Rotor detection in atrial fibrillation

Atrial fibrillation (AF) is one of the most common arrhythmias in the clinical practice. Catheter ablation method was developed more than 20 years ago as an approach to terminate this rhythm disorder. Since its outbreak, this technique obtained international acceptance among the clinicians, and technological advances in this field increased its safety while reducing the procedure duration. However, there is no perfect AF treatment procedure described yet, since the understanding of the driving and sustaining AF mechanisms remains poor, with pulmonary vein isolation being the most common ablation strategy. Several theories try to explain the initiating and maintenance mechanisms of the AF, ranging from multiple wavelets propagating at random in the atria to ectopic focus fired from the pulmonary veins. Alternatively, spatiotemporal stable sources (rotors) have been proposed as the maintenance mechanism of AF. The most representative characteristic of a rotor is the re-entry spiral-like propagation pattern that the electrical wavefront exhibits as it propagates. The assessment of its presence and posterior ablation of the sites where rotors anchor might improve the success of AF ablation. Technical solutions emerged focusing on the rotor assessment problem. They base their methods on the reconstruction of the atrial activity using multi-electrode catheters and phase maps, in which they detect singularity points, the sites where rotors spin. The ablation of these sites showed promising results, but the difficulty to reproduce the results by other authors increased the controversy on this technique. In this Thesis we address the rotor detection problem in the time domain as opposed to current methods based on the phase domain of the signals. We develop a new method to identify local activation times (LATs) in unipolar electrograms (EGMs) recorded with multi-electrode catheters. We propose a new filtering scheme to enhance the activation component of the EGM while considerably reducing the presence of noise in the signal. This signal processing method reects the real activity of the tissue in contact with the electrode. It opposes the Hilbert transform (HT) used to extract the phase component of the signal, that do not correlate well with the temporal activations. With the EGM LATs we perform a spatial interpolation translating the electrode positions of the catheter into a regular 2D grid. This way we generate isochronal maps revealing the electrical wavefronts in the atrium. What is more, this step guarantees compatibility with multi-electrode catheters, not restricting the method to specific models. With the isochronal maps, we develop a new rotor detection algorithm based on the optical flow of the wavefront dynamics, and a rotation pattern match. Additionally, we develop a new method based on Granger's causality to estimate the directionality of the wavefronts, that provides an additional indicator for rotational patterns. We validate the methods using in silico and real AF signals. We implement these methods into a system that can assess the presence of rotational activation sites in the atrium. Our system is able to operate in realtime with multi-electrode catheters of different topologies in contact with the atrial wall. We integrate signal acquisition and processing in our system, allowing direct acquisition of the signals without requiring signal exportation from a recording device, which delays the clinical procedure. We address the computational time handicap by designing parallelizable signal processing steps. We employ multi-core processors and GPU based code to distribute the computations and minimize the processing times, achieving near real-time results. The results presented in this Thesis provide a new technical solution to detect the presence of rotational activity (rotors) in AF patients in real-time. Although the presence of rotational activity is itself controversial, we individually validate each of the steps of the procedure and obtain evidence of the presence of rotational activity in AF patients. The system has been also found useful to characterize the atrial sites where rotational activity was found in terms of spatial and voltage distribution. The results of this Thesis provide a new alternative to existing methods based on phase analysis and open a new research line in the detection of the mechanisms sustaining AF.La fibrilación auricular (FA) es una de las arritmias más comunes en la práctica clínica. Para tratar de terminar esta fibrilación en pacientes se desarrollo el método de ablación con catéter hace ya más de 20 años. Desde su puesta en marchar esta técnica ha ido ganando aceptación internacional por parte de la comunidad médica, y los avances tecnológicos desarrollados en esta línea han aumentado la seguridad y disminuido la duración del procedimiento. Sin embargo todavía no existe un tratamiento