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

A simple scheme for the parallelization of particle filters and its application to the tracking of complex stochastic systems

Documento depositado en el repositorio arXiv.org. Versión: arXiv:1407.8071v2 [stat.CO]We investigate the use of possibly the simplest scheme for the parallelisation of the standard particle filter, that consists in splitting the computational budget into M fully independent particle filters with N particles each, and then obtaining the desired estimators by averaging over the M independent outcomes of the filters. This approach minimises the parallelisation overhead yet displays highly desirable theoretical properties. Under very mild assumptions, we analyse the mean square error (MSE) of the estimators of 1-dimensional statistics of the optimal filtering distribution and show explicitly the effect of parallelisation scheme on the convergence rate. Specifically, we study the decomposition of the MSE into variance and bias components, to show that the former decays as 1/MN, i.e., linearly with the total number of particles, while the latter converges towards 0 as 1/N². Parallelisation, therefore, has the obvious advantage of dividing the running times while preserving the (asymptotic) performance of the particle filter. Following this lead, we propose a time-error index to compare schemes with different degrees of parallelisation. Finally, we provide two numerical examples. The first one deals with the tracking of a Lorenz 63 chaotic system with dynamical noise and partial (noisy) observations, while the second example involves a dynamical network of modified FitzHugh-Nagumo (FH-N) stochastic nodes. The latter is a large dimensional system (≈3,000 state variables in our computer experiments) designed to numerically reproduce typical electrical phenomena observed in the atria of the human heart. In both examples, we show how the proposed parallelisation scheme attains the same approximation accuracy as a centralised particle filter with only a small fraction of the running time, using a standard multicore computer.The work of J. M. and G. R. was partially supported by Ministerio de Economía y Competitividad of Spain (project TEC2012-38883-C02-01 COMPREHENSION) and the Office of Naval Research Global (award no. N62909- 15-1-2011. D. C. and J. M. would also like to acknowledge the support of the Isaac Newton Institute through the program “Monte Carlo Inference for High-Dimensional Statistical Models”

Particle Filter Tracking of Complex Stochastic Systems Applied to In Silico Wavefront Propagation

Proceeding of 2018 Computing in Cardiology Conference (CinC), September 23-26, 2018, Maastricht, The NetherlandsA high dimensional tracking system based on the FithzHugh-Nagumo (FH-N) equations emulating the biological excitation and propagation dynamics of the action potential across cardiac cells is proposed. The modified FH-N model tracks the electric cardiac wavefronts on a tissue, emulating an approximated atrial fibrillation scenario. Bayesian tracking is achieved with two particle filter (PF) schemes: a sequential Auxiliary PF (APF) and a parallelized method, Independent APF (IAPF). The numerical results of the two examples, involving both estimation errors and running times, provide numerical evidence that support the theoretical findings.This work has been partly supported by MINECO/FEDER (ADVENTURE, id. TEC2015-69868-C2-1-R), and Comunidad de Madrid (project CASI-CAM-CM, id. S2013/ICE-2845).Publicad

Causality analysis of atrial fibrillation electrograms

Proceeding of 2015 Computing in Cardiology Conference (CinC 2015), September 6-9, 2015, Nice, FranceMulti-channel intracardiac electrocardiograms (electrograms) are sequentially acquired during heart surgery performed on patients with sustained atrial fibrillation (AF) to guide radio frequency catheter ablation. These electrograms are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex electrograms). In this paper, we introduce a novel hierarchical causality analysis method for the multi-output sequentially acquired electrograms. The causal model obtained provides important information regarding delays among signals as well as the direction and strength of their causal connections. The tool developed may ultimately serve to guide cardiologists towards candidate areas for catheter ablation. Preliminary results on synthetic signals are used to validate the proposed approach.This work has been supported by the Spanish government’s projects ALCIT (TEC2012-38800-C03-01), AGES (S2010/BMD-2422), and OTOSiS (TEC2013-41718-R), and COMPREHENSION (TEC2012-38883-C02-01). D. Luengo has also been funded by the BBVA Foundation’s “I Convocatoria de Ayudas Fundación BBVA a Investigadores, Innovadores y Creadores Culturales”.Publicad

