Catheter ablation in patients with atrial fibrillation : mapping refinements, outcome prediction and effect on quality of life

PhD ThesisChapter 1 presents a literature review, focused primarily on the pathophysiology and management of atrial fibrillation (AF). Chapter 2 examines correlations between the dominant frequency of AF - calculated using principal component analysis from a modified surface 12-lead ECG (which included posterior leads), a standard 12-lead ECG and intracardiac recordings from both atria. The inclusion of posterior leads did not improve correlation with left atrial activity because of the dominance of lead V1 in both ECG configurations. Chapter 3 explores whether acute and 12-month outcome following catheter ablation for AF can be predicted beforehand from clinical and surface AF waveform parameters. Multivariate risk scores combining these parameters can predict arrhythmia outcome following ablation, and could therefore be used to identify those most likely to benefit from this therapy. Chapter 4 examines the effect of catheter ablation on AF symptoms and quality of life (QoL). AF symptom and QoL scores improved significantly in patients who maintained sinus rhythm after ablation but did not change in those with recurrent AF. AF-specific QoL scales are more responsive to change and correlate better with ablation outcome. Chapter 5 examines inter-atrial frequency gradients in patients with persistent AF using multipolar contact mapping. A right-to-left atrial frequency gradient was found in a quarter of the patients studied, implying that their arrhythmia was being maintained by high frequency sources in the right rather than the left atrium. Chapter 6 examines whether targeting high frequency and highly repetitive complex fractionated atrial electrogram sites, identified using multipolar contact mapping during persistent AF, resulted in arrhythmia termination and maintenance of sinus rhythm long-term. The utility of administering flecainide to distinguish critical from bystander AF sites was also investigated. Flecainide did not help refine ablation targets and 12-month outcome after targeting these sites was not superior to other ablation strategies

Pulmonary Vein Activity Organization to Determine Atrial Fibrillation Recurrence: Preliminary Data from a Pilot Study

[EN] Ablation of pulmonary veins has emerged as a key procedure for normal rhythm restoration in atrial fibrillation patients. However, up to half of ablated Atrial fibrillation (AF) patients suffer recurrences during the first year. In this article, simultaneous intra-atrial recordings registered at pulmonary veins previous to the ablation procedure were analyzed. Spatial cross-correlation and transfer entropy were computed in order to estimate spatial organization. Results showed that, in patients with arrhythmia recurrence, pulmonary vein electrical activity was less correlated than in patients that maintained sinus rhythm. Moreover, correlation function between dipoles showed higher delays in patients with AF recurrence. Results with transfer entropy were consistent with spatial cross-correlation measurements. These results show that arrhythmia drivers located at the pulmonary veins are associated with a higher organization of the electrical activations after the ablation of these sites.This research was funded by Spanish Ministry of Research and Innovation : PID2019-109547RB-I00. This research was supported by the PID2019-109547RB-I00 National Research Program RETOS from the Spanish Ministry of Research and Innovation and partialy by GVA (PROMETEO/2018/078) & ISCIII (CB16/11/00486). Thanks to Michael Charles Willoughby for English language and scientific editing services.Cervigón, R.; Moreno, J.; Millet Roig, J.; Pérez-Villacastín, J.; Castells, F. (2020). Pulmonary Vein Activity Organization to Determine Atrial Fibrillation Recurrence: Preliminary Data from a Pilot Study. Mathematics. 8(10):1-13. https://doi.org/10.3390/math8101813S113810Andrade, J., Khairy, P., Dobrev, D., & Nattel, S. (2014). The Clinical Profile and Pathophysiology of Atrial Fibrillation. 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Novel Approaches to ECG-Based Modeling and Characterization of Atrial Fibrillation

