13 results on '"Guillem MS"'
Search Results
2. Improving electrocardiographic imaging solutions: A comprehensive study on regularization parameter selection in L-curve optimization in the Atria.
- Author
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Molero R, Martínez-Pérez M, Herrero-Martín C, Reventós-Presmanes J, Roca-Luque I, Mont L, Climent AM, and Guillem MS
- Abstract
Background: In electrocardiographic imaging (ECGI), selecting an optimal regularization parameter (λ) is crucial for obtaining accurate inverse electrograms. The effects of signal and geometry uncertainties on the inverse problem regularization have not been thoroughly quantified, and there is no established methodology to identify when λ is sub-optimal due to these uncertainties. This study introduces a novel approach to λ selection using Tikhonov regularization and L-curve optimization, specifically addressing the impact of electrical noise in body surface potential map (BSPM) signals and geometrical inaccuracies in the cardiac mesh., Methods: Nineteen atrial simulations (5 of regular rhythms and 14 of atrial fibrillation) ensuring variability in substrate complexity and activation patterns were used for computing the ECGI with added white Gaussian noise from 40 dB to -3dB. Cardiac mesh displacements (1-3 cm) were applied to simulate the uncertainty of atrial positioning and study its impact on the L-curve shape. The regularization parameter, the maximum curvature, and the most horizontal angle of the L-curve (β) were quantified. In addition, BSPM signals from real patients were used to validate our findings., Results: The maximum curvature of the L-curve was found to be inversely related to signal-to-noise ratio and atrial positioning errors. In contrast, the β angle is directly related to electrical noise and remains unaffected by geometrical errors. Our proposed adjustment of λ, based on the β angle, provides a more reliable ECGI solution than traditional corner-based methods. Our findings have been validated with simulations and real patient data, demonstrating practical applicability., Conclusion: Adjusting λ based on the amount of noise in the data (or on the β angle) allows finding optimal ECGI solutions than a λ purely found at the corner of the L-curve. It was observed that the relevant information in ECGI activation maps is preserved even under the presence of uncertainties when the regularization parameter is correctly selected. The proposed criteria for regularization parameter selection have the potential to enhance the accuracy and reliability of ECGI solutions., Competing Interests: Declaration of competing interest M.S. Guillem. A.M. Climent. Are co-founders of Corify Care SL. R. Molero, J. Reventós-Presmanes, A.M. Climent. And M.S. Guillem get honorary from Corify Care SL. M.S. Guillem, L. Mont is shareholders of Corify Care SL. L. Mont reports honoraria as consultant, lecturer, and Advisory Board from Boston Scientific, Abbott Medical, Johnson & Johnson, and Medtronic. He is a shareholder of Galgo Medical SL. I. Roca-Luque has received honoraria as a lecturer and consultant from Abbott and Biosense Webster., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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3. Regional conduction velocities determined by noninvasive mapping are associated with arrhythmia-free survival after atrial fibrillation ablation.
