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Gutiérrez-Fernández-Calvillo M, Cámara-Vázquez MÁ, Hernández-Romero I, Guillem MS, Climent AM, Fambuena-Santos C, Barquero-Pérez Ó. Non-invasive estimation of atrial fibrillation driver position using long-short term memory neural networks and body surface potentials. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 246:108052. [PMID: 38350188 DOI: 10.1016/j.cmpb.2024.108052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/12/2023] [Accepted: 01/26/2024] [Indexed: 02/15/2024]
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.
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Affiliation(s)
| | | | | | - María S Guillem
- Universitat Politècnica de València, Camí de Vera s/n, València, 46022, Spain
| | - Andreu M Climent
- Universitat Politècnica de València, Camí de Vera s/n, València, 46022, Spain
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van der Waal J, Meijborg V, Coronel R, Dubois R, Oostendorp T. Basis and applicability of noninvasive inverse electrocardiography: a comparison between cardiac source models. Front Physiol 2023; 14:1295103. [PMID: 38152249 PMCID: PMC10752226 DOI: 10.3389/fphys.2023.1295103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 11/30/2023] [Indexed: 12/29/2023] Open
Abstract
The body surface electrocardiogram (ECG) is a direct result of electrical activity generated by the myocardium. Using the body surface ECGs to reconstruct cardiac electrical activity is called the inverse problem of electrocardiography. The method to solve the inverse problem depends on the chosen cardiac source model to describe cardiac electrical activity. In this paper, we describe the theoretical basis of two inverse methods based on the most commonly used cardiac source models: the epicardial potential model and the equivalent dipole layer model. We discuss similarities and differences in applicability, strengths and weaknesses and sketch a road towards improved inverse solutions by targeted use, sequential application or a combination of the two methods.
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Affiliation(s)
- Jeanne van der Waal
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Veronique Meijborg
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Ruben Coronel
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Rémi Dubois
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac, France
| | - Thom Oostendorp
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
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Brisinda D, Fenici P, Fenici R. Clinical magnetocardiography: the unshielded bet-past, present, and future. Front Cardiovasc Med 2023; 10:1232882. [PMID: 37636301 PMCID: PMC10448194 DOI: 10.3389/fcvm.2023.1232882] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 06/23/2023] [Indexed: 08/29/2023] Open
Abstract
Magnetocardiography (MCG), which is nowadays 60 years old, has not yet been fully accepted as a clinical tool. Nevertheless, a large body of research and several clinical trials have demonstrated its reliability in providing additional diagnostic electrophysiological information if compared with conventional non-invasive electrocardiographic methods. Since the beginning, one major objective difficulty has been the need to clean the weak cardiac magnetic signals from the much higher environmental noise, especially that of urban and hospital environments. The obvious solution to record the magnetocardiogram in highly performant magnetically shielded rooms has provided the ideal setup for decades of research demonstrating the diagnostic potential of this technology. However, only a few clinical institutions have had the resources to install and run routinely such highly expensive and technically demanding systems. Therefore, increasing attempts have been made to develop cheaper alternatives to improve the magnetic signal-to-noise ratio allowing MCG in unshielded hospital environments. In this article, the most relevant milestones in the MCG's journey are reviewed, addressing the possible reasons beyond the currently long-lasting difficulty to reach a clinical breakthrough and leveraging the authors' personal experience since the early 1980s attempting to finally bring MCG to the patient's bedside for many years thus far. Their nearly four decades of foundational experimental and clinical research between shielded and unshielded solutions are summarized and referenced, following the original vision that MCG had to be intended as an unrivaled method for contactless assessment of the cardiac electrophysiology and as an advanced method for non-invasive electroanatomical imaging, through multimodal integration with other non-fluoroscopic imaging techniques. Whereas all the above accounts for the past, with the available innovative sensors and more affordable active shielding technologies, the present demonstrates that several novel systems have been developed and tested in multicenter clinical trials adopting both shielded and unshielded MCG built-in hospital environments. The future of MCG will mostly be dependent on the results from the ongoing progress in novel sensor technology, which is relatively soon foreseen to provide multiple alternatives for the construction of more compact, affordable, portable, and even wearable devices for unshielded MCG inside hospital environments and perhaps also for ambulatory patients.