perfecto para tratar la FA, debido en parte a que el conocimiento de los mecanismos que inician y sostienen la fibrilación son limitados. Como método de ablación el aislamiento de las venas pulmonares prevalece como el más empleado en la práctica, pero se hace necesario el desarrollo de nuevos métodos para hacer frente al problema de la FA. Distintas teorías tratan de explicar los mecanismos de inicio y mantenimiento de la FA, desde unas basadas en la propagación de múltiples frentes de onda aleatorios en las aurículas, hasta las que basan su hipótesis en focos ectópicos disparados principalmente desde las venas pulmonares, entre otras teorías. Recientemente, una de estas teorías basada en fuentes espacio-temporalmente estables (rotores) se propuso como mecanismo de mantenimiento de la FA. La característica más representativa de un rotor es su patrón de reentrada en forma de espiral que realiza el frente de onda eléctrico en el tejido auricular. La evaluación de la presencia de rotores y la posterior de los sitios en los que se encuentren puede mejorar el éxito de la ablación en pacientes con FA. En vista de esta tendencia por la búsqueda de rotores se desarrollaron soluciones técnicas para la evaluación de zonas que alberguen actividad rotacional. Sus técnicas se basan en la reconstrucción de la actividad auricular empleando catéteres multi-electrodo y detectando puntos de singularidad en mapas de phase, esto es la posición en la aurícula en la que el rotor gira. La ablación de estos puntos mostró resultados prometedores, pero la dificultad por replicar los resultados por parte de otros autores incremento la controversia con respecto a esta técnica. En esta Tesis abordamos el problema de la detección de rotores en el dominio del tiempo, oponiéndonos a las técnicas actuales basadas en el dominio de la fase de las señales. Para ello hemos desarrollado un nuevo para identificar tiempos de activación local en electrogramas unipolares registrados con catéteres multi-electrodo. Para ello proponemos un nuevo método de filtrado para realzar la activación del electrograma reduciendo considerablemente la presencia de ruido en la señal. Con este procesado de la señal extraemos y reflejamos la actividad real del tejido en contacto con el electrodo. Al mismo tiempo nos oponemos a la transformada de Hilbert empleada para calcular la componente de fase de la señal, que es sabido no tiene una buena correlación con las activaciones temporales. Con los electrogramas y los tiempos de activación locales aplicamos una interpolación espacial logrando trasladar la posición de los electrodos en el catéter a una rejilla regular en 2D. Mediante este paso generamos mapas isócronos que reconstruyen los frentes de onda eléctricos que se propagan en la aurícula. Además, la interpolación nos permite garantizar una compatibilidad con otros catéteres multi-electrodos, no restringiendo el uso de nuestro método a modelos específicos. Con los mapas isócronos hemos desarrollado un nuevo algoritmo de detección de rotores basado en el flujo óptico de la dinámica del frente de onda que hacemos coincidir con un patrón de rotación. Adicionalmente hemos desarrollado un nuevo método basad en la causalidad propuesta por Granger para estimar la dirección de los frentes de propagación, que sirve como indicador adicional para encontrar patrones de activación rotacional. Hemos validado todos y cada uno de los métodos empleando señales in silico así como señales reales de pacientes con FA. En la parte de aplicación, hemos implementado los métodos en un sistema que evalúa la presencia de actividad rotacional en la aurícula. Nuestro sistema opera en tiempo real siendo compatible con catéteres multi-electrodo de diferentes topologías asegurando contacto con la pared auricular. Para evitar sobreextender el procedimiento clínico, hemos integrado las partes de adquisición y procesado de señal conjuntamente, lo que nos permite un registro de las señales directo sin viii necesidad de requerir un exportado adicional desde un sistema de registro. Para hacer frente al objetivo de presentar los resultados en tiempo real hemos diseñado todos los pasos de procesado de señal para que sean paralelizables. Para ello empleamos procesadores multinúcleo y código para ejecutar en tarjetas gráficas (GPUs) para distribuir las computaciones y minimizar el tiempo de procesado, logrando resultados en quasi tiempo real. Hemos empleado el sistema de detección de rotores para estudiar la distribución espacial y de voltaje de los sitios que muestran actividad rotacional en la aurícula. Aunque la presencia de actividad rotacional es en sí misma controvertida, hemos validad individualmente todos y cada uno de los pasos descritos obteniendo evidencia de la presencia de actividad rotacional en pacientes con FA.Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: Pablo Laguna Lasaosa.- Secretario: Pablo Martínez Olmos.- Vocal: Batiste Andreu Martínez Climen

