Machine Learning approach for TWA detection relying on ensemble data design

Background and objective: T-wave alternans (TWA) is a fluctuation of the ST–T complex of the surface electrocardiogram (ECG) on an every–other–beat basis. It has been shown to be clinically helpful for sudden cardiac death stratification, though the lack of a gold standard to benchmark detection methods limits its application and impairs the development of alternative techniques. In this work, a novel approach based on machine learning for TWA detection is proposed. Additionally, a complete experimental setup is presented for TWA detection methods benchmarking. Methods: The proposed experimental setup is based on the use of open-source databases to enable experiment replication and the use of real ECG signals with added TWA episodes. Also, intra-patient overfitting and class imbalance have been carefully avoided. The Spectral Method (SM), the Modified Moving Average Method (MMA), and the Time Domain Method (TM) are used to obtain input features to the Machine Learning (ML) algorithms, namely, K Nearest Neighbor, Decision Trees, Random Forest, Support Vector Machine and Multi-Layer Perceptron. Results: There were not found large differences in the performance of the different ML algorithms. Decision Trees showed the best overall performance (accuracy 0.88 ± 0.04, precision 0.89 ± 0.05, Recall 0.90± 0.05, F1 score 0.89± 0.03). Compared to the SM (accuracy 0.79, precision 0.93, Recall 0.64, F1 score 0.76) there was an improvement in every metric except for the precision. Conclusions: In this work, a realistic database to test the presence of TWA using ML algorithms was assembled. The ML algorithms overall outperformed the SM used as a gold standard. Learning from data to identify alternans elicits a substantial detection growth at the expense of a small increment of the false alarm.Universidad de Alcal

Microvolt T-Wave Alternans Physiological Basis, Methods of Measurement, and Clinical Utility—Consensus Guideline by International Society for Holter and Noninvasive Electrocardiology

This consensus guideline was prepared on behalf of the International Society for Holter and Noninvasive Electrocardiology and is cosponsored by the Japanese Circulation Society, the Computers in Cardiology Working Group on e-Cardiology of the European Society of Cardiology, and the European Cardiac Arrhythmia Society. It discusses the electrocardiographic phenomenon of T-wave alternans (TWA) (i.e., a beat-to-beat alternation in the morphology and amplitude of the ST- segment or T-wave). This statement focuses on its physiological basis and measurement technologies and its clinical utility in stratifying risk for life-threatening ventricular arrhythmias. Signal processing techniques including the frequency-domain Spectral Method and the time-domain Modified Moving Average method have demonstrated the utility of TWA in arrhythmia risk stratification in prospective studies in >12,000 patients. The majority of exercise-based studies using both methods have reported high relative risks for cardiovascular mortality and for sudden cardiac death in patients with preserved as well as depressed left ventricular ejection fraction. Studies with ambulatory electrocardiogram-based TWA analysis with Modified Moving Average method have yielded significant predictive capacity. However, negative studies with the Spectral Method have also appeared, including 2 interventional studies in patients with implantable defibrillators. Meta-analyses have been performed to gain insights into this issue. Frontiers of TWA research include use in arrhythmia risk stratification of individuals with preserved ejection fraction, improvements in predictivity with quantitative analysis, and utility in guiding medical as well as device-based therapy. Overall, although TWA appears to be a useful marker of risk for arrhythmic and cardiovascular death, there is as yet no definitive evidence that it can guide therapy

Quantification of Ventricular Repolarization Dispersion Using Digital Processing of the Surface ECG