- Author
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Invers-Rubio E, Hernández-Romero I, Reventos-Presmanes J, Ferro E, Guichard JB, Regany-Closa M, Pellicer-Sendra B, Borras R, Prat-Gonzalez S, Tolosana JM, Porta-Sanchez A, Arbelo E, Guasch E, Sitges M, Brugada J, Guillem MS, Roca-Luque I, Climent AM, Mont L, and Althoff TF
- Subjects
- Humans, Male, Female, Middle Aged, Prospective Studies, Electrocardiography, Heart Atria physiopathology, Heart Atria diagnostic imaging, Follow-Up Studies, Magnetic Resonance Imaging, Cine methods, Recurrence, Aged, Body Surface Potential Mapping methods, Electrophysiologic Techniques, Cardiac methods, Atrial Fibrillation physiopathology, Atrial Fibrillation surgery, Catheter Ablation methods, Heart Conduction System physiopathology, Pulmonary Veins surgery, Pulmonary Veins physiopathology, Pulmonary Veins diagnostic imaging
- Abstract
Background: Atrial arrhythmogenic substrate is a key determinant of atrial fibrillation (AF) recurrence after pulmonary vein isolation (PVI), and reduced conduction velocities have been linked to adverse outcome. However, a noninvasive method to assess such electrophysiologic substrate is not available to date., Objective: This study aimed to noninvasively assess regional conduction velocities and their association with arrhythmia-free survival after PVI., Methods: A consecutive 52 patients scheduled for AF ablation (PVI only) and 19 healthy controls were prospectively included and received electrocardiographic imaging (ECGi) to noninvasively determine regional atrial conduction velocities in sinus rhythm. A novel ECGi technology obviating the need of additional computed tomography or cardiac magnetic resonance imaging was applied and validated by invasive mapping., Results: Mean ECGi-determined atrial conduction velocities were significantly lower in AF patients than in healthy controls (1.45 ± 0.15 m/s vs 1.64 ± 0.15 m/s; P < .0001). Differences were particularly pronounced in a regional analysis considering only the segment with the lowest average conduction velocity in each patient (0.8 ± 0.22 m/s vs 1.08 ± 0.26 m/s; P < .0001). This average conduction velocity of the "slowest" segment was independently associated with arrhythmia recurrence and better discriminated between PVI responders and nonresponders than previously proposed predictors, including left atrial size and late gadolinium enhancement (magnetic resonance imaging). Patients without slow-conduction areas (mean conduction velocity <0.78 m/s) showed significantly higher 12-month arrhythmia-free survival than those with 1 or more slow-conduction areas (88.9% vs 48.0%; P = .002)., Conclusion: This is the first study to investigate regional atrial conduction velocities noninvasively. The absence of ECGi-determined slow-conduction areas well discriminates PVI responders from nonresponders. Such noninvasive assessment of electrical arrhythmogenic substrate may guide treatment strategies and be a step toward personalized AF therapy., Competing Interests: Disclosures Dr Till Althoff has received research grants for investigator-initiated trials from Biosense Webster and honoraria as consultant from Corify Care. Prof Lluís Mont has received honoraria as a lecturer and consultant and has received research grants from Abbott Medical, Biosense Webster, Boston Scientific, and Medtronic; he is a shareholder of Galgo Medical SL and Corify Care. Drs Andreu Climent and María S. Guillem are co-founders of Corify Care and receive honoraria from the company. Dr Ismael Hernández is co-founder of Corify Care. Jana Reventos is employed by Corify Care. Drs Ivo Roca-Luque, Jose M. Tolosana, and Andreu Porta-Sanchez received honoraria as consultants for Biosense Webster, Boston Scientific, and Medtronic. Dr Jean-Baptiste Guichard reports honoraria as a consultant from Microport CRM and as lecturer from Microport CRM and Abbott and an unrestricted grant support for a fellowship from Abbott Laboratories., (Copyright © 2024 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)
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- 2024
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4. Non-invasive estimation of atrial fibrillation driver position using long-short term memory neural networks and body surface potentials.