This thesis deals with signal processing algorithms for analysis of the electrocardiogram (ECG) during atrial fibrillation (AF). Such analysis can be used for diagnosing patients, and for monitoring and predicting their response to various treatment. The thesis comprises an introduction and five papers describing methods for ECG-based modeling and characterization of AF. Paper I--IV deal with methods for characterization of the atrial activity, whereas Paper V deals with modeling of the ventricular response, both problems with the assumption that AF is present. In Paper I, a number of measures characterizing the atrial activity in the ECG, obtained using time-frequency analysis as well as nonlinear methods, are evaluated for their ability to predict spontaneous termination of AF. The AF frequency, i.e, the repetition rate of the atrial fibrillatory waves of the ECG, proved to be a significant factor for discrimination between terminating and non-terminating AF. Noise is a common problem in ECG signals, particularly in long-term ambulatory recordings. Hence, robust algorithms for analysis and characterization are required. In Paper II, a robust method for tracking the AF frequency in noisy signals is presented. The method is based on a hidden Markov model (HMM), which takes the harmonic pattern of the atrial activity into account. Using the HMM-based method, the average RMS error of the frequency estimates at high noise levels was significantly lower compared to existing methods. In Paper III, the HMM-based method is employed for analysis of 24-h ambulatory ECG signals in order to explore circadian variation in AF frequency. Circadian variations reflect autonomic modulation; attenuation or absence of such variations may help to diagnose patients. Methods based on curve fitting, autocorrelation, and joint variation, respectively, are employed to quantify circadian variations, showing that it is present in most patients with long-standing persistent AF, although the short-term variation is considerable. In Paper IV, 24-h ambulatory ECG recordings with paroxysmal and persistent AF are analyzed using an entropy-based method for characterization of the atrial activity. Short segments are classified based on these measures, showing that it is feasible to distinguish between patient with paroxysmal and persistent AF from 10-s ECGs; the average classification rate was above 95%. The ventricular response during AF is mainly determined by the AV nodal blocking of atrial impulses. In Paper V, a new model-based approach for analysis of the ventricular response during AF is proposed. The model integrates physiological properties of the AV node and the atrial fibrillatory rate; the model parameters can be estimated from ECG signals. Results show that ventricular response is sufficiently represented by the estimated model in a majority of the recordings; in 85.7% of the analyzed 30-min segments the model fit was considered accurate, and that changes of AV nodal properties caused by autonomic modulation could be tracked through the estimated model parameters. In summary, the work within this thesis contributes with new methods for non-invasive analysis of AF, which can be used to tailor and evaluate different strategies for AF treatment

High-Density Mapping Analysis of Electrical Spatiotemporal Behaviour in Atrial Fibrillation