Digital processing of electrocardiographic records was one of the first applications of signal processing on medicine. There are many ways to analyze and study electrical cardiac activity using the surface electrocardiogram (ECG) and nowadays a good clinical diagnostic and prevention of cardiac risk are the principal goal to be achieved. One aim of digital processing of ECG signals has been quantification of ventricular repolarization dispersion (VRD), phenomenon which mainly is determined by heterogeneity of action potential durations (APD) in different myocardial regions. The APD differs not only between myocytes of apex and the base of both ventricles, but those of endocardial and epicardial surfaces (transmural dispersion) and between both ventricles. Also, it was demonstrated that several electrophysiologically and functionally different myocardial cells, like epicardial, endocardial and mid-myocardial M cells. The APD inequalities develop global and/or local voltage gradients that play an important role in the inscription of ECG T-wave morphology. In this way, we can assume that T-wave is a direct expression of ventricular repolarization inhomogeneities on surface ECG. Experimental and clinical studies have demonstrated a relationship between VRD and severe ventricular arrhythmias. In addition, patients having increased VRD values have a higher risk of developing reentrant arrhythmias. Frequently the heart answer to several pathological states produced an increase of VRD; this phenomenon may develop into malignant ventricular arrhythmia (MVA) and/or sudden cardiac death (SCD). Moreover, it has been showed that the underlying mechanisms in MVA and/or SCD are cardiac re-entry, increased automation, influence of autonomic nervous system and arrhythmogenic substrates linked with cardiac pathologies. These cardiac alterations could presented ischemia, hypothermia, electrolyte imbalance, long QT syndrome, autonomic system effects and others. Digital processing of ECG has been proved to be useful for cardiac risk assessment, with additional advantages like of being non invasive treatments and applicable to the general population. With the aim to identify high cardiac risk patients, the researchers have been tried to quantify the VRD with different parameters obtained by mathematic-computational processing of the surface ECG. These parameters are based in detecting changes of T-wave intervals and T-wave morphology during cardiac pathologies, linking these changes with VRD. In this chapter, we have presented a review of VRD indexes based on digital processing of ECG signals to quantify cardiac risk. The chapter is organized as follows: Section 2 explains ECG preprocessing and delineation of fiducial points. In Section 3, indexes of VRD quantification, such as: QT interval dispersion, QT interval variability and T-wave duration, are described. In Section 4, different repolarization indexes describing T-wave morphology and energy are examined, including complexity of repolarization, T-wave residuum, angle between the depolarization and repolarization dominant vectors, micro T-wave alternans, T-wave area and amplitude and T-wave spectral variability. Finally, in Section 5 conclusions are presented.Fil: Vinzio Maggio, Ana Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; ArgentinaFil: Bonomini, Maria Paula. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Ingeniería Biomédica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Laciar Leber, Eric. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería; ArgentinaFil: Arini, Pedro David. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Ingeniería Biomédica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; Argentin

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

Assessment of ventricular repolarization instability and cardiac risk stratification in different pathological and abnormal conditions