- Author
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Gutiérrez-Fernández-Calvillo M, Cámara-Vázquez MÁ, Hernández-Romero I, Guillem MS, Climent AM, Fambuena-Santos C, and Barquero-Pérez Ó
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- Humans, Quality of Life, Memory, Short-Term, Heart Atria surgery, Neural Networks, Computer, Atrial Fibrillation diagnosis, Catheter Ablation methods
- Abstract
Background and Objective: Atrial Fibrillation (AF) is a supraventricular tachyarrhythmia that can lead to thromboembolism, hearlt failure, ischemic stroke, and a decreased quality of life. Characterizing the locations where the mechanisms of AF are initialized and maintained is key to accomplishing an effective ablation of the targets, hence restoring sinus rhythm. Many methods have been investigated to locate such targets in a non-invasive way, such as Electrocardiographic Imaging, which enables an on-invasive and panoramic characterization of cardiac electrical activity using recording Body Surface Potentials (BSP) and a torso model of the patient. Nonetheless, this technique entails some major issues stemming from solving the inverse problem, which is known to be severely ill-posed. In this context, many machine learning and deep learning approaches aim to tackle the characterization and classification of AF targets to improve AF diagnosis and treatment., Methods: In this work, we propose a method to locate AF drivers as a supervised classification problem. We employed a hybrid form of the convolutional-recurrent network which enables feature extraction and sequential data modeling utilizing labeled realistic computerized AF models. Thus, we used 16 AF electrograms, 1 atrium, and 10 torso geometries to compute the forward problem. Previously, the AF models were labeled by assigning each sample of the signals a region from the atria from 0 (no driver) to 7, according to the spatial location of the AF driver. The resulting 160 BSP signals, which resemble a 64-lead vest recording, are preprocessed and then introduced into the network following a 4-fold cross-validation in batches of 50 samples., Results: The results show a mean accuracy of 74.75% among the 4 folds, with a better performance in detecting sinus rhythm, and drivers near the left superior pulmonary vein (R1), and right superior pulmonary vein (R3) whose mean sensitivity bounds around 84%-87%. Significantly good results are obtained in mean sensitivity (87%) and specificity (83%) in R1., Conclusions: Good results in R1 are highly convenient since AF drivers are commonly found in this area: the left atrial appendage, as suggested in some previous studies. These promising results indicate that using CNN-LSTM networks could lead to new strategies exploiting temporal correlations to address this challenge effectively., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2024
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5. Standardized 2D atrial mapping and its clinical applications.
- Author
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Wang T, Karel J, Invers-Rubio E, Hernández-Romero I, Peeters R, Bonizzi P, and Guillem MS
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- Humans, Heart Atria diagnostic imaging, Atrial Fibrillation diagnostic imaging, Atrial Fibrillation surgery, Atrial Appendage, Catheter Ablation methods
- Abstract
The visualization and comparison of electrophysiological information in the atrium among different patients could be facilitated by a standardized 2D atrial mapping. However, due to the complexity of the atrial anatomy, unfolding the 3D geometry into a 2D atrial mapping is challenging. In this study, we aim to develop a standardized approach to achieve a 2D atrial mapping that connects the left and right atria, while maintaining fixed positions and sizes of atrial segments across individuals. Atrial segmentation is a prerequisite for the process. Segmentation includes 19 different segments with 12 segments from the left atrium, 5 segments from the right atrium, and two segments for the atrial septum. To ensure consistent and physiologically meaningful segment connections, an automated procedure is applied to open up the atrial surfaces and project the 3D information into 2D. The corresponding 2D atrial mapping can then be utilized to visualize different electrophysiological information of a patient, such as activation time patterns or phase maps. This can in turn provide useful information for guiding catheter ablation. The proposed standardized 2D maps can also be used to compare more easily structural information like fibrosis distribution with rotor presence and location. We show several examples of visualization of different electrophysiological properties for both healthy subjects and patients affected by atrial fibrillation. These examples show that the proposed maps provide an easy way to visualize and interpret intra-subject information and perform inter-subject comparison, which may provide a reference framework for the analysis of the atrial fibrillation substrate before treatment, and during a catheter ablation procedure., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Maria S Guillem and Ismael Hernández-Romero are the shareholders and have received honoraria from Corify Care., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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6. Electrocardiographic imaging in the atria.
