Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality

[EN] Electrocardiographic Imaging has become an increasingly used technique for non-invasive diagnosis of cardiac arrhythmias, although the need for medical imaging technology to determine the anatomy hinders its introduction in the clinical practice. This paper explores the ability of a new metric based on the inverse reconstruction quality for the location and orientation of the atrial surface inside the torso. Body surface electrical signals from 31 realistic mathematical models and four AF patients were used to estimate the optimal position of the atria inside the torso. The curvature of the L-curve from the Tikhonov method, which was found to be related to the inverse reconstruction quality, was measured after application of deviations in atrial position and orientation. Independent deviations in the atrial position were solved by finding the maximal L-curve curvature with an error of 1.7 +/- 2.4 mm in mathematical models and 9.1 +/- 11.5 mm in patients. For the case of independent angular deviations, the error in location by using the L-curve was 5.8 +/- 7.1 degrees in mathematical models and 12.4 degrees +/- 13.2 degrees in patients. The ability of the L-curve curvature was tested also under superimposed uncertainties in the three axis of translation and in the three axis of rotation, and the error in location was of 2.3 +/- 3.2 mm and 6.4 degrees +/- 7.1 degrees in mathematical models, and 7.9 +/- 10.7 mm and 12.1 degrees +/- 15.5 degrees in patients. The curvature of L-curve is a useful marker for the atrial position and would allow emending the inaccuracies in its location.This work was supported in part by Generalitat Valenciana under Grant ACIF/2013/021, in part by the Instituto de Salud Carlos III, Ministry of Economy and Competitiveness, Spain, under Grant PI13-01882, Grant PI13-00903, Grant PI14/00857, Grant TEC2013-46067-R, and Grant DTS16/00160, in part by the Spanish Society of Cardiology (Grant for Clinical Research in Cardiology 2015), and in part by the Spanish Ministry of Science and Innovation (Red RIC) under Grant PLE2009-0152.Rodrigo Bort, M.; Climent, AM.; Liberos Mascarell, A.; Hernández-Romero, I.; Arenal, A.; Bermejo, J.; Fernández-Avilés, F.... (2018). Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality. IEEE Transactions on Medical Imaging. 37(3):733-740. https://doi.org/10.1109/TMI.2017.2707413S73374037

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

Atrial location optimization by electrical measures for Electrocardiographic Imaging