Cardiovascular diseases (CVDs) represents the leading cause of mortality worldwide [1,2]. These pathological conditions are mainly characterized by a structurally abnormal heart, that is, a vulnerable substrate, prone to the abnormal generation and/or propagation of the electrical impulse, determining the onset of ventricular arrhythmias, which can result in sudden cardiac death (SCD) [3]. In this context, the assessment of ventricular repolarization from the electrocardiogram (ECG) signal has been shown to provide with valuable information for risk stratification and several electrocardiographic indices have been proposed in the literature [4]. The main objective of this thesis is to propose methodological advances for the assessment of ventricular repolarization instability in pathological and abnormal conditions. These contributions are aimed at improving the prediction of ventricular arrhythmias and, consequently, better identifying SCD risk. In particular, we have addressed this objective by developing robust methodologies for the assessment of T-wave alternans (TWA) and ventricular repolarization instability, in invasive and non-invasive cardiac signals, that have been evaluated in both experimental and clinical conditions. In the first part of the thesis, TWA was simultaneously characterized (prevalence, magnitude, time-course, and alternans waveform) in body-surface ECG and intracardiac electrograms (EGMs) signals during coronary artery occlusion. Signals from both body surface ECG and intracardiac EGMs recorded from 4 different anatomical heart locations (coronary sinus, epicardial space and left and right ventricles) were analyzed following a multilead strategy. Leads were linearly combined using the periodic component analysis (πCA) [5], which maximizes the 2-beat periodicity (TWA periodicity) content present on the available leads. Then the Laplacian Likelihood Ratio method (LLRM) [6] was applied for TWA detection and estimation. A sensitivity study for TWA detection from the 5 different locations of leads was performed, revealing that it is the combination of the ECG leads that better performs. In addition, this multilead approach allowed us to find the optimal combination of intracardiac leads usable for in-vivo monitorization of TWA directly from an implantable device, with a sensitivity comparable to the ECG analysis. These results encourage further research to determine the feasibility of predicting imminent VT/VF episodes by TWA analysis implemented in implantable cardioverter defibrillator’s (ICD) technology.Then, we have studied the potential changes induced by a prolonged exposure to simulated microgravity on ventricular repolarization in structurally normal hearts. It is well known that this environmental condition affects the control of autonomic and cardiovascular systems [7], with a potential increase on cardiac electrical instability. The effects of short- (5 days), mid- (21 days) and long- (60 days) exposure to simulated microgravity on TWA using the head-down bed-rest (HDBR) model [8] were assessed. TWA was evaluated before (PRE), during and after (POST) the immobilization period, by the long-term averaging technique in ambulatory ECG Holter recordings [9]. Additionally, we proposed an adapted short-term averaging approach for shorter, non-stationary ECG signals obtained during two stress manoeuvres (head-up tilt-table and bicycle exercise tests). Both approaches are based on the multilead analysis used in the previous study. The absence of significant changes between PRE and POST-HDBR on TWA indices suggests that a long-term exposure to simulated microgravity is not enough to induce alterations in healthy myocardial substrate up to the point of reflecting electrical instability in terms of TWA on the ECG. Finally, methodological advances were proposed for the assessment of ventricular repolarization instability from the ECG signal in the presence of sporadic (ventricular premature contractions, VPCs) and sustained (atrial fibrillation) rhythm disturbances.On the one hand, a methodological improvement for the estimation of TWA amplitude in ambulatory ECG recordings was proposed, which deals with the possible phase reversal on the alternans sequence induced by the presence of VPCs [10]. The performance of the algorithm was first evaluated using synthetic signals. Then, the effect of the proposed method in the prognostic value of TWA amplitude was assessed in real ambulatory ECG recordings from patients with chronic heart failure (CHF). Finally, circadian TWA changes were evaluated as well as the prognostic value of TWA at different times of the day. A clinical study demonstrated the enhancement in the predictive value of the index of average alternans (IAA) [9] for SCD stratification. In addition, results suggested that alternans activity is modulated by the circadian pattern, preserving its prognostic information when computed just during the morning, which is also the day interval with the highest reported SCD incidence. Thus, suggesting that time of the day should be considered for SCD risk prediction. On the other hand, the high irregularity of the ventricular response in atrial fibrillation (AF) limits the use of the most common ECG-derived markers of repolarization heterogeneity, including TWA, under this clinical condition [11]. A new method for assessing ventricular repolarization changes based on a selective averaging technique was developed and new non-invasive indices of repolarization variation were proposed. The positive impact in the prognostic value of the computed indices was demonstrated in a clinical study, by analyzing ECG Holter recordings from CHF patients with AF. To the best of our knowledge, this is the first study that attempts a non-invasive SCD stratification of patients under AF rhythm by assessing ventricular repolarization instability from the ECG signal. To conclude, the research presented in this thesis sheds some light in the identification of pro-arrhythmic factors, which plays an important role in adopting efficient therapeutic strategies. In particular, the optimal configuration for real-time monitoring of repolarization alternans from intracardiac EGMs, together with the prognostic value of the proposed non-invasive indices of alternans activity and ventricular instability variations in case of AF rhythms demonstrated in two clinical studies, would increase the effectiveness of (ICD) therapy. Finally, the analysis of ECG signals recorded during HDBR experiments in structurally healthy hearts, also provides interesting information on cardiovascular alterations produced in immobilized or bedridden patients.<br /

Investigation of Absolute Refractory Period Pacing to Prevent Lethal Arrhythmias in Humans