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Hernández-Romero I, Molero R, Fambuena-Santos C, Herrero-Martín C, Climent AM, and Guillem MS
- Subjects
- Humans, Body Surface Potential Mapping methods, Electrocardiography methods, Heart Atria diagnostic imaging, Diagnostic Imaging, Atrial Fibrillation
- Abstract
The inverse problem of electrocardiography or electrocardiographic imaging (ECGI) is a technique for reconstructing electrical information about cardiac surfaces from noninvasive or non-contact recordings. ECGI has been used to characterize atrial and ventricular arrhythmias. Although it is a technology with years of progress, its development to characterize atrial arrhythmias is challenging. Complications can arise when trying to describe the atrial mechanisms that lead to abnormal propagation patterns, premature or tachycardic beats, and reentrant arrhythmias. This review addresses the various ECGI methodologies, regularization methods, and post-processing techniques used in the atria, as well as the context in which they are used. The current advantages and limitations of ECGI in the fields of research and clinical diagnosis of atrial arrhythmias are outlined. In addition, areas where ECGI efforts should be concentrated to address the associated unsatisfied needs from the atrial perspective are discussed., (© 2022. The Author(s).)
- Published
- 2023
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7. In silico experiments explain the non-consistent benefit of conduction system pacing over cardiac resynchronization therapy. The need to personalize therapy.
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Guillem MS, Pujol-López M, Sanchez-Arciniegas J, and Mont L
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- Humans, Heart Conduction System, Cardiac Conduction System Disease, Cardiac Resynchronization Therapy
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- 2023
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8. Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location.
- Author
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Molero R, González-Ascaso A, Climent AM, and Guillem MS
- Subjects
- Humans, Uncertainty, Heart Atria diagnostic imaging, Diagnostic Imaging, Body Surface Potential Mapping methods, Electrocardiography methods, Atrial Fibrillation
- Abstract
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., Competing Interests: Declaration of Competing Interest R. Molero and A. González-Ascaso have no conflict of interests., (Copyright © 2022. Published by Elsevier Inc.)
- Published
- 2023
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9. AF driver detection in pulmonary vein area by electropcardiographic imaging: Relation with a favorable outcome of pulmonary vein isolation.
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Fambuena-Santos C, Hernández-Romero I, Molero R, Atienza F, Climent AM, and Guillem MS
- Abstract
Pulmonary vein isolation (PVI) is the most successful treatment for atrial fibrillation (AF) nowadays. However, not all AF patients benefit from PVI. In this study, we evaluate the use of ECGI to identify reentries and relate rotor density in the pulmonary vein (PV) area as an indicator of PVI outcome. Rotor maps were computed in a set of 29 AF patients using a new rotor detection algorithm. The relationship between the distribution of reentrant activity and the clinical outcome after PVI was studied. The number of rotors and proportion of PSs in different atrial regions were computed and compared retrospectively in two groups of patients: patients that remained in sinus rhythm 6 months after PVI and patients with arrhythmia recurrence. The total number of rotors obtained was higher in patients returning to arrhythmia after the ablation (4.31 ± 2.77 vs. 3.58 ± 2.67%, p = 0.018). However, a significantly higher concentration of PSs in the pulmonary veins was found in patients that remained in sinus rhythm (10.20 ± 12.40% vs. 5.19 ± 9.13%, p = 0.011) 6 months after PVI. The results obtained show a direct relationship between the expected AF mechanism and the electrophysiological parameters provided by ECGI, suggesting that this technology offers relevant information to predict the clinical outcome after PVI in AF patients., Competing Interests: AC, MG, IH-R, and FA hold equity in Corify Care. AC has received honoraria from Corify Care. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Fambuena-Santos, Hernández-Romero, Molero, Atienza, Climent and Guillem.)
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- 2023
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10. Atrial fibrosis identification with unipolar electrogram eigenvalue distribution analysis in multi-electrode arrays.
