Estimation of Atrial Electrical Complexity during Atrial Fibrillation by Solving the Inverse Problem of Electrocardiography

Tesis por compendio[ES] La fibrilación auricular (FA) es la arritmia más prevalente en el mundo y está asociada con una elevada morbilidad, mortalidad y costes sanitarios. A pesar de los avances en opciones de tratamiento farmacológico y terapia de ablación, el manejo de la FA todavía tiene margen de mejora. La imagen electrocardiográfica (ECGI) se ha destacado como un prometedor método no invasivo para evaluar la electrofisiología cardíaca y guiar las decisiones terapéuticas en casos de fibrilación auricular. No obstante, el ECGI se enfrenta a desafíos como la necesidad de resolver de manera precisa el denominado problema inverso de la electrocardiografía y de optimizar la calidad de las reconstrucciones de ECGI. Además, la integración del ECGI en los procesos clínicos rutinarios sigue siendo un reto, en gran medida debido a los costos que supone la necesidad de imágenes cardíacas. Por ello, los objetivos principales de esta tesis doctoral son impulsar la tecnología ECGI mediante la determinación de sus requisitos técnicos mínimos y la mejora de las metodologías existentes para obtener señales de ECGI precisas. Asimismo, buscamos evaluar la capacidad de ECGI para cuantificar de forma no invasiva la complejidad de la FA. Para lograr estos objetivos, se han llevado a cabo diversos estudios a lo largo de la tesis, desde el perfeccionamiento del ECGI hasta la evaluación de la FA utilizando esta tecnología. En primer lugar, se han estudiado los requisitos geométricos y de señal del problema inverso mediante el estudio de los efectos de la densidad de la malla del torso y la distribución de electrodos en la precisión del ECGI, lo que ha conducido a la identificación del número mínimo de nodos y su distribución en la malla del torso. Además, hemos identificado que para obtener señales de ECGI de alta calidad, es crucial la correcta disposición de los electrodos en la malla del torso reconstruido. Asimismo, se ha definido y evaluado una nueva metodología de ECGI sin necesidad de usar técnicas de imagen cardiaca. Para ello, hemos comparado métricas derivadas del ECGI calculadas con la geometría original del corazón de los pacientes con las métricas medidas en diferentes geometrías cardíacas. Nuestros resultados han mostrado que el ECGI sin necesidad de imágenes cardíacas es efectivo para la correcta cuantificación y localización de los patrones y zonas que mantienen la FA. En paralelo, hemos optimizado la regularización de Tikhonov de orden cero actual y la optimización de la curva L para el cálculo de las señales ECGI, investigando cómo el ruido eléctrico y las incertidumbres geométricas influyen en la regularización. A partir de ello, propusimos un nuevo criterio que realza la precisión de las soluciones de ECGI en escenarios con incertidumbre debido a condiciones de señal no ideales. En segundo lugar, en esta tesis doctoral, se han llevado a cabo múltiples análisis relativos a diferentes metodologías de procesado de señales y obtención métricas derivadas del ECGI con el fin de caracterizar mejor el sustrato cardíaco y la actividad reentrante en las señales de ECGI de pacientes con FA. Con el objetivo de obtener una comprensión más profunda de los mecanismos electrofisiológicos subyacentes a la FA, hemos establecido la estrategia de filtrado óptima para extraer patrones reentrantes específicos del paciente y métricas derivadas de señales ECGI. Además, hemos investigado la reproducibilidad de los mapas de reentradas derivados de las señales de ECGI y hemos encontrado su relación con el éxito de la ablación de venas pulmonares (PVI). Nuestros resultados han mostrado que una mayor reproducibilidad en los patrones reentrantes de FA detectados con ECGI está relacionada con el éxito de la PVI, creando una metodología para estratificar a los pacientes con FA antes de los procedimientos de ablación.[CA] La fibril·lació auricular (FA) és l'arrítmia més prevalent al món i està associada amb una elevada morbiditat, mortalitat i costos sanitaris. Malgrat els avanços en opcions de tractament farmacològic i teràpies d'ablació, el maneig de la FA encara té marge de millora. La imatge electrocardiogràfica (ECGI) s'ha destacat com un prometedor mètode no invasiu per a avaluar l'electrofisiologia cardíaca i guiar les decisions terapèutiques en casos de fibril·lació auricular. No obstant això, l'ECGI s'enfronta a desafiaments com la necessitat de resoldre de manera precisa el denominat problema invers de la electrocardiografia i d'optimitzar la qualitat de les reconstruccions de ECGI. A més, la integració del ECGI en els processos clínics rutinaris continua sent un repte, en gran manera a causa dels costos que suposa la necessitat d'imatges cardíaques. Per això, els objectius principals d'aquesta tesi doctoral són impulsar la tecnologia de l'ECGI mitjançant la determinació dels seus requisits tècnics mínims i la millora de les metodologies existents per obtenir senyals d'ECGI precises. A més, busquem avaluar la capacitat de l'ECGI per quantificar de forma no invasiva la complexitat de la FA. Per a aconseguir aquests objectius, s'han dut a terme diversos estudis al llarg de la tesi, des del perfeccionament de l'ECGI fins a l'avaluació de la FA utilitzant aquesta tecnologia. En primer lloc, hem estudiat els requisits geomètrics i de senyal del problema invers mitjançant l'estudi dels efectes de la densitat de la malla del tors i la distribució d'elèctrodes en la precisió de l'ECGI, el que ha conduït a la identificació del nombre mínim de nodes i la seva distribució en la malla del tors. A més, hem identificat que per obtindre senyals d'ECGI d'alta qualitat, és crucial la correcta disposició dels elèctrodes en la malla del tors