Sudden cardiac death (SCD) is a major health issue, being the commonest cause of natural death in the industrialised world. SCD frequently results from the development of erratic heart rhythms which are usually preceded by repolarisation alternans (RA). Previous studies suggest that the abolishment of RA may prevent the onset of arrhythmia. In a recent swine study, absolute refractory period pacing (ARPP) showed promising results in RA modulation. However, the cellular mechanisms underlying this therapy and its efficiency in human patients remains unclear. Single cell in silico modelling showed that ARPP might be used to both increase or decrease action potential duration (APD) with the degree of modulation depending mainly on stimulus duration, magnitude and coupling interval. ICaL, IKr and IK1 were the main currents involved, and conductance of Ito and ICaL strongly influenced results. APD alternans was successfully reduced in a population of alternating models. In vivo results obtained using an epicardial sock during cardiac surgery showed significant changes in repolarisation when applying ARPP. However, elevated morphological signal alterations led to question the results’ validity. The investigation of signal processing methodology led to the acknowledgement of high-pass filter interference in signal morphology due to the ARPP artefact, resulting in altered markers. Further in vivo data showed no significant effect of ARPP on local RT at the whole heart level. Small effects on RT, spectral method and Tend markers close to the pacing site were observed, suggesting a localised effect. One dimensional in silico modelling showed a rapid decline of the ARPP effect, being limited to around 10mm from the pacing site, correlating with the in vivo results. These results provide important new knowledge regarding the effects of ARPP in the human ventricle at the cellular and organ level. It also provides relevant information for further development, analysis and translation of pacing based therapies

Prediction of Cardiac Death Risk by Analysis of Ventricular Repolarization Restitution from the Electrocardiogram Signal