[EN] Background: The Electrocardiographic Imaging (ECGI) technique, used to non-invasively reconstruct the epicardial electrical activity, requires an accurate model of the atria and torso anatomy. Here we evaluate a new automatic methodology able to locate the atrial anatomy within the torso based on an intrinsic electrical parameter of the ECGI solution. Methods: In 28 realistic simulations of the atrial electrical activity, we randomly displaced the atrial anatomy for +/- 2.5 cm and +/- 30 degrees on each axis. An automatic optimization method based on the L-curve curvature was used to estimate the original position using exclusively non-invasive data. Results: The automatic optimization algorithm located the atrial anatomy with a deviation of 0.5 +/- 0.5 cm in position and 16.0 +/- 10.7 degrees in orientation. With these approximate locations, the obtained electrophysiological maps reduced the average error in atrial rate measures from 1.1 +/- 1.1 Hz to 0.5 +/- 1.0 Hz and in the phase singularity position from 7.2 +/- 4.0 cm to 1.6 +/- 1.7 cm (p < 0.01). Conclusions: This proposed automatic optimization may help to solve spatial inaccuracies provoked by cardiac motion or respiration, as well as to use ECGI on torso and atrial anatomies from different medical image systems.This work was supported in part by: Generalitat Valenciana Grants [APOSTD/2017] and projects [GVA/2018/103]; Nvidia Corporation with GPU QUADRO P6000 donation.Gisbert Soler, V.; Jiménez-Serrano, S.; Roses-Albert, E.; Rodrigo Bort, M. (2020). Atrial location optimization by electrical measures for Electrocardiographic Imaging. Computers in Biology and Medicine. 127:1-8. https://doi.org/10.1016/j.compbiomed.2020.104031S18127Cuculich, P. S., Zhang, J., Wang, Y., Desouza, K. A., Vijayakumar, R., Woodard, P. K., & Rudy, Y. (2011). The Electrophysiological Cardiac Ventricular Substrate in Patients After Myocardial Infarction. Journal of the American College of Cardiology, 58(18), 1893-1902. doi:10.1016/j.jacc.2011.07.029Revishvili, A. S., Wissner, E., Lebedev, D. S., Lemes, C., Deiss, S., Metzner, A., … Kuck, K.-H. (2015). Validation of the mapping accuracy of a novel non-invasive epicardial and endocardial electrophysiology system. Europace, 17(8), 1282-1288. doi:10.1093/europace/euu339Haissaguerre, M., Hocini, M., Denis, A., Shah, A. J., Komatsu, Y., Yamashita, S., … Dubois, R. (2014). Driver Domains in Persistent Atrial Fibrillation. Circulation, 130(7), 530-538. doi:10.1161/circulationaha.113.005421PEDRÓN-TORRECILLA, J., RODRIGO, M., CLIMENT, A. M., LIBEROS, A., PÉREZ-DAVID, E., BERMEJO, J., … GUILLEM, M. S. (2016). Noninvasive Estimation of Epicardial Dominant High-Frequency Regions During Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 27(4), 435-442. doi:10.1111/jce.12931Cuculich, P. S., Wang, Y., Lindsay, B. D., Faddis, M. N., Schuessler, R. B., Damiano, R. J., … Rudy, Y. (2010). Noninvasive Characterization of Epicardial Activation in Humans With Diverse Atrial Fibrillation Patterns. Circulation, 122(14), 1364-1372. doi:10.1161/circulationaha.110.945709Wang, Y., Schuessler, R. B., Damiano, R. J., Woodard, P. K., & Rudy, Y. (2007). Noninvasive electrocardiographic imaging (ECGI) of scar-related atypical atrial flutter. Heart Rhythm, 4(12), 1565-1567. doi:10.1016/j.hrthm.2007.08.019Milan Horáček, B., & Clements, J. C. (1997). The inverse problem of electrocardiography: A solution in terms of single- and double-layer sources on the epicardial surface. Mathematical Biosciences, 144(2), 119-154. doi:10.1016/s0025-5564(97)00024-2Rodrigo, M., Climent, A. M., Liberos, A., Hernandez-Romero, I., Arenal, A., Bermejo, J., … Guillem, M. S. (2018). Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality. IEEE Transactions on Medical Imaging, 37(3), 733-740. doi:10.1109/tmi.2017.2707413Dössel, O., Krueger, M. W., Weber, F. M., Wilhelms, M., & Seemann, G. (2012). Computational modeling of the human atrial anatomy and electrophysiology. Medical & Biological Engineering & Computing, 50(8), 773-799. doi:10.1007/s11517-012-0924-6Koivumäki, J. T., Seemann, G., Maleckar, M. M., & Tavi, P. (2014). In Silico Screening of the Key Cellular Remodeling Targets in Chronic Atrial Fibrillation. PLoS Computational Biology, 10(5), e1003620. doi:10.1371/journal.pcbi.1003620Garcia-Molla, V. M., Liberos, A., Vidal, A., Guillem, M. S., Millet, J., Gonzalez, A., … Climent, A. M. (2014). Adaptive step ODE algorithms for the 3D simulation of electric heart activity with graphics processing units. Computers in Biology and Medicine, 44, 15-26. doi:10.1016/j.compbiomed.2013.10.023Rodrigo, M., Climent, A. M., Liberos, A., Fernández-Avilés, F., Berenfeld, O., Atienza, F., & Guillem, M. S. (2017). Highest dominant frequency and rotor positions are robust markers of driver location during noninvasive mapping of atrial fibrillation: A computational study. Heart Rhythm, 14(8), 1224-1233. doi:10.1016/j.hrthm.2017.04.017Dolan, E. D., Lewis, R. M., & Torczon, V. (2003). On the Local Convergence of Pattern Search. SIAM Journal on Optimization, 14(2), 567-583. doi:10.1137/s1052623400374495Rodrigo, M., Guillem, M. S., Climent, A. M., Pedrón-Torrecilla, J., Liberos, A., Millet, J., … Berenfeld, O. (2014). Body surface localization of left and right atrial high-frequency rotors in atrial fibrillation patients: A clinical-computational study. Heart Rhythm, 11(9), 1584-1591. doi:10.1016/j.hrthm.2014.05.013Sanders, P., Berenfeld, O., Hocini, M., Jaïs, P., Vaidyanathan, R., Hsu, L.