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Sinais e Imagens Médicas), 2022, Universidade de Lisboa, Faculdade de CiênciasDoenças cardiovasculares, tais como arritmias, são a principal causa de morte no mundo, especialmente no Sul e no Este da Ásia, e nos Estados Unidos da América [1]. As arritmas são caracterizadas pela alteração no ritmo sinusal normal do coração. Em particular, a fibrilhação auricular (FA) é a arritmia cardíaca mais comum na prática clínica, contribuindo para mais de 200 mil mortes globalmente em 2017 [2]. Caracteriza-se pela contração rápida e dessincronizada das aurículas, e está associada ao aumento da mortalidade e afecta de forma negativa a qualidade de vida dos pacientes. A FA é geralmente tratada através de medicação, porém quando esta falha, a ablação por cateter é indicada, sendo um tratamento de referência para combater esta patologia. A ablação apresenta uma taxa de sucesso de aproximadamente 50% no primeiro procedimento, sendo necessário efectuar vários procedimentos para aumentar a eficácia do tratamento [3]. A detecção desta patologia envolve, numa primeira fase, a realização de um electrocardiograma (ECG) e, posteriormente um estudo electrofisiológico para saber com precisão onde se localiza e o mecanismo subjacente à mesma. Este último implica o registo da actividade eléctrica através de electrogramas (EGM) locais em diferentes pontos das aurículas e dos ventrículos, com o auxílio de sistemas de mapeamento tridimensionais (3D) electroanatómicos, sendo um procedimento invasivo. Existem diversos métodos lineares e não lineares que permitem a análise dos EGMs nos domínios do tempo, frequência, fase, entre outros, com a finalidade de melhor compreender os mecanismos subjacentes à FA e, consequentemente aumentar a taxa de sucesso do processo de ablação e melhorar a sua eficiência. Esta área de estudo progrediu significativamente, tanto a nível de hardware, como de software. Apesar disso, os métodos desenvolvidos não têm nem acrescentado benefícios adicionais, nem melhorado significativamente a taxa de sucesso do processo de ablação. Existem várias razões para tal, e grande parte deve-se ao facto destes métodos de análise estarem incorporados nos sistemas de mapeamento e o seu software ser exclusivo. Isto leva a que não consigamos perceber como é que os algoritmos funcionam nos diferentes sistemas de mapeamento para comparar as suas diferenças e semelhanças. Devido a estes constrangimentos, os investigadores são compelidos a desenvolver os seus próprios métodos de análise e técnicas de mapeamento, o que leva à existência de uma multitude de métodos e técnicas de mapeamento que parecem ser diferentes entre si, resultando em informação ambígua e conflituosa no que diz respeito aos mecanismos da FA, e a conclusões distintas entre estudos. O sucesso do tratamento poderia aumentar se tivéssemos uma melhor compreensão dos métodos de análise e da sua aplicação no contexto da FA; perceber se os métodos apontam para o mesmo fenómeno de fibrilhação, se existe alguma correlação entre os métodos, e se a informação fornecida pelos mesmos é complementar ou redundante. Assim, o objectivo deste trabalho consistiu em implementar diferentes métodos para analisar os EGMs e a estrutura 3D da aurícula esquerda (AE) de doentes com FA, numa tentativa de responder às questões que motivaram a realização deste projecto. Em última análise, ao observar os mapas 3D da AE tendo uma melhor compreensão dos métodos, poderemos identificar com precisão as regiões na AE responsáveis por iniciar a FA, e ter mais conhecimento sobre os mecanismos responsáveis pela mesma. Desta forma, o processo de ablação poderá alcançar o seu potencial. Para este projecto, foram incluídos os mapas 3D electroanatómicos da AE de dez doentes com FA paroxística ou persistente do hospital de Santa Marta, recolhidos com o sistema de mapeamento CARTO 3. Cada ponto electroanatómico dos mapas inclui as 12 derivações do ECG, e os EGMs unipolares e bipolares registados com o cateter de mapeamento Pentaray de 20 pólos. Porém, apenas os EGMs bipolares foram incluídos na análise. Processaram-se os sinais bipolares e, devido a algumas limitações, foi possível apenas a implementação de dois métodos diferentes para os analisar: um no domínio da frequência – Frequência Dominante (FD) –, e outro no domínio da Teoria da Informação – a entropia de Shannon. De seguida, criaram-se três tipos de mapas 3D electroanatómicos da AE para cada doente: um de voltagem, cuja informação foi adquirida com o sistema de mapeamento, um de FD, e outro de entropia. A informação de cada mapa estava organizada segundo um padrão de cores. Observando os diferentes tipos de mapas da AE paralelamente, foi possível comparar os métodos, e perceber que tipo de informação cada um deles fornecia, numa tentativa de melhor compreender os mecanismos da FA. Foi possível observar em algumas regiões da AE, principalmente nos mapas de voltagem e de FD, a presença de “centros de activação” ou “centros de fibrilhação”, que poderão ser os gatilhos responsáveis por desencadear ou manter o mecanismo de fibrilhação. Para confirmar se de facto aquelas regiões eram os gatilhos de fibrilhação, seria necessário submeter os doentes ao processo de ablação e queimar essas zonas; e posteriormente acompanhar os doentes para observar os efeitos do procedimento e confirmar a hipótese. Contudo, dadas as limitações do trabalho e o facto desta área de investigação ser pouco explorada, é fulcral obter um maior número de estudo comparativos entre mais métodos de diferentes domínios e confirmar se apontam ou não para o mesmo fenómeno de fibrilhação. Apesar de terem sido implementados apenas dois métodos de análise dos EGMs, o projecto permitiu a comparação entre os mesmos, uma área de estudo por onde ainda há muito para investigar. Com mais conhecimento sobre os diferentes métodos, a sua aplicação, inter-relação e adequação no estudo dos mecanismos da FA e das propriedades electrofisiológicas desta patologia, é possível desenvolver procedimentos de ablação mais eficientes e selectivos, de forma a diminuir os riscos e aumentar a taxa de sucesso do tratamento.Atrial fibrillation (AF) is the most frequent cardiac arrhythmia in clinical practice and is described by rapid and irregular contractions of the atria. Despite catheter ablation (CA) being a well-established treatment for AF, it is sub-optimal, with a success rate of approximately 50 % after a single procedure, with some patients requiring multiple procedures to achieve long-term freedom from this pathology. This prompted the proposal and development of various quantitative electrogram (EGM)-based methods along with different mapping systems with their respective mapping techniques, to better understand the mechanisms responsible for initiating and maintaining AF, thus improving ablation outcomes. However, this diversification of methods and tools resulted in disperse and inconsistent data regarding the mechanisms of AF. This work consisted of employing two different methods to analyse the electrograms (EGM): dominant frequency (DF) and Shannon entropy (ShEn). From these EGMs, metrics were then extracted and displayed in colour-coded fashion on a 3D mesh of the left atrium (LA) from patients with paroxysmal or persistent AF. The two methods were compared to understand whether or not these indicated different phenomena/mechanisms, and if these could locate sites suspected of triggering and maintaining AF. The results, while not fully conforming to the literature, allowed the comparison between different EGM analysis methods, a field of study that requires further research. Overall, this project highlighted the limited data available within the topic, hindering our understanding of AF mechanisms and development of more effective and selective ablation procedures to avoid unnecessary complications, and ultimately improve the effects of the treatment's outcomes

