. The study supported the earlier assumptions that discordant alternans is induced by the interaction of conduction velocity and action potential duration restitution at high pacing rates. However, mechanical contraction may influence the spatial pattern and onset of discordant alternans. Computer algorithms were developed for analysis of human physiology. The 12-lead electrocardiography (ECG) is the gold standard for diagnosis of various cardiac abnormalities. However, disturbances and mistakes may modify physiological waves in ECG and lead to wrong diagnoses. This dissertation developed advanced signal analysis techniques and computer software to detect and suppress artifacts and errors in ECG. These algorithms can help to improve the quality of health care when integrated into medical devices or services. Moreover, computer algorithms were developed to predict patient mortality in intensive care units using various physiological measures. Models and analysis techniques developed here may help to improve the quality of health care

Circ Res

Atrial fibrillation (AF) is the most common sustained arrhythmia in humans. The mechanisms that govern AF initiation and persistence are highly complex, of dynamic nature, and involve interactions across multiple temporal and spatial scales in the atria. This article aims to review the mathematical modeling and computer simulation approaches to understanding AF mechanisms and aiding in its management. Various atrial modeling approaches are presented, with descriptions of the methodological basis and advancements in both lower-dimensional and realistic geometry models. A review of the most significant mechanistic insights made by atrial simulations is provided. The article showcases the contributions that atrial modeling and simulation have made not only to our understanding of the pathophysiology of atrial arrhythmias, but also to the development of AF management approaches. A summary of the future developments envisioned for the field of atrial simulation and modeling is also presented. The review contends that computational models of the atria assembled with data from clinical imaging modalities that incorporate electrophysiological and structural remodeling could become a first line of screening for new AF therapies and approaches, new diagnostic developments, and new methods for arrhythmia prevention.DP1 HL123271/HL/NHLBI NIH HHS/United StatesDP1HL123271/DP/NCCDPHP CDC HHS/United States2015-04-25T00:00:00Z24763468PMC4043630vault:242