-F., … Haïssaguerre, M. (2005). Spectral Analysis Identifies Sites of High-Frequency Activity Maintaining Atrial Fibrillation in Humans. Circulation, 112(6), 789-797. doi:10.1161/circulationaha.104.517011Atienza, F., Almendral, J., Ormaetxe, J. M., Moya, Á., Martínez-Alday, J. D., Hernández-Madrid, A., … Jalife, J. (2014). Comparison of Radiofrequency Catheter Ablation of Drivers and Circumferential Pulmonary Vein Isolation in Atrial Fibrillation. Journal of the American College of Cardiology, 64(23), 2455-2467. doi:10.1016/j.jacc.2014.09.053Rodrigo, M., Climent, A. M., Liberos, A., Fernández-Avilés, F., Berenfeld, O., Atienza, F., & Guillem, M. S. (2017). Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activity in Direct- and Inverse-Computed Electrograms. Circulation: Arrhythmia and Electrophysiology, 10(9). doi:10.1161/circep.117.005008Miller, J. M., Kalra, V., Das, M. K., Jain, R., Garlie, J. B., Brewster, J. A., & Dandamudi, G. (2017). Clinical Benefit of Ablating Localized Sources for Human Atrial Fibrillation. Journal of the American College of Cardiology, 69(10), 1247-1256. doi:10.1016/j.jacc.2016.11.079Perez-Alday, E. A., Thomas, J. A., Kabir, M., Sedaghat, G., Rogovoy, N., van Dam, E., … Tereshchenko, L. G. (2018). Torso geometry reconstruction and body surface electrode localization using three-dimensional photography. Journal of Electrocardiology, 51(1), 60-67. doi:10.1016/j.jelectrocard.2017.08.035Schulze, W. H. W., Mackens, P., Potyagaylo, D., Rhode, K., Tülümen, E., Schimpf, R., … Dössel, O. (2014). Automatic camera-based identification and 3-D reconstruction of electrode positions in electrocardiographic imaging. Biomedical Engineering / Biomedizinische Technik, 59(6). doi:10.1515/bmt-2014-0018Ghanem, R. N., Ramanathan, C., Ping Jia, & Rudy, Y. (2003). Heart-surface reconstruction and ecg electrodes localization using fluoroscopy, epipolar geometry and stereovision: application to noninvasive imaging of cardiac electrical activity. IEEE Transactions on Medical Imaging, 22(10), 1307-1318. doi:10.1109/tmi.2003.818263Lee, J., Thornhill, R. E., Nery, P., Robert deKemp, Peña, E., Birnie, D., … Ukwatta, E. (2019). Left atrial imaging and registration of fibrosis with conduction voltages using LGE-MRI and electroanatomical mapping. Computers in Biology and Medicine, 111, 103341. doi:10.1016/j.compbiomed.2019.103341Weiss, E., Wijesooriya, K., Dill, S. V., & Keall, P. J. (2007). Tumor and normal tissue motion in the thorax during respiration: Analysis of volumetric and positional variations using 4D CT. International Journal of Radiation Oncology*Biology*Physics, 67(1), 296-307. doi:10.1016/j.ijrobp.2006.09.009Wikström, K., Isacsson, U., Nilsson, K., & Ahnesjö, A. (2018). Reproducibility of heart and thoracic wall position in repeated deep inspiration breath holds for radiotherapy of left-sided breast cancer patients. Acta Oncologica, 57(10), 1318-1324. doi:10.1080/0284186x.2018.1490027Messinger-Rapport, B. J., & Rudy, Y. (1986). The Inverse Problem in Electrocardiography: A Model Study of the Effects of Geometry and Conductivity Parameters on the Reconstruction of Epicardial Potentials. IEEE Transactions on Biomedical Engineering, BME-33(7), 667-676. doi:10.1109/tbme.1986.325756Messinger-Rapport, B. J., & Rudy, Y. (1990). Noninvasive recovery of epicardial potentials in a realistic heart-torso geometry. Normal sinus rhythm. Circulation Research, 66(4), 1023-1039. doi:10.1161/01.res.66.4.1023Coll-Font, J., & Brooks, D. H. (2018). Tracking the Position of the Heart From Body Surface Potential Maps and Electrograms. Frontiers in Physiology, 9. doi:10.3389/fphys.2018.01727Van der Waal, J., Meijborg, V., Schuler, S., Coronel, R., & Oostendorp, T. (2020). In silico validation of electrocardiographic imaging to reconstruct the endocardial and epicardial repolarization pattern using the equivalent dipole layer source model. Medical & Biological Engineering & Computing, 58(8), 1739-1749. doi:10.1007/s11517-020-02203-yChamorro-Servent, J., Dubois, R., & Coudière, Y. (2019). Considering New Regularization Parameter-Choice Techniques for the Tikhonov Method to Improve the Accuracy of Electrocardiographic Imaging. Frontiers in Physiology, 10. doi:10.3389/fphys.2019.0027