Spatial Characterization and Estimation of Intracardiac Propagation Patterns During Atrial Fibrillation

This doctoral thesis is in the field of biomedical signal processing with focus on methods for the analysis of atrial fibrillation (AF). Paper I of the present thesis addresses the challenge of extracting spatial properties of AF from body surface signals. Different parameters are extracted to estimate the preferred direction of atrial activation and the complexity of the atrial activation pattern. In addition, the relation of the spatial properties to AF organization, which is quantified by AF frequency, is evaluated. While no significant correlation between the preferred direction of atrial activation and AF frequency could be observed, the complexity of the atrial activation pattern was found to increase with AF frequency. The remaining three papers deal with the analysis of the propagation of the electrical activity in the atria during AF based on intracardiac signals. In Paper II, a time-domain method to quantify propagation patterns along a linear catheter based on the detected atrial activation times is developed. Taking aspects on intra-atrial signal organization into account, the detected activation times are combined into wavefronts, and parameters related to the consistency of the wavefronts over time and the activation order along the catheter are extracted. Furthermore, the potential relationship of the extracted parameters to established measures from body surface signals is investigated. While the degree of wavefront consistency was not reflected by the applied body surface measures, AF frequency could distinguish between recordings with different degrees of intra-atrial signal organization. This supports the role of AF frequency as an organization measure of AF. In Paper III, a novel method to analyze intracardiac propagation patterns based on causality analysis in the frequency domain is introduced. In particular, the approach is based on the partial directed coherence (PDC), which evaluates directional coupling between multiple signals in the frequency domain. The potential of the method is illustrated with simulation scenarios based on a detailed ionic model of the human atrial cell as well as with real data recordings, selected to present typical propagation mechanisms and recording situations in atrial tachyarrhythmias. For simulated data, the PDC is correctly reflecting the direction of coupling and thus the propagation between all recording sites. For real data, clear propagation patterns are identified which agree with previous clinical observations. Thus, the results illustrate the ability of the novel approach to identify propagation patterns from intracardiac signals during AF which can provide important information about the underlying AF mechanisms, potentially improving the planning and outcome of ablation. However, spurious couplings over long distances can be observed when analyzing real data comprised by a large number of simultaneously recorded signals, which gives room for further improvement of the method. The derivation of the PDC is entirely based on the fit of a multivariate autoregressive (MVAR) model, commonly estimated by the least-squares (LS) method. In Paper IV, the adaptive group least absolute selection and shrinkage operator (LASSO) is introduced in order to avoid overfitting of the MVAR model and to incorporate prior information such as sparsity of the solution. The sparsity can be motivated by the observation that direct couplings over longer distances are likely to be zero during AF; an information which has been further incorporated by proposing distance-adaptive group LASSO. In simulations, adaptive and distance-adaptive group LASSO are found to be superior to LS estimation in terms of both detection and estimation accuracy. In addition, the results of both simulations and real data analysis indicate that further improvements can be achieved when the distance between the recording sites is known or can be estimated. This further promotes the PDC as a method for analysis of AF propagation patterns, which may contribute to a better understanding of AF mechanisms as well as improved AF treatment

Study on the non-linear metrics contribution to estimate atrial fibrillation organization from the surface electrocardiogram