reconstruïda. També s'ha definit i avaluat una nova metodologia d'ECGI sense necessitat d'utilitzar tècniques d'imatge cardíaca. Per a això, hem comparat mètriques derivades de l'ECGI calculades amb la geometria original del cor dels pacients amb les mètriques mesurades en diferents geometries cardíaques. Els nostres resultats han mostrat que l'ECGI sense necessitat d'imatges cardíaques és efectiu per a la correcta quantificació i localització dels patrons i zones que mantenen la FA. Paral·lelament, hem optimitzat la regularització de Tikhonov d'ordre zero actual i l'optimització de la corba L per al càlcul de les senyals d'ECGI, investigant com el soroll elèctric i les incerteses geomètriques influeixen en la regularització. Addicionalment, vam proposar un nou criteri que reforça la precisió de les solucions d'ECGI en escenaris amb incertesa degut a condicions de senyal no ideals. En segon lloc, en aquesta tesi doctoral, s'han dut a terme múltiples anàlisis relatius a diferents metodologies de processament de senyals i obtenció de mètriques derivades de l'ECGI amb l'objectiu de caracteritzar millor el substrat cardíac i l'activitat reentrant en les senyals d'ECGI de pacients amb FA. Amb l'objectiu d'obtindre una comprensió més profunda dels mecanismes electrofisiològics subjacents a la FA, hem establert l'estratègia de filtrat òptima per extreure patrons reentrants específics del pacient i mètriques derivades de senyals ECGI. A més, hem investigat la reproductibilitat dels mapes de reentrades derivats de les senyals d'ECGI i hem trobat la seva relació amb l'èxit de l'ablació de venes pulmonars (PVI). Els nostres resultats han mostrat que una major reproductibilitat en els patrons reentrants de FA detectats amb ECGI està relacionada amb l'èxit de la PVI, creant una metodologia per estratificar els pacients amb FA abans dels procediments d'ablació.[EN] Atrial fibrillation (AF) is the most prevalent arrhythmia in the world and is associated with significant morbidity, mortality, and healthcare costs. Despite advancements in pharmaceutical treatment alternatives and ablation therapy, AF management remains suboptimal. Electrocardiographic Imaging (ECGI) has emerged as a promising non-invasive method for assessing cardiac electrophysiology and guiding therapeutic decisions in atrial fibrillation. However, ECGI faces challenges in dealing with accurately resolving the ill-posed inverse problem of electrocardiography and optimizing the quality of ECGI reconstructions. Additionally, the integration of ECGI into clinical workflows is still a challenge that is hindered by the associated costs arising from the need for cardiac imaging. For this purpose, the main objectives of this PhD thesis are to advance ECGI technology by determining the minimal technical requirements and refining existing methodologies for acquiring accurate ECGI signals. In addition, we aim to assess the capacity of ECGI for noninvasively quantifying AF complexity. To fulfill these objectives, several studies were developed throughout the thesis, advancing from ECGI enhancement to AF evaluation using ECGI. Firstly, geometric and signal requirements of the inverse problem were addressed by studying the effects of torso mesh density and electrode distribution on ECGI accuracy, leading to the identification of the minimal number of nodes and their distribution on the torso mesh. Besides, we identified that the correct location of the electrodes on the reconstructed torso mesh is critical for the accurate ECGI signal obtention. Additionally, a new methodology of imageless ECGI was defined and assessed by comparing ECGI-derived drivers computed with the original heart geometry of the patients to the drivers measured in different heart geometries. Our results showed the ability of imageless ECGI to the correct quantification and location of atrial fibrillation drivers, validating the use of ECGI without the need for cardiac imaging. Also, the current state of-the-art zero-order Tikhonov regularization and L-curve optimization for computing ECGI signals were improved by investigating the impact of electrical noise and geometrical uncertainties on the regularization. We proposed a new criterion that enhances the accuracy and reliability of ECGI solutions in situations with uncertainty from unfavorable signal conditions. Secondly, in this PhD thesis, several analyses, signal processing methodologies, and ECGIderived metrics were investigated to better characterize the cardiac substrate and reentrant activity in ECGI signals from AF patients. With the objective of obtaining a deeper understanding of the electrophysiological mechanisms underlying AF, we established the optimal filtering strategy to extract patient-specific reentrant patterns and derived metrics in ECGI signals. Furthermore, we investigated the reproducibility of the obtained ECGI-reentrant maps and linked them to the success of PVI ablation. Our results showed that higher reproducibility on AF drivers detected with ECGI is linked with the success of PVI, creating a proof-of-concept mechanism for stratifying AF patients prior to ablation procedures.This work was supported by: Instituto de Salud Carlos III, and Ministerio de Ciencia e Innovación (supported by FEDER Fondo Europeo de Desarrollo Regional DIDIMO PLEC2021- 007614, ESSENCE PID2020-119364RB-I00, and RYC2018- 024346B-750), EIT Health (Activity code SAVE-COR 220385, EIT Health is supported by EIT, a body of the European Union) and Generalitat Valenciana Conselleria d’Educació, Investigació, Cultura i Esport (ACIF/2020/265 and BEFPI/2021/062).Molero Alabau, R. (2023). Estimation of Atrial Electrical Complexity during Atrial Fibrillation by Solving the Inverse Problem of Electrocardiography [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/199029Compendi