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

Noninvasive Assessment of Complexity of Atrial Fibrillation Correlation With Contact Mapping and Impact of Ablation

[EN] Background: It is difficult to noninvasively phenotype atrial fibrillation (AF) in a way that reflects clinical end points such as response to therapy. We set out to map electrical patterns of disorganization and regions of reentrant activity in AF from the body surface using electrocardiographic imaging, calibrated to panoramic intracardiac recordings and referenced to AF termination by ablation. Methods: Bi-atrial intracardiac electrograms of 47 patients with AF at ablation (30 persistent, 29 male, 63 +/- 9 years) were recorded with 64-pole basket catheters and simultaneous 57-lead body surface ECGs. Atrial epicardial electrical activity was reconstructed and organized sites were invasively and noninvasively tracked in 3-dimension using phase singularity. In a subset of 17 patients, sites of AF organization were targeted for ablation. Results: Body surface mapping showed greater AF organization near intracardially detected drivers than elsewhere, both in phase singularity density (2.3 +/- 2.1 versus 1.9 +/- 1.6; P=0.02) and number of drivers (3.2 +/- 2.3 versus 2.7 +/- 1.7; P=0.02). Complexity, defined as the number of stable AF reentrant sites, was concordant between noninvasive and invasive methods (r(2)=0.5; CC=0.71). In the subset receiving targeted ablation, AF complexity showed lower values in those in whom AF terminated than those in whom AF did not terminate (P<0.01). Conclusions: AF complexity tracked noninvasively correlates well with organized and disorganized regions detected by panoramic intracardiac mapping and correlates with the acute outcome by ablation. This approach may assist in bedside monitoring of therapy or in improving the efficacy of ongoing ablation procedures.This article was supported in part by: Instituto de Salud Carlos III FEDER (Fondo Europeo de Desarrollo Regional; IJCI-2014-22178, DTS16/00160; PI14/00857, PI16/01123; PI17/01059; PI17/01106), Generalitat Valenciana Grants (APOSTD/2017 and APOSTD/2018) and projects (GVA/2018/103); National Institutes of Health (Dr Narayan: R01 HL85537; K24 HL103800); EITHealth 19600 AFFINE.Rodrigo Bort, M.; Martínez Climent, BA.; Hernández-Romero, I.; Liberos Mascarell, A.; Baykaner, T.; Rogers, AJ.; Alhusseini, M.... (2020). Noninvasive Assessment of Complexity of Atrial Fibrillation Correlation With Contact Mapping and Impact of Ablation. Circulation Arrhythmia and Electrophysiology. 13(3):236-246. https://doi.org/10.1161/CIRCEP.119.007700S236246133Calkins H Hindricks G Cappato R Kim YH Saad EB Aguinaga L Akar JG Badhwar VBrugada J Camm J etal 2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensusstatement on catheter and surgical ablation of atrial fibrillation: Executive summary. J Arrhythm.2017;33:369-409Narayan SM Krummen DE Clopton P Shivkumar K Miller JM. Direct or coincidentalelimination of stable rotors or focal sources may explain successful atrial fibrillation ablation:on-treatment analysis of the CONFIRM trial (Conventional ablation for AF with or without focalHaissaguerre M Hocini M Denis A Shah AJ Komatsu Y Yamashita S Daly M Amraoui SZellerhoff S Picat MQ etal. Driver domains in persistent atrial fibrillation. Circulation.2014;130:530-8.Atienza F Almendral J Ormaetxe JM Moya A Martínez-Alday JD Hernández-Madrid ACastellanos E Arribas F Arias MÁ Tercedor L etal. Comparison of radiofrequency catheterablation of drivers and circumferential pulmonary vein isolation in atrial fibrillation: aAtienza, F., Almendral, J., Ormaetxe, J. M., Moya, Á., Martínez-Alday, J. D., Hernández-Madrid, A., … Jalife, J. (2014). Comparison of Radiofrequency Catheter Ablation of Drivers and Circumferential Pulmonary Vein Isolation in Atrial Fibrillation. Journal of the American College of Cardiology, 64(23), 2455-2467. doi:10.1016/j.jacc.2014.09.053Seitz J Bars C Théodore G Beurtheret S Lellouche N Bremondy M Ferracci A Faure JPenaranda G Yamazaki M etal. AF Ablation Guided by Spatiotemporal ElectrogramDispersion Without Pulmonary Vein Isolation: A Wholly Patient-Tailored Approach. J Am CollGuillem MS Climent AM Millet J Arenal Á Fernández-Avilés F Jalife J Atienza FBerenfeld O. Noninvasive localization of maximal frequency sites of atrial fibrillation by bodysurface potential mapping. Circ Arrhythm Electrophysiol. 2013;6:294-301.Ramirez FD Birnie DH Nair GM Szczotka A Redpath CJ Sadek MM Nery PB. Efficacyand safety of driver-guided catheter ablation for atrial fibrillation: A systematic review and metaRamirez, F. D., Birnie, D. H., Nair, G. M., Szczotka, A., Redpath, C. J., Sadek, M. M., & Nery, P. B. (2017). Efficacy and safety of driver-guided catheter ablation for atrial fibrillation: A systematic review and meta-analysis. Journal of Cardiovascular Electrophysiology, 28(12), 1371-1378. doi:10.1111/jce.13313Baykaner T Rogers AJ Meckler GL Zaman J Navara R Rodrigo M Alhusseini MKowalewski CAB Viswanathan MN Narayan SM etal. Clinical Implications of Ablation ofDrivers for Atrial Fibrillation: A Systematic Review and Meta-Analysis. Circ ArrhythmBrachmann J Hummel JD Wilber DJ Sarver AE Rapkin J Shpun S Szili-Torok T.Prospective randomized comparison of rotor ablation vs. conventional ablation for treatment ofVijayakumar R Vasireddi SK Cuculich PS Faddis MN Rudy Y. MethodologyConsiderations in Phase Mapping of Human Cardiac Arrhythmias. Circ ArrhythmAlhusseini M Vidmar D Meckler GL Kowalewski CA Shenasa F Wang PJ Narayan SMRappel WJ. Two Independent Mapping Techniques Identify Rotational Activity Patterns at Sitesof Local Termination During Persistent Atrial Fibrillation. J Cardiovasc Electrophysiol.2017;28:615-622.Miller JM Kalra V Das MK Jain R Garlie JB Brewster JA Dandamudi G. Clinical Benefitof Ablating Localized Sources for Human Atrial Fibrillation: The Indiana University FIRMZaman JAB Baykaner T Clopton P Swarup V Kowal RC Daubert JP Day JD Hummel JSchricker AA Krummen DE etal. Recurrent Post-Ablation Paroxysmal Atrial FibrillationShares Substrates With Persistent Atrial Fibrillation: An 11-Center Study. JACC ClinYushkevich PA Zhang H Gee JC. Continuous medial representation for anatomicalstructures. IEEE Trans Med Imaging. 