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

Presence and stability of rotors in atrial fibrillation: evidence and therapeutic implications

[EN] Rotor-guided ablation has opened new perspectives into the therapy of atrial fibrillation (AF). Analysis of the spatio-temporal cardiac excitation patterns in the frequency and phase domains has demonstrated the importance of rotors in research models of AF, however, the dynamics and role of rotors in human AF are still controversial. In this review, the current knowledge gained through research models and patient data that support the notion that rotors are key players in AF maintenance is summarized. We report and discuss discrepancies regarding rotor prevalence and stability in various studies, which can be attributed in part to methodological differences among mapping systems. Future research for validation and improvement of current clinical electrophysiology mapping technologies will be crucial for developing mechanistic-based selection and application of the best therapeutic strategy for individual AF patient, being it, pharmaceutical, ablative, or other approach.This work was supported in part by grants from the Instituto de Salud Carlos III (Ministry of Economy and Competitiveness, Spain: PI13-01882, PI13-00903, and PI14/00857), Spanish Society of Cardiology (Clinical Research Grant 2015), Generalitat Valenciana (ACIF/2013/021), Innovation (Red RIC, PLE2009-0152), and NHLBI (P01-HL039707, P01-HL087226, and R01-HL118304).Guillem Sánchez, MS.; Climent, AM.; Rodrigo Bort, M.; Fernandez-Aviles, F.; Atienza, F.; Berenfeld, O. (2016). Presence and stability of rotors in atrial fibrillation: evidence and therapeutic implications. Cardiovascular Research. 109(4):480-492. https://doi.org/10.1093/cvr/cvw011S480492109

Detection of Atrial Fibrillation Driver Locations Using CNN and Body Surface Potentials

[EN] Atrial fibrillation (AF) is characterized by complex and irregular propagation patterns, and AF onset locations and drivers responsible for its perpetuation are main targets for ablation procedures. Several Deep Learningbased methods have proposed to detect AF, but the estimation of the atrial area where the drivers are found is a topic where further research is needed. In this work, we propose to estimate the zone where AF drivers are found from body surface potentials (BSPs) and Convolutional Neural Networks (CNN), modeling a supervised classification problem. Accuracy in the test set was 0.89 when using noisy BSPs (SNR=20dB), while the Cohen¿s Kappa was 0.85. Therefore, the proposed method could help to identify target regions for ablation using a non-invasive procedure, and avoiding the use of ECG Imaging (ECGI).This work has been partially supported by: Ministerio de Ciencia e Innovacion (PID2019-105032GB-I00), Instituto de Salud Carlos III, and Ministerio de Ciencia, Innovacion y Universidades (supported by FEDER Fondo Europeo de Desarrollo Regional PI17/01106 and RYC2018-024346B-750), Consejeria de Ciencia, Universidades e Innovacion of the Comunidad de Madrid through the program RIS3 (S-2020/L2-622), EIT Health (Activity code 19600, EIT Health is supported by EIT, a body of the European Union) and the European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie grant agreement No. 860974.Cámara-Vázquez, MÁ.; Hernández-Romero, I.; Morgado-Reyes, E.; Guillem Sánchez, MS.; Climent, AM.; Barquero-Pérez, Ó. (2021). Detection of Atrial Fibrillation Driver Locations Using CNN and Body Surface Potentials. 1-4. https://doi.org/10.22489/CinC.2021.2561

Effects of high-intensity interval training on vascular function in patients with cardiovascular disease: a systematic review and meta-analysis

Background: Exercise training improves endothelial function in patients with cardiovascular disease (CVD). However, the influence of training variables remains unclear. The aim of this study was to evaluate the effect of highintensity interval training (HIIT), compared to moderate intensity training (MIT) and other exercise modalities (i.e., resistance and combined exercise), on endothelial function, assessed by arterial flow-mediated dilation (FMD) or endothelial progenitor cells (EPCs), in patients with CVD. Secondly, we investigated the influence of other training variables (i.e., HIIT protocol). Methods: The PICOS strategy was used to identify randomised and nonrandomised studies comparing the effect of HIIT and other exercise modalities (e.g., MIT) on endothelial function in patients with CVD. Electronic searches were carried out in Pubmed, Embase, and Web of Science up to November 2022. The TESTEX scale was used to evaluate the methodological quality of the included studies. Random-effects models of between-group mean difference (MD) were estimated. A positive MD indicated an effect in favour of HIIT. Heterogeneity analyses were performed by the chi-square test and I2 index. Subgroup analyses evaluated the influence of potential moderator variables. Results: Fourteen studies (13; 92.9% randomised) were included. Most of the studies trained 3 days a week for 12 weeks and performed long HIIT. No statistically significant differences were found between HIIT and MIT for improving brachial FMD in patients with coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF) (8 studies; MD+ = 0.91% [95% confidence interval (CI) = −0.06, 1.88]). However, subgroup analyses showed that long HIIT (i.e., > 1 min) is better than MIT for enhancing FMD (5 studies; MD+ = 1.46% [95% CI = 0.35, 2.57]), while no differences were found between short HIIT (i.e., ≤ 1 min) and MIT (3 studies; MD+ = −0.41% [95% CI = −1.64, 0.82]). Insufficient data prevented pooled analysis for EPCs, and individual studies failed to find statistically significant differences (p > .050) between HIIT and other exercise modalities in increasing EPCs. Discussion: Poor methodological quality could limit the precision of the current results and increase the inconsistency. Long HIIT is superior to MIT for improving FMD in patients with CAD or HFrEF. Future studies comparing HIIT to other exercise modalities, as well as the effect on EPCs and in HF with preserved ejection fraction are required