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Riccio J, Alcaine A, Rocher S, Martinez-Mateu L, Saiz J, Invers-Rubio E, Guillem MS, Martínez JP, and Laguna P
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- Electrodes, Electrophysiologic Techniques, Cardiac, Fibrosis, Heart Atria, Humans, Atrial Fibrillation diagnosis, Catheter Ablation methods
- Abstract
Atrial fibrosis plays a key role in the initiation and progression of atrial fibrillation (AF). Atrial fibrosis is typically identified by a peak-to-peak amplitude of bipolar electrograms (b-EGMs) lower than 0.5 mV, which may be considered as ablation targets. Nevertheless, this approach disregards signal spatiotemporal information and b-EGM sensitivity to catheter orientation. To overcome these limitations, we propose the dominant-to-remaining eigenvalue dominance ratio (EIGDR) of unipolar electrograms (u-EGMs) within neighbor electrode cliques as a waveform dispersion measure, hypothesizing that it is correlated with the presence of fibrosis. A simulated 2D tissue with a fibrosis patch was used for validation. We computed EIGDR maps from both original and time-aligned u-EGMs, denoted as [Formula: see text] and [Formula: see text], respectively, also mapping the gain in eigenvalue concentration obtained by the alignment, [Formula: see text]. The performance of each map in detecting fibrosis was evaluated in scenarios including noise and variable electrode-tissue distance. Best results were achieved by [Formula: see text], reaching 94% detection accuracy, versus the 86% of b-EGMs voltage maps. The proposed strategy was also tested in real u-EGMs from fibrotic and non-fibrotic areas over 3D electroanatomical maps, supporting the ability of the EIGDRs as fibrosis markers, encouraging further studies to confirm their translation to clinical settings. Upper panels: map of [Formula: see text] from 3×3 cliques for Ψ= 0
∘ and bipolar voltage map Vb-m , performed assuming a variable electrode-to-tissue distance and noisy u-EGMs (noise level σv = 46.4 μV ). Lower panels: detected fibrotic areas (brown), using the thresholds that maximize detection accuracy of each map., (© 2022. The Author(s).)- Published
- 2022
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11. Identification of atrial fibrillation drivers by means of concentric ring electrodes.
- Author
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Prats-Boluda G, Guillem MS, Rodrigo M, Ye-Lin Y, and Garcia-Casado J
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- Body Surface Potential Mapping, Electrodes, Heart Atria, Humans, Atrial Fibrillation
- Abstract
Background and Objective: The prevalence of atrial fibrillation (AF) has tripled in the last 50 years due to population aging. High-frequency (DFdriver) activated atrial regions lead the activation of the rest of the atria, disrupting the propagation wavefront. Fourier based spectral analysis of body surface potential maps have been proposed for DFdriver identification, although these approaches present serious drawbacks due to their limited spectral resolution for short AF epochs and the blurring effect of the volume conductor. Laplacian signals (BC-ECG) from bipolar concentric ring electrodes (CRE) have been shown to outperform the spatial resolution achieved with conventional unipolar recordings. Our aimed was to determine the best DFdriver estimator in endocardial electrograms and to assess the BC-ECG capacity of CRE to quantify AF activity non-invasively., Methods: 31 AF episodes were simulated using realistic tridimensional models of the atria electrical activity and torso. Periodogram and autoregressive (AR) spectral estimators were computed and the percentile (P90
th , P95th and P98th ) to impose on the dominant frequencies (DFs) across whole atria to define the best DFdriver estimator evaluated. The identification of DFdriver on DFs from BC-ECG and unipolar surface signals with conventional disc electrodes was compared., Results: The best DFdriver estimator was P95th and AR order 100. BC-ECG signals allowed better detection of AF activity than unipolar signals, with a significantly greater percentage of electrode locations in which DFdriver was identified (p-value 0.0095)., Conclusions: The use of BC-ECG signals for body surface Laplacian potential mapping with CRE could be helpful for better AF diagnosis, prognosis and ablation procedures than those with conventional disk electrodes., (Copyright © 2022 Elsevier Ltd. All rights reserved.)- Published
- 2022
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12. Effects of torso mesh density and electrode distribution on the accuracy of electrocardiographic imaging during atrial fibrillation.