[EN] Atrial fibrillation (AF) is the most frequently diagnosed arrhythmia, characterized by an uncoordinated atrial electrical activation, thus causing the atria to be unable to pump blood effectively. The prevalence of AF is expected to increase significantly in the next decades as the population ages. However, both the knowledge and the treatment of this arrhythmia still have to experiment a significant progress. Previous studies have reported that AF organization, which can be defined as the repetitiveness degree of the atrial activity pattern, correlates with the arrhythmia status as well as with the therapy outcome. Thus, estimating AF organization from surface electrocardiographic (ECG) recordings constitutes a very interesting approach because ECG recordings are easy and cheap to obtain. The objective of this doctoral thesis is to assess the use of a variety of nonlinear indices in the estimation of AF organization from single-lead noninvasive ECG recordings. Apart from the most common noninvasive AF organization estimators, such as Sample Entropy (SampEn) and the dominant atrial frequency (DAF), the following nonlinear indices have been studied: Fuzzy Entropy, Spectral Entropy, Lempel-Ziv Complexity and Hurst Exponents. Moreover, since the presence of noise and ventricular residuals affects the performance of nonlinear methods, the application of a strategy aimed at reducing these nuisances has been evaluated. Therefore, the application of these metrics over the atrial activity fundamental waveform, named the main atrial wave (MAW), has been proposed. In this doctoral thesis, the following scenarios involving AF organization have been considered: the prediction of paroxysmal AF spontaneous termination, the study of the earlier signs anticipating AF termination and the classification between paroxysmal and persistent AF from short ECG recordings. Firstly, the performance of the studied metrics discriminating events related to AF organization was tested making use of a reference database aimed at predicting AF spontaneous termination. In this study, most of the proposed indices provided higher accuracy than traditional AF organization estimators. Accuracy values higher than 90% were obtained with several indices. In particular, the generalized Hurst exponents of order 1 and 2, H(1) and H(2), achieved outstanding results, thus being selected for later studies in this thesis. Furthermore, the computation of H(2) depends on two critical parameters, namely, the analyzed interval length (L) and the maximum search window for self-similarities (tau). Hence, a study with 660 combinations on these two parameters was performed, together with the sampling frequency (fs) of the recording, in order to obtain their optimal combination in computing AF organization. On the other hand, previous works analyzing the spontaneous termination of AF have been only focused on the last 2 minutes preceding the termination. In contrast, a different scenario considering longer recordings to detect the earlier signs anticipating paroxysmal AF termination has been analyzed for the first time in this thesis. H(2) was selected for the study because of its highest accuracy in AF termination prediction. Additionally, the DAF and SampEn were also computed as references. Through this study it has been corroborated that AF organization only varies significantly within the last 3 minutes before spontaneous termination. As a consequence, the early prediction of paroxysmal AF spontaneous termination does not seem feasible through the current signal analysis tools. Finally, H(2) was applied in the classification between paroxysmal and persistent AF from short ECG recordings, achieving a higher diagnostic accuracy than DAF and SampEn. This result suggests that the analysis of ambulatory ECG recordings through H(2) could be a future alternative to the use of Holter ECG recordings in the classification between paroxysmal and persistent AF.[ES] La fibrilación auricular (FA) es la arritmia más frecuente y se caracteriza por una actividad auricular descoordinada, que impide que las aurículas bombeen sangre de manera eficaz. Se espera que la prevalencia de la FA aumente significativamente en las próximas décadas debido al envejecimiento de la población. Sin embargo, tanto el conocimiento relativo a esta arritmia como su tratamiento son todavía mejorables. Estudios previos han relacionado la organización de la FA, que se puede definir como el grado de repetitividad de la actividad auricular, con el estado de la arritmia o su respuesta al tratamiento. Además, la estimación de la organización de la FA a partir de registros electrocardiográficos (ECG) de superficie resulta especialmente interesante porque su obtención es sencilla y barata. El objetivo de esta tesis doctoral es evaluar el uso de distintos índices no lineales para estimar la organización de la FA a partir del ECG. Además de los estimadores no invasivos de organización más comunes, como la entropía muestral (SampEn) y la frecuencia auricular dominante (DAF), se han estudiado los siguientes métodos no lineales: la entropía borrosa, la entropía espectral, la complejidad Lempel-Ziv y los exponentes de Hurst. Además, se ha estudiado el uso de una estrategia destinada a la reducción del ruido y los residuos de actividad ventricular para mejorar el desempeño de métodos no lineales. Así, los índices estudiados también se han aplicado sobre la forma de onda fundamental de la actividad auricular, conocida como la onda auricular principal (MAW). Se han considerado los siguientes escenarios relacionados con la organización de la FA: la predicción de la terminación espontánea de la FA paroxística, el estudio de los primeros indicios de terminación espontánea de la FA y la clasificación entre FA paroxística y FA persistente a partir de registros ECG de corta duración. Primero, se estudió la capacidad de los índices estudiados para distinguir eventos relacionados con la organización