2006;25:1547-64.Remondino F. 3-D reconstruction of static human body shape from image sequence.Remondino, F. (2004). 3-D reconstruction of static human body shape from image sequence. Computer Vision and Image Understanding, 93(1), 65-85. doi:10.1016/j.cviu.2003.08.006Eggert DW Lorusso A Fish RB. Estimating 3-D rigid body transformations: a comparisonRodrigo M Guillem MS Climent AM Pedrón-Torrecilla J Liberos A Millet J FernándezRodrigo, M., Guillem, M. S., Climent, A. M., Pedrón-Torrecilla, J., Liberos, A., Millet, J., … Berenfeld, O. (2014). Body surface localization of left and right atrial high-frequency rotors in atrial fibrillation patients: A clinical-computational study. Heart Rhythm, 11(9), 1584-1591. doi:10.1016/j.hrthm.2014.05.013Rodrigo M Climent AM Liberos A Fernández-Avilés F Berenfeld O Atienza F GuillemMS. Highest dominant frequency and rotor positions are robust markers of driver location duringMS. Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activityin Direct- and Inverse-Computed Electrograms. Circ Arrhythm Electrophysiol.2017;10:e005008.Castells F Mora C Rieta JJ Moratal-Pérez D Millet J. Estimation of atrial fibrillatory wavefrom single-lead atrial fibrillation electrocardiograms using principal component analysisconcepts. Med Biol Eng Comput. 2005;43:557-560.Rodrigo M Climent AM Liberos A Hernandez-Romero I Arenal A Bermejo J FernandezAviles F Atienza F Guillem MS. Solving Inaccuracies in Anatomical Models forElectrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality. IEEERodrigo, M., Climent, A. M., Liberos, A., Hernandez-Romero, I., Arenal, A., Bermejo, J., … Guillem, M. S. (2018). Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality. IEEE Transactions on Medical Imaging, 37(3), 733-740. doi:10.1109/tmi.2017.2707413Honarbakhsh S Schilling RJ Providência R Dhillon G Sawhney V Martin CA Keating EFinlay M Ahsan S Chow A etal. Panoramic atrial mapping with basket catheters: Aquantitative analysis to optimize practice patient selection and catheter choice. J CardiovascElectrophysiol. 201;28:1423-1432Knecht S Sohal M Deisenhofer I Albenque JP Arentz T Neumann T Cauchemez BDuytschaever M Ramoul K Verbeet T etal. Multicentre evaluation of non-invasive biatrialmapping for persistent atrial fibrillation ablation: the AFACART study. Europace.2017;19:1302-1309.Metzner A Wissner E Tsyganov A Kalinin V Schlüter M Lemes C Mathew S Maurer THeeger CH Reissmann B etal. Noninvasive phase mapping of persistent atrial fibrillation inhumans: Comparison with invasive catheter mapping. Ann Noninvasive Electrocardiol.2018;23:e12527.Duchateau J Sacher F Pambrun T Derval N Chamorro-Servent J Denis A Ploux S HociniM Jaïs P Bernus O etal. Performance and limitations of noninvasive cardiac activationDuchateau, J., Sacher, F., Pambrun, T., Derval, N., Chamorro-Servent, J., Denis, A., … Dubois, R. (2019). Performance and limitations of noninvasive cardiac activation mapping. Heart Rhythm, 16(3), 435-442. doi:10.1016/j.hrthm.2018.10.010Rudy Y. Letter to the Editor-ECG imaging and activation mapping. Heart Rhythm. 2019;16:e50-e.Podziemski P Zeemering S Kuklik P van Hunnik A Maesen B Maessen J Crijns HJWillems S Verma A Betts TR Murray S Neuzil P Ince H Steven D Sultan A Heck PMHall MC etal. Targeting Nonpulmonary Vein Sources in Persistent Atrial Fibrillation IdentifiedLim HS Hocini M Dubois R Denis A Derval N Zellerhoff S Yamashita S Berte BMahida S Komatsu Y etal. Complexity and Distribution of Drivers in Relation to Duration ofCamm AJ Breithardt G Crijns H Dorian P Kowey P Le Heuzey JY Merioua I PedrazziniL Prystowsky EN Schwartz PJ etal. Real-life observations of clinical outcomes with rhythmand rate-control therapies for atrial fibrillation RECORDAF (Registry on Cardiac RhythmCamm, A. J., Breithardt, G., Crijns, H., Dorian, P., Kowey, P., Le Heuzey, J.-Y., … Weintraub, W. (2011). Real-Life Observations of Clinical Outcomes With Rhythm- and Rate-Control Therapies for Atrial Fibrillation. Journal of the American College of Cardiology, 58(5), 493-501. doi:10.1016/j.jacc.2011.03.034Kowalewski CAB Shenasa F Rodrigo M Clopton P Meckler G Alhusseini MI SwerdlowMA Joshi V Hossainy S Zaman JAB etal. Interaction of Localized Drivers and DisorganizedActivation in Persistent Atrial Fibrillation: Reconciling Putative Mechanisms Using MultipleChelu MG King JB Kholmovski EG Ma J Gal P Marashly Q AlJuaid MA Kaur G SilverMA Johnson KA etal. Atrial Fibrosis by Late Gadolinium Enhancement Magnetic ResonanceImaging and Catheter Ablation of Atrial Fibrillation: 5-Year Follow-Up Data. J Am Heart Assoc.2018;7:e006313.Guillem MS Bollmann A Climent AM Husser D Millet-Roig J Castells F. How manyleads are necessary for a reliable reconstruction of surface potentials during atrial fibrillation?De la Salud Guillem, M., Bollmann, A., Climent, A. M., Husser, D., Millet-Roig, J., & Castells, F. (2009). How Many Leads Are Necessary for a Reliable Reconstruction of Surface Potentials During Atrial Fibrillation? IEEE Transactions on Information Technology in Biomedicine, 13(3), 330-340. doi:10.1109/titb.2008.2011894Rodrigo M Climent AM Liberos A Fernández-Aviles F Atienza F Guillem MS BerenfeldO. Minimal configuration of body surface potential mapping for discrimination of left versu