Hierarchical algorithms for causality retrieval in atrial fibrillation intracavitary electrograms

Multi-channel intracavitary electrograms (EGMs), are acquired at the electrophysiology laboratory to guide radio frequency catheter ablation of patients suffering from atrial fibrillation (AF). These EGMs are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex fractionated electrograms). In this paper, we introduce two hierarchical algorithms to retrieve the causal interactions among these multiple EGMs. Both algorithms are based on Granger causality, but other causality measures can be easily incorporated. In both cases, they start by selecting a root node, but they differ on the way in which they explore the set of signals to determine their cause-effect relationships: either testing the full set of unexplored signals (GS-CaRe) or performing a local search only among the set of neighbor EGMs (LS-CaRe). The ensuing causal model provides important information about the propagation of the electrical signals inside the atria, uncovering wavefronts and activation patterns that can guide cardiologists towards candidate areas for catheter ablation. Numerical experiments, on both synthetic signals and annotated real-world signals, show the good performance of the two proposed approaches

Statistical and Graph-Based Signal Processing: Fundamental Results and Application to Cardiac Electrophysiology

The goal of cardiac electrophysiology is to obtain information about the mechanism, function, and performance of the electrical activities of the heart, the identification of deviation from normal pattern and the design of treatments. Offering a better insight into cardiac arrhythmias comprehension and management, signal processing can help the physician to enhance the treatment strategies, in particular in case of atrial fibrillation (AF), a very common atrial arrhythmia which is associated to significant morbidities, such as increased risk of mortality, heart failure, and thromboembolic events. Catheter ablation of AF is a therapeutic technique which uses radiofrequency energy to destroy atrial tissue involved in the arrhythmia sustenance, typically aiming at the electrical disconnection of the of the pulmonary veins triggers. However, recurrence rate is still very high, showing that the very complex and heterogeneous nature of AF still represents a challenging problem. Leveraging the tools of non-stationary and statistical signal processing, the first part of our work has a twofold focus: firstly, we compare the performance of two different ablation technologies, based on contact force sensing or remote magnetic controlled, using signal-based criteria as surrogates for lesion assessment. Furthermore, we investigate the role of ablation parameters in lesion formation using the late-gadolinium enhanced magnetic resonance imaging. Secondly, we hypothesized that in human atria the frequency content of the bipolar signal is directly related to the local conduction velocity (CV), a key parameter characterizing the substrate abnormality and influencing atrial arrhythmias. Comparing the degree of spectral compression among signals recorded at different points of the endocardial surface in response to decreasing pacing rate, our experimental data demonstrate a significant correlation between CV and the corresponding spectral centroids. However, complex spatio-temporal propagation pattern characterizing AF spurred the need for new signals acquisition and processing methods. Multi-electrode catheters allow whole-chamber panoramic mapping of electrical activity but produce an amount of data which need to be preprocessed and analyzed to provide clinically relevant support to the physician. Graph signal processing has shown its potential on a variety of applications involving high-dimensional data on irregular domains and complex network. Nevertheless, though state-of-the-art graph-based methods have been successful for many tasks, so far they predominantly ignore the time-dimension of data. To address this shortcoming, in the second part of this dissertation, we put forth a Time-Vertex Signal Processing Framework, as a particular case of the multi-dimensional graph signal processing. Linking together the time-domain signal processing techniques with the tools of GSP, the Time-Vertex Signal Processing facilitates the analysis of graph structured data which also evolve in time. We motivate our framework leveraging the notion of partial differential equations on graphs. We introduce joint operators, such as time-vertex localization and we present a novel approach to significantly improve the accuracy of fast joint filtering. We also illustrate how to build time-vertex dictionaries, providing conditions for efficient invertibility and examples of constructions. The experimental results on a variety of datasets suggest that the proposed tools can bring significant benefits in various signal processing and learning tasks involving time-series on graphs. We close the gap between the two parts illustrating the application of graph and time-vertex signal processing to the challenging case of multi-channels intracardiac signals