Las enfermedades cardiovasculares siguen siendo la mayor causa de muertes en todo el mundo, y se espera que el número de casos crezca progresivamente en los próximos años con el envejecimiento de la población. Por ello, se necesitan marcadores no invasivos con alta capacidad de predicción de muerte para reducir la incidencia de estos eventos fatales.La insuficiencia cardiaca crónica (CHF, del inglés "Chronic Heart Failure") describe la condición por la cual el corazón no es capaz de bombear suficiente sangre para alcanzar las demandas del cuerpo. Se ha demostrado que los pacientes con CHF pueden experimentar un empeoramiento progresivo de los síntomas, pudiendo llegar a producirse la muerte por fallo de bomba (PFD, del inglés "Pump Failure Death"), o sufrireventos arrítmicos malignos que lleven a la muerte súbita cardiaca (SCD, del inglés "Sudden Cardiac Death"). Uno de los factores electro-fisiológicos con mayor influencia en la generación de arritmias malignas es el aumento de la dispersión de la repolarización, o la variación espacio-temporal en los tiempos de repolarización. También se ha demostrado que la respuesta de esta dispersión a variaciones en el ritmo cardiaco, es decir, la dispersión de la restitución de la repolarización, está relacionada con mayor riesgo arrítmico y de SCD. Por otro lado, el empeoramiento de CHF se manifiesta con una reducción de la respuesta de los ventrículos a la estimulación autonómica, y con un balance simpato-vagal anormal. Con la llegada de los defibriladores cardioversores implantables (ICDs, del inglés "Implantable Cardioverter Defibrillators"), y de la terapia de resincronización cardiaca (CRT, del inglés "Cardiac Resynchronization Therapy"), los dos dispositivos más popularmente usados en la práctica clínica para prevenir SCD y PFD, respectivamente, la estratificación de riesgo se ha vuelto muy relevante. Específicamente, ser capaces de predecir el evento potencial que un paciente con CHF podría sufrir (SCD, PFD u otras causas) es de gran importancia. La señal de electrocardiograma (ECG) es un método barato y no invasivo que contiene información importante acerca de la actividad eléctrica del corazón.El objetivo principal de esta tesis es desarrollar marcadores de riesgo derivados del ECG que caractericen la restitución de la repolarización ventricular para mejorar la predicción de SCD y PFD en pacientes con CHF. Para ello, se han utilizado, por un lado, índices basados en intervalos temporales, como los intervalos QT y Tpe, ya que las dinámicas de estos intervalos están asociadas con la restitución de la repolarización, y con su dispersión, respectivamente, y, por el otro lado, índices basados en la morfología de la onda T. Para utilizar la información de la morfología, se ha desarrollado una metodología innovadora que permite la comparación de dos formas diferentes, y la cuantificación de sus diferencias.En el capítulo 2 se desarrolló un algoritmo completamente automático para estimar la pendiente y la curvatura de las dinámicas de los intervalos QT y Tpe a partir de registros ECG Holter de 24 horas de 651 pacientes con CHF. A continuación, se estudió la modulación del patrón circadiano de las estimaciones propuestas, y se evaluó su valor predictivo de SCD y PFD. Finalmente, se estudió la capacidad de clasificación del marcador analizado con mayor valor predictivo, individualmente y en combinación con otros dos marcadores de riesgo de ECG previamente propuestos, que reflejan mecanismos electro-fisiológicos y autonómicos. Los resultados demostraron que la dispersión de la restitución de la repolarización, cuantificada a partir de la pendiente de la dinámica del intervalo Tpe, tiene valor predictivo de SCD y de PFD, con pendientes altas indicativas de sustrato arrímico predisponiendo a SCD y pendientes planas indicativas de fatiga mecánica del corazón predisponiendo a PFD. Sin embargo, la pendiente de la restitución de la repolarización, cuantificada como la pendiente de la relación QT/RR, así como los parámetros de curvatura de las dos relaciones, no mostraron asociación con ningún tipo de muerte cardiaca. El patrón circadiano moduló estos parámetros, con valores significativamente mayores durante el día que durante la noche. Finalmente, los resultados de clasificación probaron que la combinación de los marcadores de riesgo derivados del ECG que reflejan información complementaria mejora la discriminación entre SCD, PFD y otros pacientes. Nuestros resultados sugieren que la pendiente de la dinámica del intervalo Tpe podría incluirse en la práctica clínica como herramienta para estratificar pacientes de acuerdo a su riesgo de sufrir SCD o PFD y, por lo tanto, aumentar el beneficio del tratamiento con ICDs o CRT.Considerando estos resultados, postulamos a continuación