Novel Methods to Incorporate Physiological Prior Knowledge into the Inverse Problem of Electrocardiography - Application to Localization of Ventricular Excitation Origins

17 Millionen Todesfälle jedes Jahr werden auf kardiovaskuläre Erkankungen zurückgeführt. Plötzlicher Herztod tritt bei ca. 25% der Patienten mit kardiovaskulären Erkrankungen auf und kann mit ventrikulärer Tachykardie in Verbindung gebracht werden. Ein wichtiger Schritt für die Behandlung von ventrikulärer Tachykardie ist die Detektion sogenannter Exit-Points, d.h. des räumlichen Ursprungs der Erregung. Da dieser Prozess sehr zeitaufwändig ist und nur von fähigen Kardiologen durchgeführt werden kann, gibt es eine Notwendigkeit für assistierende Lokalisationsmöglichkeiten, idealerweise automatisch und nichtinvasiv. Elektrokardiographische Bildgebung versucht, diesen klinischen Anforderungen zu genügen, indem die elektrische Aktivität des Herzens aus Messungen der Potentiale auf der Körperoberfläche rekonstruiert wird. Die resultierenden Informationen können verwendet werden, um den Erregungsursprung zu detektieren. Aktuelle Methoden um das inverse Problem zu lösen weisen jedoch entweder eine geringe Genauigkeit oder Robustheit auf, was ihren klinischen Nutzen einschränkt. Diese Arbeit analysiert zunächst das Vorwärtsproblem im Zusammenhang mit zwei Quellmodellen: Transmembranspannungen und extrazelluläre Potentiale. Die mathematischen Eigenschaften der Relation zwischen den Quellen des Herzens und der Körperoberflächenpotentiale werden systematisch analysiert und der Einfluss auf das inverse Problem verdeutlicht. Dieses Wissen wird anschließend zur Lösung des inversen Problems genutzt. Hierzu werden drei neue Methoden eingeführt: eine verzögerungsbasierte Regularisierung, eine Methode basierend auf einer Regression von Körperoberflächenpotentialen und eine Deep-Learning-basierte Lokalisierungsmethode. Diese drei Methoden werden in einem simulierten und zwei klinischen Setups vier etablierten Methoden gegenübergestellt und bewertet. Auf dem simulierten Datensatz und auf einem der beiden klinischen Datensätze erzielte eine der neuen Methoden bessere Ergebnisse als die konventionellen Ansätze, während Tikhonov-Regularisierung auf dem verbleibenden klinischen Datensatz die besten Ergebnisse erzielte. Potentielle Ursachen für diese Ergebnisse werden diskutiert und mit Eigenschaften des Vorwärtsproblems in Verbindung gebracht