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Affiliation(s)
- D. Brisinda
- Dipartimento Scienze dell'invecchiamento, ortopediche e reumatologiche, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy
- School of Medicine and Surgery, Catholic University of the Sacred Heart, Rome, Italy
- Biomagnetism and Clinical Physiology International Center (BACPIC), Rome, Italy
| | - P. Fenici
- School of Medicine and Surgery, Catholic University of the Sacred Heart, Rome, Italy
- Biomagnetism and Clinical Physiology International Center (BACPIC), Rome, Italy
| | - R. Fenici
- Biomagnetism and Clinical Physiology International Center (BACPIC), Rome, Italy
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Dogrusoz YS, Rasoolzadeh N, Ondrusova B, Hlivak P, Zelinka J, Tysler M, Svehlikova J. Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data. Front Physiol 2023; 14:1197778. [PMID: 37362428 PMCID: PMC10288213 DOI: 10.3389/fphys.2023.1197778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/22/2023] [Indexed: 06/28/2023] Open
Abstract
Introduction: Localization of premature ventricular contraction (PVC) origin to guide the radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non-invasive electrocardiographic imaging. However, the results reported in the literature vary significantly depending on the source model and the level of complexity in the forward model. This study aims to compare the paced and spontaneous PVC localization performances of dipole-based and potential-based source models and corresponding inverse methods using the same clinical data and to evaluate the effects of torso inhomogeneities on these performances. Methods: The publicly available EP solution data from the EDGAR data repository (BSPs from a maximum of 240 electrodes) with known pacing locations and the Bratislava data (BSPs in 128 leads) with spontaneous PVCs from patients who underwent successful RFA procedures were used. Homogeneous and inhomogeneous torso models and corresponding forward problem solutions were used to relate sources on the closed epicardial and epicardial-endocardial surfaces. The localization error (LE) between the true and estimated pacing site/PVC origin was evaluated. Results: For paced data, the median LE values were 25.2 and 13.9 mm for the dipole-based and potential-based models, respectively. These median LE values were higher for the spontaneous PVC data: 30.2-33.0 mm for the dipole-based model and 28.9-39.2 mm for the potential-based model. The assumption of inhomogeneities in the torso model did not change the dipole-based solutions much, but using an inhomogeneous model improved the potential-based solutions on the epicardial-endocardial ventricular surface. Conclusion: For the specific task of localization of pacing site/PVC origin, the dipole-based source model is more stable and robust than the potential-based source model. The torso inhomogeneities affect the performances of PVC origin localization in each source model differently. Hence, care must be taken in generating patient-specific geometric and forward models depending on the source model representation used in electrocardiographic imaging (ECGI).
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Affiliation(s)
- Yesim Serinagaoglu Dogrusoz
- Department of Electrical-Electronics Engineering, Middle East Technical University, Ankara, Türkiye
- Department of Scientific Computing, Middle East Technical University, Institute of Applied Mathematics, Ankara, Türkiye
| | - Nika Rasoolzadeh
- Department of Electrical-Electronics Engineering, Middle East Technical University, Ankara, Türkiye
- Department of Scientific Computing, Middle East Technical University, Institute of Applied Mathematics, Ankara, Türkiye
| | - Beata Ondrusova
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
- Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Bratislava, Slovakia
| | - Peter Hlivak
- National Institute for Cardiovascular Diseases, Bratislava, Slovakia
| | - Jan Zelinka
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Milan Tysler
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Jana Svehlikova
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
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Hernández-Romero I, Molero R, Fambuena-Santos C, Herrero-Martín C, Climent AM, Guillem MS. Electrocardiographic imaging in the atria. Med Biol Eng Comput 2023; 61:879-896. [PMID: 36370321 PMCID: PMC9988819 DOI: 10.1007/s11517-022-02709-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022]
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.
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Affiliation(s)
| | - Rubén Molero
- ITACA, Universitat Politècnica de València, Valencia, Spain
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Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location. J Electrocardiol 2023; 77:58-61. [PMID: 36634462 DOI: 10.1016/j.jelectrocard.2022.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/13/2022] [Accepted: 12/23/2022] [Indexed: 01/04/2023]
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.