que la morfología de la onda T contiene información adicional, no tenida en cuenta al usar únicamente índices basados en intervalos temporales. Por lo tanto, en el capítulo 3 desarrollamos una metodología para comparar la morfología de dos ondas T, y propusimos y evaluamos la capacidad de nuevos marcadores derivados del ECG para cuantificar variaciones en la morfología de la onda T. Primero, comparamos la capacidad de eliminar la variabilidad en el dominio temporal de dos algoritmos, "Dynamic Time Warping" (DTW) y "Square-root Slope Function" (SRSF). Luego, se propusieron índices morfológicos y se evaluó su robustez ante la presencia de ruido aditivo con señales generadas sintéticamente. A continuación, se utilizó un modelo electrofisiológico cardiaco para investigarla relación entre los índices de variabilidad morfológica de onda T y los cambios morfológicos a nivel celular. Finalmente, se cuantificaron las variaciones en la morfología de la onda T producidas por una prueba de tabla basculante en registros de ECG con los marcadores propuestos y se estudió su correlación con el ritmo cardiaco y otros marcadores tradicionales. Nuestros resultados mostraron que SRSF fue capaz de separarlas variaciones en el tiempo y en la amplitud de la onda T. Además, los marcadores propuestos de variabilidad morfológica probaron ser robustos frente a ruido aditivo Laplaciano y demostraron reflejar variaciones en la dispersión de la repolarización a nivel celular en simulación y en registros de ECG reales. En conclusión, los índices propuestos que cuantifican variaciones morfológicas de la onda T han demostrado un gran potential para ser usados como predictores de riesgo arrítmico.En el capítulo 4, se exploró la restitución de la repolarización ventricular usando los índices de variabilidad morfológica presentados en el capítulo 3. Bajo la hipótesis de que la morfología de la onda T refleja la dispersión de la repolarización, hipotetizamos que la restitución de la morfología de la onda T reflejaría la dispersión de la restitución de la repolarización. Por lo tanto, calculamos la pendiente de la restituciónde la morfología de la onda T y evaluamos su valor predictivo de SCD y PFD. También estudiamos, como en el capítulo 2, la modulación del patrón circadiano y la capacidad de clasificación. Los resultados mostraron que la dispersión de la restitución de la repolarización cuantificada a través de la pendiente de la restitución de la morfología de la onda T, estaba asociada específicamente con SCD, sin ninguna relación con PFD. El patrón circadiano también moduló la restitución de la morfología de la onda T, con valores significativamente mayores durante el día que durante la noche. Finalmente, los resultados de clasificación también mejoraron al utilizar una combinación de marcadores de riesgo derivados del ECG. En conclusión, la pendiente de la restitución de la morfología de la onda T podría usarse en la práctica clínica como herramienta para definir una población de alto riesgo de SCD que podría beneficiarse de implantación con ICDs.Finalmente, aunque lo deseable es encontrar un índice individual con alto valor predictivo, los eventos de SCD y PFD son el resultado de una múltiple cadena de mecanismos. Por lo tanto, la predicción podría mejorarse todavía más si se usara un marcador que integrara varios factores de riesgo. En el capítulo 5 se propusieron modelos clínicos, basados en el ECG y otros combinando ambos tipos de variables, para predecir específicamente riesgo de SCD y de PFD. Además, se comparó su valor predictivo. Los modelos clínicos, basados en ECG y combinado demostraron mejorar la predicción de SCD y de PFD, comparado con los marcadores individuales. Para SCD, la combinación de variables clínicas y derivadas del ECG mejoró sustancialmente la predicción de riesgo, comparado con el uso de uno de los dos tipos de variables. Sinembargo, la predicción de riesgo de PFD demostró ser óptima al utilizar el modelo derivado del ECG, ya que la combinación con variables clínicas no añadió ninguna información predictiva de PFD. Nuestros resultados confirman la necesidad de utilizar un índice multi-factorial, que incluya información de mecanismos complementarios, para optimizar la estratificación de riesgo de SCD y de PFD.En conclusión, en esta tesis se han propuesto dos índices derivados del ECG, que reflejan dispersión de la restitución de la repolarización, y se ha demostrado su valor predictivo de SCD y PFD. Cada índice explota información diferente de la onda T, uno utiliza el intervalo Tpe y el otro utiliza la morfología completa de la onda T. Para la cuantificación de las diferencias en la morfología de la onda T, se ha desarrollado una metodología robusta que se basa en la re-parametrización en el tiempo.<br /