de la FA mediante el análisis de una base de datos de referencia para la predicción de su terminación espontánea. La mayoría de los índices propuestos consiguieron una mayor precisión que los estimadores tradicionales de organización. Así, varios de los índices obtuvieron una precisión superior al 90% en la predicción de la terminación espontánea de la FA. En particular, los exponentes de Hurst generalizados de orden 1 y 2, H(1) y H(2), lograron los mejores resultados de clasificación. Puesto que el cálculo de H(2) depende de dos parámetros críticos, la longitud del intervalo analizado (L) y el tamaño máximo de la ventana donde buscar similitudes (tau), se llevó a cabo un estudio con 660 combinaciones de esos dos parámetros junto con la frecuencia de muestreo (fs) del registro para determinar el uso óptimo de este índice. Por otra parte, los trabajos previos que han estudiado la terminación espontánea de la FA se han centrado en los últimos 2 minutos antes de la terminación. Por contra, en esta tesis doctoral se han estudiado por primera vez registros de mayor duración para detectar los primeros indicios de la terminación de la FA. Para ello, se eligió el uso de H(2) por su alta precisión en la predicción de la terminación de la FA. Además, la DAF y SampEn se calcularon como referencias. En este estudio se ha comprobado que la organización de la FA solamente presenta variaciones significativas en los últimos 3 minutos antes de su terminación espontánea. Por ello, la predicción temprana de la terminación no parece posible con los medios actuales de análisis de la señal. Por último, se aplicó H(2) para clasificar entre FA paroxística y FA persistente a partir de ECGs de corta duración, obteniendo una mayor precisión diagnóstica que la DAF y SampEn. Este resultado sugiere que el análisis de ECGs ambulatorios por medio de H(2) puede ser en el futuro una alte[CA] La fibril·lació auricular (FA) és l'arítmia més freqüent i es caracteritza per una activitat auricular descoordinada, que impedix que les aurícules bomben sang de manera eficaç. S'espera que la prevalença de la FA augmente significativament en les pròximes dècades a causa de l'envelliment de la població. No obstant això, tant el coneixement relatiu a esta arítmia com el seu tractament són encara millorables. Estudis previs han relacionat l'organització de la FA, que es pot definir com el grau de repetitivitat de l'activitat auricular, amb l'estat de l'arítmia o la seua resposta al tractament. A més, l'estimació de l'organització de la FA a partir de registres electrocardiogràfics (ECG) de superfície resulta especialment interessant perquè la seua obtenció és senzilla i barata. L'objectiu d'esta tesi doctoral és avaluar l'ús de distints índexs no lineals en l'estimació de l'organització de la FA a partir de l'ECG de superfície. A més dels estimadors no invasius d'organització més comuns, com l'entropia mostral (SampEn) i la freqüència auricular dominant (DAF), s'han estudiat els següents mètodes no lineals: l'entropia borrosa, l'entropia espectral, la complexitat Lempel-Ziv i els exponents de Hurst. A més, s'ha estudiat l'ús d'una estratègia destinada a la reducció del soroll i els residus d'activitat ventricular per a millorar la seua capacitat d'estimar l'organització. Així, doncs, els índexs estudiats també s'han aplicat sobre la forma d'onda fonamental de l'activitat auricular, coneguda com l'onda auricular principal (MAW). S'han considerat els següents escenaris relacionats amb l'organització de la FA: la predicció de la terminació espontània de la FA paroxística, l'estudi dels primers indicis de terminació espontània de la FA i la classificació entre FA paroxística i FA persistent a partir de registres ECG de curta duració. Primer, es va estudiar la capacitat dels índexs estudiats per a distingir esdeveniments relacionats amb l'organització de la FA per mitjà de l'anàlisi d'una base de dades de referència per a la predicció de la seua terminació espontània. La majoria dels índexs proposats van aconseguir una major precisió que els estimadors tradicionals d'organització de la FA. Així, alguns dels índexs van obtindre una precisió superior al 90% en la predicció de la terminació espontània de la FA. En particular, els exponents de Hurst generalitzats d'orde 1 i 2, H(1) i H(2), van aconseguir els millors resultats de classificació. Com el càlcul de H(2) depén de dos paràmetres crítics, la longitud de l'interval analitzat (L) i la grandària màxima de la finestra on buscar similituds (tau), es va dur a terme un estudi amb 660 combinacions d'eixos dos paràmetres junt amb la freqüència de mostratge (fs) del registre per a determinar la combinació òptima de valors per a estimar l'organització de la FA. D'altra banda, els treballs previs que han estudiat la terminació espontània de la FA s'han centrat en els últims 2 minuts abans de la terminació. Per contra, en esta tesi doctoral s'han estudiat per primera vegada registres de major duració amb l'objectiu de detectar els primers indicis de la terminació de la FA. Es va triar l'ús de H(2) per a este estudi per la seua alta precisió en la predicció de la terminació de la FA. A més, la DAF i SampEn es van calcular com a referències. En este estudi s'ha comprovat que l'organització de la FA només presenta variacions significatives en els últims 3 minuts abans de la seua terminació espontània. Per això, la predicció primerenca de la terminació no pareix possible amb els mitjans actuals d'anàlisi del senyal. Finalment, es va aplicar H(2) per a classificar entre FA paroxística i FA persistent a partir d'ECGs de curta duració, obtenint una millor precisió diagnòstica que amb la DAF i SampEn. Este resultat suggerix que l'anàlisi d'ECGs ambulatoris per mitjà de H(2) pot ser en eJulián Seguí, M. (2015). Study on the non-linear metrics contribution to estimate atrial fibrillation organization from the surface electrocardiogram [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/56150TESI