Real-time ventricular cancellation in unipolar atrial fibrillation electrograms

Unipolar atrial fibrillation (AF) electrograms (EGMs) require far-field ventricle cancellation to recover hidden atrial activations. Current methods cannot achieve real-time cancellation because of the temporal delay they introduce. We propose a new real-time ventricular cancellation (RVC) method based on causal implementation optimized for real-time functioning. The method is similar to the classical average beat subtraction (ABS) method but it computes the ventricular contribution before the ventricular activation finishes. We compare the proposed method to the ABS on synthetic and real EGM databases for the time and frequency domains. All parameters and their optimal values are analyzed and validated. The RVC method provides a good reconstruction of the unipolar EGMs and a better local activation time detection than the classical approach with average F1scores 0.7307 and 0.7125, respectively. The spectral analysis shows that the average power after ventricular cancellation is reduced for frequency bands between 3 and 5.5 Hz, demonstrating that the proposed method removes the ventricular component present in the unipolar EGM signals compared to the ABS method. The phase mapping analysis on the RVC method presented lower error when comparing the annotated EGM cycles with the phase inversion intervals. In terms of performance ABS and RVC behave similarly, but the real-time capability of the latter justifies its preference over the offline implementations. In the clinical environment other online investigations, e.g., rotational activity assessment, dominant frequency or local activation time mapping, might benefit from the real-time potential of the proposed cancellation method.This study was supported by grants PI18/01895 from the Instituto de Salud Carlos III, and RD16/0011/0029 Red de Terapia Celular from the Instituto de Salud Carlos III, projects RTI2018-099655-B-I00; TEC2017-92552-EXP from Ministerio de Ciencia, Innovación y Universidades, Y2018/TCS-4705, PRACTICO-CM Comunidad de Madrid, and the support of NVIDIA Corporation with the donation of the Titan V GPU used during this research

Convolutional Neural Networks for Mechanistic Driver Detection in Atrial Fibrillation

The maintaining and initiating mechanisms of atrial fibrillation (AF) remain controversial. Deep learning is emerging as a powerful tool to better understand AF and improve its treatment, which remains suboptimal. This paper aims to provide a solution to automatically identify rotational activity drivers in endocardial electrograms (EGMs) with convolutional recurrent neural networks (CRNNs). The CRNN model was compared with two other state-of-the-art methods (SimpleCNN and attention-based time-incremental convolutional neural network (ATI-CNN)) for different input signals (unipolar EGMs, bipolar EGMs, and unipolar local activation times), sampling frequencies, and signal lengths. The proposed CRNN obtained a detection score based on the Matthews correlation coefficient of 0.680, an ATI-CNN score of 0.401, and a SimpleCNN score of 0.118, with bipolar EGMs as input signals exhibiting better overall performance. In terms of signal length and sampling frequency, no significant differences were found. The proposed architecture opens the way for new ablation strategies and driver detection methods to better understand the AF problem and its treatment

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

Patient-Tailored In Silico 3D Simulations and Models From Electroanatomical Maps of the Left Atrium

Proceeding of 2018 Computing in Cardiology Conference (CinC), September 23-26, 2018, Maastricht, The NetherlandsThe mechanisms underlying atrial fibrillation (AF) are still under debate, making treatments for this arrhythmia remain suboptimal, with most treatments applied in a standard fashion with no patient personalization. Recent technological advances in electroanatomical mapping (EAM) using multi-electrode catheter allow the physicians to better characterize the substrate, thanks to a better spatial resolution and higher density of acquisition points. Taking advantage of this technology, we describe a workflow to build personalized electrophysiological atrial models for AF patients. We seek to better predict the outcome of a treatment and study the AF problem in a more specific scenario. We generated physiological 3D models from the EAM data using hexahedral meshing of element size 300μm, and added fiber orientation based on a generic model. We used the local activation time (LAT) maps performed in sinus rhythm (SR) to estimate the conduction velocity (CV) of the regions in the atrium with a new method that combines the LATs of neighboring tissue as the average CV of triplets of points. We also characterized the cellular model by Maleckar et al. in terms of longitudinal conductivity and CV to personalize the atrial models. We were able to simulate SR and AF scenarios on the personalized models, and we generated a database of atrial models for future analysis.This work has been partly supported by MINECO/FEDER (ADVENTURE, id. TEC2015-69868-C2-1-R), Co munidad de Madrid (CASI-CAM-CM, id. S2013/ICE-2845), Centro de Investigación Biomédica en Red (CIBER), proyecto DPI2016-75458, and the Programa Prometeo, Generalitat Valenciana, Award Number: 2016/088.Publicad