Non-invasive identification of atrial fibrillation drivers

Atrial fibrillation (AF) is one of the most common cardiac arrhythmias. Nowadays the fibrillatory process is known to be provoked by the high-frequency reentrant activity of certain atrial regions that propagates the fibrillatory activity to the rest of the atrial tissue, and the electrical isolation of these key regions has demonstrated its effectiveness in terminating the fibrillatory process. The location of the dominant regions represents a major challenge in the diagnosis and treatment of this arrhythmia. With the aim to detect and locate the fibrillatory sources prior to surgical procedure, non-invasive methods have been developed such as body surface electrical mapping (BSPM) which allows to record with high spatial resolution the electrical activity on the torso surface or the electrocardiographic imaging (ECGI) which allows to non-invasively reconstruct the electrical activity in the atrial surface. Given the novelty of these systems, both technologies suffer from a lack of scientific knowledge about the physical and technical mechanisms that support their operation. Therefore, the aim of this thesis is to increase that knowledge, as well as studying the effectiveness of these technologies for the localization of dominant regions in patients with AF. First, it has been shown that BSPM systems are able to noninvasively identify atrial rotors by recognizing surface rotors after band-pass filtering. Furthermore, the position of such surface rotors is related to the atrial rotor location, allowing the distinction between left or right atrial rotors. Moreover, it has been found that the surface electrical maps in AF suffer a spatial smoothing effect by the torso conductor volume, so the surface electrical activity can be studied with a relatively small number of electrodes. Specifically, it has been seen that 12 uniformly distributed electrodes are sufficient for the correct identification of atrial dominant frequencies, while at least 32 leads are needed for non-invasive identification of atrial rotors. Secondly, the effect of narrowband filtering on the effectiveness of the location of reentrant patterns was studied. It has been found that this procedure allows isolating the reentrant electrical activity caused by the rotor, increasing the detection rate for both invasive and surface maps. However, the spatial smoothing caused by the regularization of the ECGI added to the temporal filtering causes a large increase in the spurious reentrant activity, making it difficult to detect real reentrant patterns. However, it has been found that maps provided by the ECGI without temporal filtering allow the correct detection of reentrant activity, so narrowband filtering should be applied for intracavitary or surface signal only. Finally, we studied the stability of the markers used to detect dominant regions in ECGI, such as frequency maps or the rotor presence. It has been found that in the presence of alterations in the conditions of the inverse problem, such as electrical or geometrical noise, these markers are significantly more stable than the ECGI signal morphology from which they are extracted. In addition, a new methodology for error reduction in the atrial spatial location based on the curvature of the curve L has been proposed. The results presented in this thesis showed that BSPM and ECGI systems allows to non-invasively locate the presence of high-frequency rotors, responsible for the maintenance of AF. This detection has been proven to be unambiguous and robust, and the physical and technical mechanisms that support this behavior have been studied. These results indicate that both non-invasive systems provide information of great clinical value in the treatment of AF, so their use can be helpful for selecting and planning atrial ablation procedures.La fibrilación auricular (FA) es una de las arritmias cardiacas más frecuentes. Hoy en día se sabe que el proceso fibrilatorio está provocado por la actividad reentrante a alta frecuencia de ciertas regiones auriculares que propagan la actividad fibrilatoria en el resto del tejido auricular, y se ha demostrado que el aislamiento eléctrico de estas regiones dominantes permite detener el proceso fibrilatorio. La localización de las regiones dominantes supone un gran reto en el diagnóstico y tratamiento de la FA. Con el objetivo de poder localizar las fuentes fibrilatorias con anterioridad al procedimiento quirúrgico, se han desarrollado métodos no invasivos como la cartografía eléctrica de superficie (CES) que registra con gran resolución espacial la actividad eléctrica en la superficie del torso o la electrocardiografía por imagen (ECGI) que permite reconstruir la actividad eléctrica en la superficie auricular. Dada la novedad de estos sistemas, existe una falta de conocimiento científico sobre los mecanismos físicos y técnicos que sustentan su funcionamiento. Por lo tanto, el objetivo de esta tesis es aumentar dicho conocimiento, así como estudiar la eficacia de ambas tecnologías para la localización de regiones dominantes en pacientes con FA. En primer lugar, ha visto que los sistemas CES permiten identificar rotores auriculares mediante el reconocimiento de rotores superficiales tras el filtrado en banda estrecha. Además, la posición de los rotores superficiales está relacionada con la localización de dichos rotores, permitiendo la distinción entre rotores de aurícula derecha o izquierda. Por otra parte, se ha visto que los mapas eléctricos superficiales durante FA sufren una gran suavizado espacial por el efecto del volumen conductor del torso, lo que permite que la actividad eléctrica superficial pueda ser estudiada con un número relativamente reducido de electrodos. Concretamente, se ha visto que 12 electrodos uniformemente distribuidos son suficientes para una correcta identificación de frecuencias dominantes, mientras que son