Atrial fibrillation: a study of substrate and triggers

1. Introduction2. History and Overview of Atrial Fibrillation3. A New Fully Implantable Goat Model of Atrial Fibrillation4. The Profibdilatory Action of Verapamil is Not Prevented by Propafenone5. Repetitive Four-Week Periods of Atrial Electrical Remodelling Promote Stability of Atrial Fibrillation -Evidence for a Second Factor Independent of Atrial Refractoriness in the Self-Perpetuation of Atrial Fibrillation6. Atrial Ectopy - The Coupling Interval of Atrial Premature Beats Following DC Cardioversion of Persistent AF Predicts Subsequent Recurrence of AF7. Atrial Ectopy -Evidence for Reversal of Atrial Electrical Remodelling8. Prevalence and Significance of Focal Sources of Atrial Arrhythmia in Patients Undergoing Cardioversion of Persistent Atrial Fibrillation9. Changes in Heart Rate Variability Following Cardioversion of Persistent Atrial Fibrillation in Ma

Relationship between body surface potential maps and atrial electrograms in patients with atrial fibrillation

PhD ThesisAtrial fibrillation (AF) is the most common cardiac arrhythmia. It is distinguished by fibrillating or trembling of the atrial muscle instead of normal contraction. Patients in AF have a much higher risk of stroke. AF is often driven by the left atrium (LA) and the diagnosis of AF is normally made from lead V1 in a 12-lead electrocardiogram (ECG). However, lead V1 is dominated by right atrial activity due to its proximal location to the right atrium (RA). Consequently it is not well understood how electrical activity from the LA contributes to the ECG. Studies of the AF mechanisms from the LA are typically based on invasive recording techniques. From a clinical point of view it is highly desirable to have an alternative, non-invasive characterisation of AF. The aim of this study was to investigate how the LA electrical activity was expressed on the body surface, and if it could be observed preferentially in different sites on the body surface. For this purpose, electrical activity of the heart from 20 patients in AF were recorded simultaneously using 64-lead body surface potential mapping (BSPM) and bipolar 10-electrode catheters located in the LA and coronary sinus (CS). Established AF characteristics such as amplitude, dominant frequency (DF) and spectral concentration (SC) were estimated and analysed. Furthermore, two novel AF characteristics (intracardiac DF power distribution, and body surface spectral peak type) were proposed to investigate the relationship between the BSPM and electrogram (EGM) recordings. The results showed that although in individual patients there were body surface sites that preferentially represented the AF characteristics estimated from the LA, those sites were not consistent across all patients. It was found that the left atrial activity could be detected in all body surface sites such that all sites had a dominant or non-dominant spectral peak corresponding to EGM DF. However, overall the results suggested that body surface site 22 (close to lead V1) was more closely representative of the CS activity, and site 49 (close to the posterior lower central right) was more closely representative of the left atrial activity. There was evidence of more accurate estimation of AF characteristics using additional electrodes to lead V1