Electrocardiographic Imaging in Atrial Fibrillation: Selection of the Optimal Tikhonov-Regularization Parameter

[EN] Electrocardiographic imaging (ECGI) allows evaluating the complexity of atrial fibrillation (AF) signals using the Boundary Element Method and Tikhonov regularization. An accurate ECGI reconstruction is dependent on a proper selection of the regularization parameter (¿). In this work, two ranges of ¿ are explored to evaluate the effect of ¿ on the quality of the ECGI reconstruction. ECGIs of 20 AF patients were computed using zero (T0), first (T1) and second (T2) order Tikhonov regularization (TR) for two ranges of ¿: from 10-9 to 102 and 10-12 to 10-4. Dominant frequencies (DF) and the number of rotors obtained with the two ranges and methods were compared. Zero-order Tikhonov showed to be more robust in ¿ selection for different ¿ ranges. For lower ¿ ranges, higher DF was found (T2, p<0.05) and more rotors were detected for T1 and T2 (p<0.01). Differences between TR methods compared by ¿ ranges showed more variability in derived metrics for lower ¿ range (p<0.01). Optimal ranges for ¿ search differ among T0, T1 and T2. Election of lower than optimal ¿ values result in an increased estimated electrical complexity.This work was supported by: Instituto de Salud Carlos III, and Ministerio de Ciencia, Innovación y Universidades (supported by FEDER Fondo Europeo de Desarrollo Regional PI17/01106 and RYC2018-024346B-750), EIT Health (Activity code 19600, EIT Health is supported by EIT, a body of the European Union), Generalitat Valenciana Grants (ACIF/2020/265) and PersonalizeAF project, which received funding from the European Union¿s Horizon 2020 research and innovation programme under the Marie Skodowska-Curie grant agreement No 860974. This publication reflects only the author's view and the Agency is not responsible for any use that maybe made of the information it contains.Molero-Alabau, R.; Fambuena, C.; Climent, AM.; Guillem Sánchez, MS. (2021). Electrocardiographic Imaging in Atrial Fibrillation: Selection of the Optimal Tikhonov-Regularization Parameter. 1-4. https://doi.org/10.22489/CinC.2021.2161

Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location

[EN] Introduction: Electrocardiographic Imaging is a non-invasive technique that requires cardiac Imaging for the reconstruction of cardiac electrical activity. In this study, we explored imageless ECGI by quantifying the errors of using heart meshes with either an inaccurate location inside the thorax or an inaccurate geometry. Methods: Multiple-lead body surface recordings of 25 atrial fibrillation (AF) patients were recorded. Cardiac atrial meshes were obtained by segmentation of medical images obtained for each patient. ECGI was computed with each patient's segmented atrial mesh and compared with the ECGI obtained under errors in the atrial mesh used for ECGI estimation. We modeled both the uncertainty in the location of the atria inside the thorax by artificially translating the atria inside the thorax and the geometry of the atrial mesh by using an atrial mesh in a reference database. ECGI signals obtained with the actual meshes and the translated or estimated meshes were compared in terms of their correlation coefficients, relative difference measurement star, and errors in the dominant frequency (DF) estimation in epicardial nodes.Results: CC between ECGI signals obtained after translating the actual atrial meshes from the original position by 1 cm was above 0.97. CC between ECGIs obtained with patient specific atrial geometry and estimated atrial geometries was 0.93 +/- 0.11. Mean errors in DF estimation using an estimated atrial mesh were 7.6 +/- 5.9%.Conclusion: Imageless ECGI can provide a robust estimation of cardiac electrophysiological parameters such as activation rates even during complex arrhythmias. Furthermore, it can allow more widespread use of ECGI in clinical practice.This work was supported by: Instituto de Salud Carlos III, and Ministerio de Ciencia e Innovacion (supported by FEDER Fondo Europeo de Desarrollo Regional DIDIMO PLEC2021-007614, ESSENCE PID2020-119364RB-I00, and RYC2018-024346-I) , EIT Health (Activity code SAVE-COR 220385, EIT Health is supported by EIT, a body of the Eu-ropean Union) and Generalitat Valenciana Conselleria d'Educacio, Investigacio, Cultura i Esport (ACIF/2020/265) . The authors want to thank the organizers of the 2022 meeting of the International Society for Computerized Electrocardiology for their invitation to the meeting.Molero-Alabau, R.; González-Ascaso, A.; Climent, AM.; Guillem Sánchez, MS. (2023). Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location. Journal of Electrocardiology. 77:58-61. https://doi.org/10.1016/j.jelectrocard.2022.12.00758617

Filtering strategies of electrocardiographic imaging signals for stratification of atrial fibrillation patients