necesarios al menos 32 para una correcta identificación de rotores auriculares. Por otra parte, también se ha estudiado el efecto del filtrado en banda estrecha sobre la eficacia de la localización de patrones reentrantes. Así, se ha visto que este procedimiento permite aislar la actividad eléctrica reentrante provocada por el rotor, aumentando la tasa de detección tanto para señal obtenida de manera invasiva como para los mapas superficiales. No obstante, este filtrado temporal sobre la señal de ECGI provoca un gran aumento de la actividad reentrante espúrea que dificulta la detección de patrones reentrantes reales. Sin embargo, los mapas ECGI sin filtrado temporal permiten la detección correcta de la actividad reentrante, por lo el filtrado debería ser aplicado únicamente para señal intracavitaria o superficial. Por último, se ha estudiado la estabilidad de los marcadores utilizados en ECGI para detectar regiones dominantes, como son los mapas de frecuencia o la presencia de rotores. Se ha visto que en presencia de alteraciones en las condiciones del problema inverso, como ruido eléctrico o geométrico, estos marcadores son significativamente más estables que la morfología de la propia señal ECGI. Además, se ha propuesto una nueva metodología para la reducción del error en la localización espacial de la aurícula basado en la curvatura de la curva L. Los resultados presentados en esta tesis revelan que los sistemas de CES y ECGI permiten localizar de manera no invasiva la presencia de rotores de alta frecuencia. Esta detección es univoca y robusta, y se han estudiado los mecanismos físicos y técnicos que sustentan dicho comportamiento. Estos resultados indican que ambos sistemas no invasivos proporcionan información de gran valor clínico en el tratamiento de la FA, por lo que su uso puede ser de gran ayuda para la selección y planificaciLa fibril·lació auricular (FA) és una de les arítmies cardíaques més freqüents. Hui en dia es sabut que el procés fibrilatori està provocat per l'activitat reentrant de certes regions auriculars que propaguen l'activitat fibril·latoria a la resta del teixit auricular, i s'ha demostrat que l'aïllament elèctric d'aquestes regions dominants permet aturar el procés fibrilatori. La localització de les regions dominants suposa un gran repte en el diagnòstic i tractament d'aquesta arítmia. Amb l'objectiu de poder localitzar fonts fibril·latories amb anterioritat al procediment quirúrgic s'han desenvolupat mètodes no invasius com la cartografia elèctrica de superfície (CES) que registra amb gran resolució espacial l'activitat elèctrica en la superfície del tors o l'electrocardiografia per imatge (ECGI) que permet obtenir de manera no invasiva l'activitat elèctrica en la superfície auricular. Donada la relativa novetat d'aquests sistemes, existeix una manca de coneixement científic sobre els mecanismes físics i tècnics que sustenten el seu funcionament. Per tant, l'objectiu d'aquesta tesi és augmentar aquest coneixement, així com estudiar l'eficàcia d'aquestes tecnologies per a la localització de regions dominants en pacients amb FA. En primer lloc, s'ha vist que els sistemes CES permeten identificar rotors auriculars mitjançant el reconeixement de rotors superficials després del filtrat en banda estreta. A més, la posició dels rotors superficials està relacionada amb la localització d'aquests rotors, permetent la distinció entre rotors de aurícula dreta o esquerra. També s'ha vist que els mapes elèctrics superficials durant FA pateixen un gran suavitzat espacial per l'efecte del volum conductor del tors, el que permet que l'activitat elèctrica superficial pugui ser estudiada amb un nombre relativament reduït d'elèctrodes. Concretament, s'ha vist que 12 elèctrodes uniformement distribuïts són suficients per a una correcta identificació de freqüències dominants auriculars, mentre que són necessaris almenys 32 per a una correcta identificació de rotors auriculars. D'altra banda, també s'ha estudiat l'efecte del filtrat en banda estreta sobre l'eficàcia de la localització de patrons reentrants. Així, s'ha vist que aquest procediment permet aïllar l'activitat elèctrica reentrant provocada pel rotor, augmentant la taxa de detecció tant pel senyal obtingut de manera invasiva com per als mapes superficials. No obstant això, aquest filtrat temporal sobre el senyal de ECGI provoca un gran augment de l'activitat reentrant espúria que dificulta la detecció de patrons reentrants reals. A més, els mapes proporcionats per la ECGI sense filtrat temporal permeten la detecció correcta de l'activitat reentrant, per la qual cosa el filtrat hauria de ser aplicat únicament per a senyal intracavitària o superficial. Per últim, s'ha estudiat l'estabilitat dels marcadors utilitzats en ECGI per a detectar regions auriculars dominants, com són els mapes de freqüència o la presència de rotors. S'ha vist que en presència d'alteracions en les condicions del problema invers, com soroll elèctric o geomètric, aquests marcadors són significativament més estables que la morfologia del mateix senyal ECGI. A més, s'ha proposat una nova metodologia per a la reducció de l'error en la localització espacial de l'aurícula basat en la curvatura de la corba L. Els resultats presentats en aquesta tesi revelen que els sistemes de CES i ECGI permeten localitzar de manera no invasiva la presència de rotors d'alta freqüència. Aquesta detecció és unívoca i robusta, i s'han estudiat els mecanismes físics i tècnics que sustenten aquest comportament. Aquests resultats indiquen que els dos sistemes no invasius proporcionen informació de gran valor clínic en el tractament de la FA, pel que el seu ús pot ser de gran ajuda per a la selecció i planificació de procediments d'ablació auricular.Rodrigo Bort, M. (2016). Non-invasive identification of atrial fibrillation drivers [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/75346TESISPremios Extraordinarios de tesis doctorale