Multiscale image analysis of calcium dynamics in cardiac myocytes

Cardiac myocytes constitute a unique physiological system. They are the muscle cells that build up heart tissue and provide the force to pump blood by synchronously contracting at every beat. This contraction is regulated by calcium concentration, among other ions, which exhibits a very complex behaviour, rich in dynamical states at the molecular, cellular and tissue levels. Details of such dynamical patterns are closely related to the mechanisms responsible for cardiac function and also cardiac disease, which is the first cause of death in the modern world. The emerging field of translational cardiology focuses on the study of how such mechanisms connect and influence each other across spatial and temporal scales finally yielding to a certain clinical condition. In order to study such patterns, we benefit from the recent and very important advances in the field of experimental cell physiology. In particular, fluorescence microscopy allows us to observe the distribution of calcium in the cell with a spatial resolution below the micron and a frame rate around the millisecond, thus providing a very accurate monitoring of calcium fluxes in the cell. This thesis is the result of over five years' work on biological signal and digital image processing of cardiac cells. During this period of time the aim has been to develop computational techniques for extracting quantitative data of physiological relevance from microscopy images at different scales. The two main subjects covered in the thesis are image segmentation and classification methods applied to fluorescence microscopy imaging of cardiac myocytes. These methods are applied to a variety of problems involving different space and time scales such as the localisation of molecular receptors, the detection and characterisation of spontaneous calcium-release events and the propagation of calcium waves across a culture of cardiac cells. The experimental images and data have been provided by four internationally renowned collaborators in the field. It is thanks to them and their teams that this thesis has been possible. They are Dr. Leif Hove-Madsen from the Institut de Ciències Cardiovasculars de Catalunya in Barcelona, Prof. S. R. Wayne Chen from the Department of Physiology and Pharmacology in the Libin Cardiovascular Institute of Alberta, University of Calgary, Dr. Peter P. Jones from the Department of Physiology in the University of Otago, and Prof. Glen Tibbits from the Department of Biomedical Physiology & Kinesiology at the Simon Fraser University in Vancouver. The work belongs to the biomedical engineering discipline, focusing on the engineering perspective by applying physics and mathematics to solve biomedical problems. Specifically, we frame our contributions in the field of computational translational cardiology, attempting to connect molecular mechanisms in cardiac cells up to cardiac disease by developing signal and image-processing methods and machine-learning methods that are scalable through the different scales. This computational approach allows for a quantitative, robust and reproducible analysis of the experimental data and allows us to obtain results that otherwise would not be possible by means of traditional manual methods. The results of the thesis provide specific insight into different cell mechanisms that have a non-negligible impact at the clinical level. In particular, we gain a deeper knowledge of cell mechanisms related to cardiac arrhythmia, fibrillation phenomena, the emergence of alternans and anomalies in calcium handling due to cell ageing.Els cardiomiòcits constitueixen un sistema fisiològic únic. Són les cèl·lules muscular que formen el cor i proporcionen la força per bombar la sang fent una contracció a cada batec. La regulació d'aquesta contracció es fa mitjançant concentració de calci (entre d'altres ions) i presenta una dinàmica molt complexa tant a l'escala molecular, cel·lular i de teixit. Detalls d'aquesta dinàmica estan fortament relacionats amb la funció cardíaca i per sobre de tot amb patologies cardíaques. La disciplina emergent de la cardiologia translacional es centra en l'estudi de com aquests mecanismes es connecten i s'influencien entre sí a través de diferents escales temporals i espacials finalment donant lloc a condicions clíniques. Per estudiar aquests patrons ens beneficiem dels recents avenços en fisiologia i biologia cel·lular. En particular, la microscòpia de fluorescència ens permet observar la distribució de calci dins una cèl·lula amb una resolució espacial per sota de la micra i temporal per sota del mil·lisegon, permetent un monitoratge acurat dels fluxos de calci en la cèl·lula cardíaca. Aquesta tesi és el resultat de més de cinc anys de feina en processament de senyal i imatge de cardiomiòcits humans. Durant aquest període de temps l'objectiu principal ha estat desenvolupar tècniques computacionals per extraure dades d'imatges de microscòpia amb rellevància fisiològica. Els dos temes principals coberts a la tesi són segmentació d'imatges i classificadors, aplicats a imatges de microscòpia de fluorescència de cardiomiòcits. Els mètodes s'apliquen a diferents problemes involucrant diverses escales espacials i temporals, des de determinar la posició de receptors a l’escala molecular passant detectar i caracteritzar alliberament espontani de calci intracel·lular fins a la propagació d'ones de calci en un cultiu de cèl·lules cardíaques. Les dades experimentals han estat proporcionades per quatre col·laboradors de renom internacional. És gràcies a ells i els seus equips que aquesta tesi ha estat possible. Són el Dr. Leif Hove-Madsen de l'Institut de Ciències Cardiovasculars de Catalunya a Barcelona, el Dr. S.R. Wayne Chen del Department of Physiology and Pharmacology al Libin Cardiovascular Institute of Alberta, University of Calgary, el Dr. Peter P. Jones del Department of Physiology a la University of Otago, i el Dr. Glen Tibbits del Department of Biomedical Physiology & Kinesiology de la Simon Fraser University a Vancouver. El treball pertany a la disciplina de la enginyeria biomèdica, fent èmfasi a la perspectiva de l'enginyeria, aplicant física i matemàtiques per solucionar problemes de la biomedicina. Específicament, s'emmarca en la cardiologia translacional computacional, mirant de connectar mecanismes a l’escala molecular amb patologies cardíaques mitjançant tècniques de processament de dades i aprenentatge automàtic que són escalables a les diferents escales d’aplicació. Aquest enfocament computacional permet una anàlisi quantitatiu, robust i reproduïble de les dades experimentals i ens permet d'obtenir resultats que serien impossibles d'assolir mitjançant els tradicionals mètodes manuals. Els resultats que proporciona la tesi han permès aprofundir en l'enteniment de diferents mecanismes fisiològics amb impacte en l'àmbit clínic. Particularment hem permès d’assolir coneixements relacionats amb l'arítmia cardíaca, la fibril·lació, processos d'alternança i anomalies relacionades amb l’envelliment