[EN] Background and objective: Electrocardiographic imaging (ECGI) has been used for guiding atrial fibrillation (AF) ablation, identifying reentrant activity by phase analysis with promising results. The objective of this study is to identify the best post-processing configuration for reentrant activity detection that better differentiates AF pa-tients with different prognoses after catheter ablation.Methods: ECGI signals of 24 AF patients before pulmonary vein isolation (PVI) were recorded. Patients were classified based on recurrence 6 months after PVI. Reentrant metrics were compared using 3 types of post -processing: none, sinusoidal recomposition (SRC), and narrow band-pass filtering centered at the highest dominant frequency (NB HDF). Different thresholds for rotor duration were also compared (0.5, 1, and 1.5 turns). Results: The use of raw ECGI signals with a threshold of 1 turn presented the optimal processing to identify PVI-positive responders (p < 0.05). NB HDF showed a better ability to find statistical differences between patients than SRC.Conclusion: Aggressive filtering of AF ECGI signals does not improve rotor identification to predict PVI outcome. Restrictive rotor duration thresholds diminish patient stratification. This definition of a post-processing strategy that allows patient stratification can be used for the improvement of the standard of care for finding the best candidates for PVI.This work was supported in part by: Instituto de Salud Carlos III FEDER (Fondo Europeo de Desarrollo Regional PI17/01106) , Agencia Estatal de Investigacion (RYC2018-024346-I and PID2020-119364RB-100) , Generalitat Valenciana Grants (ACIF/2020/265) and EIT Health (Activity code 19600) EIT Health is supported by EIT, a body of the European Union.Molero-Alabau, R.; Hernández-Romero, I.; M. Climent, A.; Guillem Sánchez, MS. (2023). Filtering strategies of electrocardiographic imaging signals for stratification of atrial fibrillation patients. Biomedical Signal Processing and Control. 81. https://doi.org/10.1016/j.bspc.2022.1044388

An evaluation on the clinical outcome prediction of rotor detection in non-invasive phase maps

[EN] Phase maps obtained from Electrocardiographic imaging (ECGI) have been used in the past for rotor identification and ablation guidance in atrial fibrillation (AF). In this study, we propose a new rotor detection algorithm and evaluate its potential use for prediction of pulmonary vein isolation (PVI) success. The mean precision and recall of the algorithm were evaluated by using manually annotated ECGI phase maps and resulted in 0.82 and 0.75, respectively. Phase singularities and rotors were then quantified on ECGI signals from 29 patients prior to PVI. A significantly higher concentration of phase singularities (PSs) in the pulmonary veins in patients with a successful PVI was found. Our results suggest that rotorrelated metrics obtained from ECGI derived phase maps contain relevant information to predict clinical outcome in PVI patients.This work was supported by PersonalizeAF project. This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie grant agreement No 860974.Fambuena-Santos, C.; Hernández-Romero, I.; Molero-Alabau, R.; Climent, AM.; Guillem Sánchez, MS. (2021). An evaluation on the clinical outcome prediction of rotor detection in non-invasive phase maps. 1-4. https://doi.org/10.22489/CinC.2021.2511

Effects of Geometry in Atrial Fibrillation Markers Obtained With Electrocardiographic Imaging

[EN] Electrocardiographic imaging (ECGI) can characterise cardiac pathologies such as atrial fibrillation (AF) through specific markers based on frequency or phase analysis. In this study, the effect of the geometry of patients torso and atria in the ECGI resolution is studied. A realistic 3D atrial geometry was located on 30 patient torsos and ECGI signals were calculated for 30 different AF simulations in each torso. Dominant frequency (DF) and reentrant activity analysis were calculated for each scenario. Anatomical and geometrical measurements of each torso (30-80% of variability between patients) and atria were calculated and compared with the errors in the ECGI estimation versus the departing EGM maps. Results show evidences that big chest dimensions worsen the non-invasive calculation of AF markers (p<0.05). Also, higher number of visible electrodes from each atrial region improves ECGI characterization measured as lower DF deviations (0.64±0.26 Hz vs 0.72±0.27 Hz, p<0.05) and higher reentrant activity coincidence (10.1±12.2% vs 3.4±3.4%, p<0.05). Torso and atrial geometry affect the quality of the non-invasive reconstruction of AF markers such as DF or reentrant activity. Knowing the geometrical parameters that worsen non-invasive AF maps may help to measure each detected AF driver reliability.Supported in part by: Instituto de Salud Carlos III FEDER (Fondo Europeo de Desarrollo Regional; IJCI2014-22178, DTS16/00160; PI14/00857, PI16/01123; PI17/01059; PI17/01106), Generalitat Valenciana Grants (APOSTD/2017 and APOSTD/2018) and projects (GVA/2018/103) and EIT-Health 19600 AFFINE.Molero-Alabau, R.; Climent, AM.; Hernández-Romero, I.; Liberos, A.; Fernández-Avilés, F.; Atienza, F.; Guillem Sánchez, MS.... (2019). Effects of Geometry in Atrial Fibrillation Markers Obtained With Electrocardiographic Imaging. IEEE. 1-4. https://doi.org/10.22489/CinC.2019.3081