Effects and Optimal Dose of Exercise on Endothelial Function in Patients with Heart Failure: A Systematic Review and Meta‑Analysis

Background Exercise-based cardiac rehabilitation (CR) is considered an effective treatment for enhancing endothelial function in patients with heart failure (HF). However, recent studies have been published and the optimal “dose” of exercise required to increase the benefits of exercise-based CR programmes on endothelial function is still unknown. Objectives (a) To estimate the effect of exercise-based CR on endothelial function, assessed by flow-mediated dilation (FMD), in patients with HF; (b) to determine whether high-intensity interval training (HIIT) is better than moderate-intensity training (MIT) for improving FMD; and (c) to investigate the influence of exercise modality (i.e. resistance exercise vs. aerobic exercise and combined exercise vs. aerobic exercise) on the improvement of endothelial function. Methods Electronic searches were carried out in PubMed, Embase, and Scopus up to February 2022. Random-effects models of between-group mean differences were estimated. Heterogeneity analyses were performed by means of the chi-square test and I2 index. Subgroup analyses and meta-regressions were used to test the influence of potential moderator variables on the effect of exercise. Results We found a FMD increase of 3.09% (95% confidence interval [CI] = 2.01, 4.17) in favour of aerobic-based CR programmes compared with control groups in patients with HF and reduced ejection fraction (HFrEF). However, the results of included studies were inconsistent (p < .001; I2 = 95.2%). Higher FMD improvement was found in studies which were randomised, reported radial FMD, or performed higher number of training sessions a week. Moreover, HIIT enhanced FMD to a greater extent than MIT (2.35% [95% CI = 0.49, 4.22]) in patients with HFrEF. Insufficient data prevented pooled analyses for the effect of exercise in patients with HF and preserved ejection fraction and the influence of exercise modality on the improvement of endothelial function. Conclusion Aerobic-based CR is a non-pharmacological treatment for enhancing endothelial function in patients with HFrEF. However, higher training frequency and HIIT induce greater adaptation of endothelial function in these patients, which should betaken into consideration when designing exercise-based CR programmes. Trial registration The protocol was prospectively registered on the PROSPERO database (CRD42022304687)

Regularization Techniques for ECG Imaging during Atrial Fibrillation: A Computational Study

The inverse problem of electrocardiography is usually analyzed during stationary rhythms. However, the performance of the regularization methods under fibrillatory conditions has not been fully studied. In this work, we assessed different regularization techniques during atrial fibrillation (AF) for estimating four target parameters, namely, epicardial potentials, dominant frequency (DF), phase maps, and singularity point (SP) location. We use a realistic mathematical model of atria and torso anatomy with three different electrical activity patterns (i.e., sinus rhythm, simple AF, and complex AF). Body surface potentials (BSP) were simulated using Boundary Element Method and corrupted with white Gaussian noise of different powers. Noisy BSPs were used to obtain the epicardial potentials on the atrial surface, using 14 different regularization techniques. DF, phase maps, and SP location were computed from estimated epicardial potentials. Inverse solutions were evaluated using a set of performance metrics adapted to each clinical target. For the case of SP location, an assessment methodology based on the spatial mass function of the SP location, and four spatial error metrics was proposed. The role of the regularization parameter for Tikhonov-based methods, and the effect of noise level and imperfections in the knowledge of the transfer matrix were also addressed. Results showed that the Bayes maximum-a-posteriori method clearly outperforms the rest of the techniques but requires a priori information about the epicardial potentials. Among the purely non-invasive techniques. Tikhonov-based methods performed as well as more complex techniques in realistic fibrillatory conditions, with a slight gain between 0.02 and 0.2 in terms of the correlation coefficient. Also, the use of a constant regularization parameter may be advisable since the performance was similar to that obtained with a variable parameter (indeed there was no difference for the zero-order Tikhonov method in complex fibrillatory conditions). Regarding the different targets. DF and SP location estimation were more robust with respect to pattern complexity and noise, and most algorithms provided a reasonable estimation of these parameters, even when the epicardial potentials estimation was inaccurate. Finally, the proposed evaluation procedure and metrics represent a suitable framework for techniques benchmarking and provide useful insights for the clinical practice.This work has been partially supported by TEC2013-46067-R (Ministerio de Economia y Competitividad, Spanish Government).Figuera C; Suárez Gutiérrez V; Hernández-Romero, I.; Rodrigo Bort, M.; Liberos Mascarell, A.; Atienza, F.; Guillem Sánchez, MS.... (2016). Regularization Techniques for ECG Imaging during Atrial Fibrillation: A Computational Study. Frontiers in Physiology. 7(466):1-17. https://doi.org/10.3389/fphys.2016.00466S117746