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Molero R, González-Ascaso A, Hernández-Romero I, Lundback-Mompó D, Climent AM, and Guillem MS
- Abstract
Introduction: Electrocardiographic Imaging (ECGI) allows computing the electrical activity in the heart non-invasively using geometrical information of the patient and multiple body surface signals. In the present study we investigate the influence of the number of nodes of geometrical meshes and recording ECG electrodes distribution to compute ECGI during atrial fibrillation (AF). Methods: Torso meshes from 100 to 2000 nodes heterogeneously and homogeneously distributed were compared. Signals from nine AF realistic mathematical simulations were used for computing the ECGI. Results for each torso mesh were compared with the ECGI computed with a 4,000 nodes reference torso. In addition, real AF recordings from 25 AF patients were used to compute ECGI in torso meshes from 100 to 1,000 nodes. Results were compared with a reference torso of 2000 nodes. Torsos were remeshed either by reducing the number of nodes while maximizing the overall shape preservation and then assigning the location of the electrodes as the closest node in the new mesh or by forcing the remesher to place a node at each electrode location. Correlation coefficients, relative difference measurements and relative difference of dominant frequencies were computed to evaluate the impact on signal morphology of each torso mesh. Results: For remeshed torsos where electrodes match with a geometrical node in the mesh, all mesh densities presented similar results. On the other hand, in torsos with electrodes assigned to closest nodes in remeshed geometries performance metrics were dependent on mesh densities, with correlation coefficients ranging from 0.53 ± 0.06 to 0.92 ± 0.04 in simulations or from 0.42 ± 0.38 to 0.89 ± 0.2 in patients. Dominant frequency relative errors showed the same trend with values from 1.14 ± 0.26 to 0.55 ± 0.21 Hz in simulations and from 0.91 ± 0.56 to 0.45 ± 0.41 Hz in patients. Conclusion: The effect of mesh density in ECGI is minimal when the location of the electrode is preserved as a node in the mesh. Torso meshes constructed without imposing electrodes to constitute nodes in the torso geometry should contain at least 400 nodes homogeneously distributed so that a distance between nodes is below 4 cm., Competing Interests: MG, IH-R, and AC are co-founders and shareholders of Corify Care SL. Author DL-M was employed by the company Corify Care SL. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Molero, González-Ascaso, Hernández-Romero, Lundback-Mompó, Climent and Guillem.)
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- 2022
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13. Higher reproducibility of phase derived metrics from electrocardiographic imaging during atrial fibrillation in patients remaining in sinus rhythm after pulmonary vein isolation.
- Author
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Molero R, Soler Torro JM, Martínez Alzamora N, M Climent A, and Guillem MS
- Subjects
- Benchmarking, Humans, Male, Recurrence, Reproducibility of Results, Treatment Outcome, Atrial Fibrillation diagnostic imaging, Atrial Fibrillation surgery, Catheter Ablation, Pulmonary Veins surgery
- Abstract
Background: Electrocardiographic imaging (ECGI) allows evaluating the complexity of the reentrant activity of atrial fibrillation (AF) patients. In this study, we evaluated the ability of ECGI metrics to predict the success of pulmonary vein isolation (PVI) to treat AF., Methods: ECGI of 24 AF patients (6 males, 13 paroxysmal, 61.8 ± 14 years) was recorded prior to PVI. Patients were distributed into two groups based on their PVI outcome 6 months after ablation (sinus vs. arrhythmia recurrence). Metrics derived from phase analysis of ECGI signals were computed for two different temporal segments before ablation. Correlation analysis and variability over time were studied between the two recorded segments and were compared between patient groups., Results: Temporal variability of both rotor duration and spatial entropy of the rotor histogram presented statistical differences between groups with different PVI outcome (p < 0.05). The reproducibility of reentrant metrics was higher (R
2 > 0.8) in patients with good outcome rather than arrhythmia recurrence patients (R2 < 0.62). Prediction of PVI success based on ECGI temporal variability metrics allows for an increased specificity over the classification into paroxysmal or persistent (0.85 vs. 0.64)., Conclusions: Patients with favorable PVI outcome present ECGI metrics more reproducible over time than patients with AF recurrence. These results suggest that ECGI derived metrics may allow selecting which patients would benefit from ablation therapies., (Copyright © 2021 Elsevier Ltd. All rights reserved.)- Published
- 2021
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