Analyse des ondes P et T des signaux ECG à l'aide de méthodes Bayésienne

Cette thèse a pour objet l étude de méthodes Bayésiennes pour l analyse des ondes P et T des signaux ECG. Différents modèles statistiques et des méthodes Bayésiennes associées sont proposés afin de réaliser la détection des ondes P et T et leur caractérisation (détermination du sommet et des limites des ondes ainsi que l estimation des formes d onde). Ces modèles prennent en compte des lois a priori pour les paramètres inconnus (les positions des ondes, les amplitudes et les coefficients de ces formes d'onde) associés aux signaux ECG. Ces lois a priori sont ensuite combinées avec la vraisemblance des données observées pour fournir les lois a posteriori des paramètres inconnus. En raison de la complexité des lois a posteriori obtenues, des méthodes de Monte Carlo par Chaînes de Markov sont proposées pour générer des échantillons distribués asymptotiquement suivant les lois d intérêt. Ces échantillons sont ensuite utilisés pour approcher les estimateurs Bayésiens classiques (MAP ou MMSE). D'autre part, pour profiter de la nature séquentielle du signal ECG, un modèle dynamique est proposé. Une méthode d'inférence Bayésienne similaire à celle développée précédemment et des méthodes de Monte Carlo séquentielles (SMC) sont ensuite étudiées pour ce modèle dynamique. Dans la dernière partie de ce travail, deux modèles Bayésiens introduits dans cette thèse sont adaptés pour répondre à un sujet de recherche clinique spécifique appelé détection de l'alternance des ondes T. Une des approches proposées a servi comme outil d'analyse dans un projet en collaboration avec St. Jude Medical, Inc et l'hôpital de Rangueil à Toulouse, qui vise à évaluer prospectivement la faisabilité de la détection des alternances des ondes T dans les signaux intracardiaques.This thesis studies Bayesian estimation/detection algorithms for P and T wave analysis in ECG signals. In this work, different statistical models and associated Bayesian methods are proposed to solve simultaneously the P and T wave delineation task (determination of the positions of the peaks and boundaries of the individual waves) and the waveform-estimation problem. These models take into account appropriate prior distributions for the unknown parameters (wave locations and amplitudes, and waveform coefficients). These prior distributions are combined with the likelihood of the observed data to provide the posterior distribution of the unknown parameters. Due to the complexity of the resulting posterior distributions, Markov chain Monte Carlo algorithms are proposed for (sample-based) detection/estimation. On the other hand, to take full advantage of the sequential nature of the ECG, a dynamic model is proposed under a similar Bayesian framework. Sequential Monte Carlo methods (SMC) are also considered for delineation and waveform estimation. In the last part of the thesis, two Bayesian models introduced in this thesis are adapted to address a specific clinical research problem referred to as T wave alternans (TWA) detection. One of the proposed approaches has served as an efficient analysis tool in the Endocardial T wave Alternans Study (ETWAS) project in collaboration with St. Jude Medical, Inc and Toulouse Rangueil Hospital. This project was devoted to prospectively assess the feasibility of TWA detection in repolarisation on EGM stored in ICD memories.TOULOUSE-INP (315552154) / SudocSudocFranceF