Multichannel Analysis of Intracardiac Electrograms - Supporting Diagnosis and Treatment of Cardiac Arrhythmias

Cardiologists diagnose and treat atrial tachycardias using electroanatomical mapping systems. These can be combined with multipolar catheters to record intracardiac electrograms. Within this thesis, various signal processing techniques were implemented and benchmarked to analyze electrograms. They support the physician in diagnosis and treatment of atrial flutter and atrial fibrillation. The developed methods were assessed using simulated data and demonstrated on clinical cases

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

Analysis of Atrial Electrograms

This work provides methods to measure and analyze features of atrial electrograms - especially complex fractionated atrial electrograms (CFAEs) - mathematically. Automated classification of CFAEs into clinical meaningful classes is applied and the newly gained electrogram information is visualized on patient specific 3D models of the atria. Clinical applications of the presented methods showed that quantitative measures of CFAEs reveal beneficial information about the underlying arrhythmia

An investigation into therapies for atrial arrythmias using a biophysical model of the human atria

The most common type of sustained arrhythmia is atrial fibrillation (AF), affecting about 2% of the general population and 8% to 11% of the elderly, more than 65 years of age. The treatment of atrial arrythmia is still based on empirical considerations and is usually evaluated in clinical studies or in animal experiments. The main drawbacks of animal experiments lie in the difficulty of technically accessing the whole atria and in the differences between animal and human anatomy. In the last years, ever-increasing computer power has permitted the development of biophysical models of the human atria. It has become possible to simulate cellular electrical propagation in the whole human heart. Compared to clinical and animal studies, an in silico approach has the advantages of repeatability and reproducibility under controlled conditions. In this thesis, a biophysical model of the human atria has been used to investigate therapies of atrial arrhythmias: surgical ablation and therapeutic pacing. First, a brief review of the concepts of biophysical modeling of human atria developed until now is presented, as well as a brief description of several types of arrhythmia that can be simulated with the biophysical model. Second, measures of organization are considered to quantify and classify the different types of AF. With these measures, AF organization is evaluated at the electrogram signals level as well as at the cellular level. Four types of atrial arrhythmia are differentiated with the use of the biophysical model: atrial flutter, chronic AF, meandering AF and cholinergic AF. Finally, simulations of atrial therapies are investigated. The biophysical model has been used to test the efficacy of ablation lines. The surgical Maze-III procedure has proven to be highly effective in treating chronic AF. However, due to the technical difficulty and the risk of the procedure, less invasive ablation techniques have been investigated. The results confirm the superiority of aggressive surgical procedures in the termination of AF, as described in the clinical studies. Furthermore, an ideal ablation pattern has been proposed using the biophysical model. The ideal pattern should be able to prevent AF with a limited number of ablation lines of minimal length, while allowing for the maintenance or recovery of mechanical activity of both atria during sinus rhythm. The second therapeutic approach investigated is that of pacing. An algorithm of pacing and different pacing sites are investigated during this research. Antitachycardia pacing on different types of AF are carried out. The simulations showed that more organized arrhythmia such as atrial flutter can be pace-terminated. On the other hand, only local capture is possible on more complex AF. The results obtained with the biophysical model are in agreement with the clinical studies. The results of the present research prove that atrial therapies can be approached by means of a biophysical model of the human atria. This tool can be used to investigate further therapeutic techniques and thus, improve the quality of life of patients

The Application of Computer Techniques to ECG Interpretation

This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field