Hidden Markov Models for Activity Detection in Atrial Fibrillation Electrograms

Proceeding of 2020 Computing in Cardiology (CinC 2020), 13-16 September 2020, Rimini, ItalyActivity detection in atrial fibrillation (AF) electrograms (EGMs) is a key concept to understand the mechanisms of this frequent arrhythmia and design new strategies for its treatment. We present a new method that employs Hidden Markov Models (HMMs) to identify activity presence in bipolar EGMs. The method is fully unsupervised and hence it does not require labeled training data. The HMM activity detection method was validated and compared to the non-linear energy operator (NLEO) method for a set of manually annotated EGMs. The HMM performed better than the NLEO and exhibited more robustness in the presence of low voltage fragmented EGMs.This study was supported by grants PI18/01895 from the Instituto de Salud Carlos III, and RD16/0011/0029 Red de Terapia Celular from the Instituto de Salud Carlos III, the projects RTI2018-099655-B-I00; TEC2017-92552-EXP; PID2019-108539RB-C22, Y2018/TCS-4705, and the support of NVIDIA Corporation with the donation of the Titan V GPU used during this research.Publicad

Structural remodeling and rotational activity in persistent/long-lasting atrial fibrillation: gender-effect differences and impact on post-ablation outcome

Background: Structural and post-ablation gender differences are reported in atrial fibrillation (AF). We analyzed the gender differences in structural remodeling and AF mechanisms in patients with persistent/long-lasting AF who underwent wide area circumferential pulmonary vein isolation (WACPVI). Materials and Methods: Ultra-high-density mapping was used to study atrial remodeling and AF drivers in 85 consecutive patients. Focal and rotational activity (RAc) were identified with the CartoFinder system and activation sequence analysis. The impact of RAc location on post-ablation outcomes was analyzed. Results: This study included 64 men and 21 women. RAc was detected in 73.4% of men and 38.1% of women (p = 0.003). RAc patients had higher left atrium (LA) voltage (0.64 ± 0.3 vs. 0.50 ± 0.2 mV; p = 0.01), RAc sites had higher voltage than non-RAc sites 0.77 ± 0.46 vs. 0.53 ± 0.37 mV (p < 0.001). Women had lower LA voltage than men (0.42 vs. 0.64 mV; p < 0.001), including pulmonary vein (PV) antra (0.16 vs. 0.30 mV; p < 0.001) and posterior wall (0.34 vs. 0.51 mV; p < 0.001). RAc in the posterior atrium was recorded in few women (23.8 vs. 54.7% in men; p = 0.014). AF recurrence rate was higher in patients with RAc outside WACPVI than those with all RAc inside WACPVI or no RAc (63.4 vs. 11.1 and 31.0%; p = 0.008 and p = 0.01). Comparison of selected patients using propensity score matching confirmed lower atrial voltage (0.4 ± 0.2 vs. 0.7 ± 0.3 mV; p = 0.007) and less RAc (38 vs. 75%; p = 0.02) in women. Conclusion: Women have shown more advanced structural remodeling at ablation, which is associated with a lower incidence of RAc (usually located outside the WACPVI). These findings could explain post-ablation gender differences.This study was supported by the Instituto de Salud Carlos III, Madrid, Spain (PI18/01895 and DTS21/00064), Red de Terapia Celular from the Instituto de Salud Carlos III, Madrid, Spain (RD16/0011/0029), Ricors "Red de Investigación Cooperativa Orientada a Resultados en Salud" RICORS TERAV (RD21/0017/0002), and the Sección del Ritmo de la Sociedad Española de Cardiología (Grant: Beca de la Asociacion del Ritmo para formación en investigacion post-residencia en centros españoles de la Sección del Ritmo de la Sociedad Española de Cardiología), Madrid, Spain