Análisis de la coordinación de las articulaciones del miembro inferior en bipedestación

[ES] El objetivo del trabajo es estudiar la coordinación de las articulaciones del miembro inferior (Rodilla, Cadera y Tobillo) para el mantenimiento del equilibrio en postura de bipedestación. Para ello se registrarán los movimientos de usuarios reales. La instrumentación utilizada para el registro serán IMUs (Inertial Measurement Units). Las medidas obtenidas se tratarán mediante librerías de software científico y se realizará un análisis estadístico para permitir obtener un modelo fiable de los movimientos del centro de gravedad en bipedestación con el menor número posible de sensores.Molero Alabau, R. (2017). Análisis de la coordinación de las articulaciones del miembro inferior en bipedestación. http://hdl.handle.net/10251/84921.TFG

Investigación experimental de los efectos no térmicos de ondas milimétricas en la conductividad de soluciones electrolíticas acuosas

[ES] Se ha demostrado en diversos estudios los efectos no térmicos de las ondas milimétricas (MMW) en sistemas biológicos. Algunos autores han demostrado que las MMW pueden mejorar la difusión de los iones en soluciones acuosas sin incrementar la temperatura de las mismas. En este Trabajo de Fin de Máster se ha realizado una investigación de un nuevo método de medida para detectar los efectos de las MMW en soluciones electrolíticas. Para medir los cambios en la difusión se ha diseñado un sistema para medir las propiedades eléctricas de las soluciones estudiadas. Se han realizado experimentos con soluciones de 0.9% NaCl en agua aplicando MMW de 10 y 60 GHz. No se han observado cambios significativos en la difusión de los iones tras la aplicación de las MMW a excepción de experimentos con una mayor concentración de NaCl. La base para futuros experimentos en este campo se ha establecido tras esta investigación.[EN] It has been demonstrated in several studies d the non-thermal effects of millimetre waves (MMW) in biological systems. Some authors have demonstrated that MMW can enhance the diffusion of ions in aqueous solutions without an increase of the temperature. In this master thesis a research of a new method to detect the effects of MMW in electrolyte solutions have been done. To measure the changes in the solutions an electrical measurement system has been designed. Experiments with 0.9% NaCl applying MMW of 10 and 60 GHz have been done. It has not been demonstrated significative changes of an enhance of the ionic diffusion in this research except for solutions with high salt concentration in water. The basis for future experiments in this field have been established.Molero Alabau, R. (2018). Experimental investigation of non-thermal millimeter wave effects on conductivity in aqueous electrolyte solutions. http://hdl.handle.net/10251/131560TFG

Analysis of Atrial Fibrillation Dynamics in Body Surface Potential Maps and Electrocardiographic Imaging

International audiencePrevious studies have shown that global short-(ST) and long-term (LT) atrial fibrillation (AF) dynamics can be characterized non-invasively by Body Surface Potentials (BSPM). Also, Electrocardiographic Imaging (ECGI) may add information as it can characterize locally the atrial substrate. The objective of this study is to compare AF dynamics characterized on both BSPM and ECGI signals. Two consecutive 4-second BSPM signals from 34 AF patients (23 male, 8 paroxysmal, 63.1± 9.5 years) were recorded, followed by ECGI computation. ST and LT dynamics metrics were computed in both BSPM and ECGI, assessed from a multivariate autocorrelation of the signals. BSPM features of ST dynamics positively correlated with LT dynamics (0.52 and 0.78). Analogous values of correlation were obtained in ECGI. When normalized by the LT dynamics, the ST inversely correlated with the speed of propagation of AF at half AF cycle (BSPM, r =-0.28 vs. ECGI, r =-0.45), showing higher stability in the ST propagation for faster AF. BSPM and ECGI reflected similar relationships in the analysis of AF propagation dynamics. Results were consistent with previous studies and suggest that BSPM are sufficient to characterize global AF dynamics, while ECGI may become relevant when more localized information is required