Tracking the Position of the Heart From Body Surface Potential Maps and Electrograms

The accurate generation of forward models is an important element in general research in electrocardiography, and in particular for the techniques for ElectroCardioGraphic Imaging (ECGI). Recent research efforts have been devoted to the reliable and fast generation of forward models. However, these model can suffer from several sources of inaccuracy, which in turn can lead to considerable error in both the forward simulation of body surface potentials and even more so for ECGI solutions. In particular, the accurate localization of the heart within the torso is sensitive to movements due to respiration and changes in position of the subject, a problem that cannot be resolved with better imaging and segmentation alone. Here, we propose an algorithm to localize the position of the heart using electrocardiographic recordings on both the heart and torso surface over a sequence of cardiac cycles. We leverage the dependency of electrocardiographic forward models on the underlying geometry to parameterize the forward model with respect to the position (translation) and orientation of the heart, and then estimate these parameters from heart and body surface potentials in a numerical inverse problem. We show that this approach is capable of localizing the position of the heart in synthetic experiments and that it reduces the modeling error in the forward models and resulting inverse solutions in canine experiments. Our results show a consistent decrease in error of both simulated body surface potentials and inverse reconstructed heart surface potentials after re-localizing the heart based on our estimated geometric correction. These results suggest that this method is capable of improving electrocardiographic models used in research settings and suggest the basis for the extension of the model presented here to its application in a purely inverse setting, where the heart potentials are unknown

Design and clinical validation of novel imaging strategies for analysis of arrhythmogenic substrate

_CURRENT CHALLENGES IN ELECTROPHYSIOLOGY_ Technical advances in cardiovascular electrophysiology have resulted in an increasing number of catheter ablation procedures reaching 200 000 in Europe for the year 2013. These advanced interventions are often complex and time consuming and may cause significant radiation exposure. Furthermore, a substantial number of ablation procedures remain associated with poor (initial) outcomes and frequently require ≥1 redo procedures. Innovations in modalities for substrate imaging could facilitate our understanding of the arrhythmogenic substrate, improve the design of patient-specific ablation strategies and improve the results of ablation procedures. _NOVEL SUBSTRATE IMAGING MODALITIES_ __Cardiac magnetic resonance__ Cardiac magnetic resonance imaging (CMR) can be considered the most comprehensive and suitable modality for the complete electrophysiology and catheter ablation workup (including patient selection, procedural guidance, and [procedural] follow-up). Utilizing inversion recovery CMR, fibrotic myocardium can be visualized and quantified 10–15 min after intravenous administration of Gadolinium contrast. This imaging technique is known as late Gadolinium enhancement (LGE) imaging. Experimental models have shown excellent agreement between size and shape in LGE CMR and areas of myocardial infarction by histopathology. Recent studies have also demonstrated how scar size, shape and location from pre-procedural LGE can be useful in guiding ventricular tachycardia’s (VT) ablation or atrial fibrillation (AF) ablation. These procedures are often time-consuming due to the preceding electrophysiological mapping study required to identify slow conduction zones involved in re-entry circuits. Post-processed LGE images provide scar maps, which could be integrated with electroanatomic mapping systems to facilitate these procedures. __Inverse potential mapping__ Through the years, various noninvasive electrocardiographic imaging techniques have emerged that estimate epicardial potentials or myocardial activation times from potentials recorded on the thorax. Utilizing an inverse procedure, the potentials on the heart surface or activation times of the myocardium are estimated with the recorded body surface potentials as source data. Although this procedure only estimates the time course of unipolar epicardial electrograms, several studies have demonstrated that the epicardial potentials and electrograms provide substantial information about intramyocardial activity and have great potential to facilitate risk-stratification and generate personalized ablation strategies. __Objectives of this thesis__ 1. To evaluate the utility of cardiac magnetic resonance derived geometrical and tissue characteristic information for patient stratification and guidance of AF ablation. 2. To design and evaluate the performance of a finite element model based inverse potential mapping in predicting the arrhythmogenic focus in idiopathic ventricular tachycardia using invasive electro-anatomical activation mapping as a reference standard

Electrocardiogram Signal Analysis and Simulations for Non-Invasive Diagnosis - Model-Based and Data-Driven Approaches for the Estimation of Ionic Concentrations and Localization of Excitation Origins

Das Elektrokardiogramm (EKG) ist die Standardtechnik zur Messung der elektrischen Aktivität des Herzens. EKG-Geräte sind verfügbar, kostengünstig und erlauben zudem eine nichtinvasive Messung. Das ist insbesondere wichtig für die Diagnose von kardiovaskulären Erkrankungen (KVE). Letztere sind mit verursachten Kosten von 210 Milliarden Euro eine der Hauptbelastungen für das Gesundheitssystem in Europa und dort der Grund für 3,9 Millionen Todesfälle – dies entspricht 45% aller Todesfälle. Neben weiteren Risikofaktoren spielen chronische Nierenerkrankungen und strukturelle Veränderungen des Herzgewebes eine entscheidende Rolle für das Auftreten von KVE. Deshalb werden in dieser Arbeit zwei Pathologien, die in Verbindung zu KVE stehen, betrachtet: Elektrolytkonzentrationsveränderungen bei chronisch Nierenkranken und ektope Foki, die autonom Erregungen iniitieren. In beiden Projekten ist die Entwicklung von Methoden mithilfe von simulierten Signalen zur Diagnoseunterstützung das übergeordnete Ziel. Im ersten Projekt helfen simulierte EKGs die Signalverarbeitungskette zur EKG-basierten Schätzung der Ionenkonzentrationen von Kalium und Calcium zu optimieren. Die Erkenntnisse dieser Optimierung fließen in zwei patienten-spezifische Methoden zur Kaliumkonzentrationsschätzung ein, die wiederum mithilfe von Patientendaten ausgewertet werden. Die Methoden lieferten im Mittel einen absoluten Fehler von 0,37 mmol/l für einen patienten-spezifischen Ansatz und 0,48 mmol/l für einen globalen Ansatz mit zusätzlicher patienten-spezifischer Korrektur. Die Vorteile der Schätzmethoden werden gegenüber bereits existierender Ansätze dargelegt. Alle entwickelten Algorithmen sind ferner unter einer Open-Source-Lizenz veröffentlicht. Das zweite Projekt zielte auf die Lokalisierung von ektopen Foki mithilfe des EKGs ohne die Nutzung der individuellen Patientengeometrie. 1.766.406 simulierte EKG-Signale (Body Surface Potential Maps (BSPMs)) wurden zum Trainieren von zwei Convolutional Neural Networks (CNNs) erzeugt. Das erste CNN sorgt für die Schätzung von Anfang und Ende der Depolarisation der Ventrikel. Das zweite CNN nutzt die Information der Depolarisation im BSPM zur Schätzung des Erregungsurpsrungs. Der spezielle Aufbau des CNNs ermöglicht die Darstellung mehrerer Lösungen, wie sie durch Mehrdeutigkeiten im BSPM vorliegen können. Der kleinste Median des Lokalisierungsfehlers lag bei 1,54 mm für den Test-Datensatz der simulierten Signale, bzw. bei 37 mm für Patientensignale. Somit erlaubt die Kombination beider CNNs die verlässliche Lokalisierung von ektopen Foki auch anhand von Patientendaten, obwohl Patientendaten vorher nicht im Training genutzt wurden. Die Resultate dieser zwei Projekte demonstrieren, wie EKG-Simulationen zur Entwicklung und Verbesserung von EKG-Signalverarbeitungsmethoden eingesetzt werden und bei der Diagnosefindung helfen können. Zudem zeigt sich das Potential der Kombination von Simulationen und CNNs, um einerseits die zumeist raren klinischen Signale zu ersetzen und andererseits Modelle zu finden, die für mehrere Patienten/-innen gültig sind. Die vorgestellten Methoden bergen die Möglichkeit, die Diagnosestellungen zu beschleunigen und mit hoher Wahrscheinlichkeit den Therapieerfolg der Patienten zu verbessern