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Stoks J, Bear LR, Vijgen J, Dendale P, Peeters R, Volders PGA, Cluitmans MJM. Understanding repolarization in the intracardiac unipolar electrogram: A long-lasting controversy revisited. Front Physiol 2023; 14:1158003. [PMID: 37089414 PMCID: PMC10119409 DOI: 10.3389/fphys.2023.1158003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/24/2023] [Indexed: 04/25/2023] Open
Abstract
Background: The optimal way to determine repolarization time (RT) from the intracardiac unipolar electrogram (UEG) has been a topic of debate for decades. RT is typically determined by either the Wyatt method or the "alternative method," which both consider UEG T-wave slope, but differently. Objective: To determine the optimal method to measure RT on the UEG. Methods: Seven pig hearts surrounded by an epicardial sock with 100 electrodes were Langendorff-perfused with selective cannulation of the left anterior descending (LAD) coronary artery and submersed in a torso-shaped tank containing 256 electrodes on the torso surface. Repolarization was prolonged in the non-LAD-regions by infusing dofetilide and shortened in the LAD-region using pinacidil. RT was determined by the Wyatt (tWyatt) and alternative (tAlt) methods, in both invasive (recorded with epicardial electrodes) and in non-invasive UEGs (reconstructed with electrocardiographic imaging). tWyatt and tAlt were compared to local effective refractory period (ERP). Results: With contact mapping, mean absolute error (MAE) of tWyatt and tAlt vs. ERP were 21 ms and 71 ms, respectively. Positive T-waves typically had an earlier ERP than negative T-waves, in line with theory. tWyatt -but not tAlt-shortened by local infusion of pinacidil. Similar results were found for the non-invasive UEGs (MAE of tWyatt and tAlt vs. ERP were 30 ms and 92 ms, respectively). Conclusion: The Wyatt method is the most accurate to determine RT from (non) invasive UEGs, based on novel and historical analyses. Using it to determine RT could unify and facilitate repolarization assessment and amplify its role in cardiac electrophysiology.
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Affiliation(s)
- Job Stoks
- Department of Cardiology, CARIM, Maastricht University Medical Center+, Maastricht, Netherlands
- Department of Advanced Computing Sciences, Maastricht University, Maastricht, Netherlands
- Biomedical Research Institute, Hasselt University, Diepenbeek, Belgium
| | - Laura R. Bear
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Johan Vijgen
- Biomedical Research Institute, Hasselt University, Diepenbeek, Belgium
| | - Paul Dendale
- Biomedical Research Institute, Hasselt University, Diepenbeek, Belgium
| | - Ralf Peeters
- Department of Advanced Computing Sciences, Maastricht University, Maastricht, Netherlands
| | - Paul G. A. Volders
- Department of Cardiology, CARIM, Maastricht University Medical Center+, Maastricht, Netherlands
| | - Matthijs J. M. Cluitmans
- Department of Cardiology, CARIM, Maastricht University Medical Center+, Maastricht, Netherlands
- *Correspondence: Matthijs J. M. Cluitmans,
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Melgarejo-Meseguer FM, Everss-Villalba E, Gutierrez-Fernandez-Calvillo M, Munoz-Romero S, Gimeno-Blanes FJ, Garcia-Alberola A, Rojo-Alvarez JL. Generalization and Regularization for Inverse Cardiac Estimators. IEEE Trans Biomed Eng 2022; 69:3029-3038. [PMID: 35294340 DOI: 10.1109/tbme.2022.3159733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Electrocardiographic Imaging (ECGI) aims to estimate the intracardiac potentials noninvasively, hence allowing the clinicians to better visualize and understand many arrhythmia mechanisms. Most of the estimators of epicardial potentials use a signal model based on an estimated spatial transfer matrix together with Tikhonov regularization techniques, which works well specially in simulations, but it can give limited accuracy in some real data. Based on the quasielectrostatic potential superposition principle, we propose a simple signal model that supports the implementation of principled out-of-sample algorithms for several of the most widely used regularization criteria in ECGI problems, hence improving the generalization capabilities of several of the current estimation methods. Experiments on simple cases (cylindrical and Gaussian shapes scrutinizing fast and slow changes, respectively) and on real data (examples of torso tank measurements available from Utah University, and an animal torso and epicardium measurements available from Maastricht University, both in the EDGAR public repository) show that the superposition-based out-of-sample tuning of regularization parameters promotes stabilized estimation errors of the unknown source potentials, while slightly increasing the re-estimation error on the measured data, as natural in non-overfitted solutions. The superposition signal model can be used for designing adequate out-of-sample tuning of Tikhonov regularization techniques, and it can be taken into account when using other regularization techniques in current commercial systems and research toolboxes on ECGI.
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Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol 2021; 71:1-9. [PMID: 34979408 DOI: 10.1016/j.jelectrocard.2021.12.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/15/2021] [Accepted: 12/21/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a unipolar EGM by the moment of maximum downslope of the QRS complex or maximum upslope of the T wave, respectively. However, both invasive and noninvasive recordings of intracardiac EGMs may suffer from noise and fractionation, making reliable detection of these deflections nontrivial. METHODS Here, we introduce a novel method that benefits from the spatial coupling of these processes, and incorporate not only the temporal EGM deflection, but also the spatial gradients. We validated this approach in computer simulations, in animal data with ECGI and invasive electrode recordings, and illustrated its use in a clinical case. RESULTS In the simulated data, the spatiotemporal approach was able to incorporate spatial information to better select the correct deflection in artificially fractionated EGMs and outperformed the traditional temporal-only method. In experimental data, the accuracy of time estimation from ECGI compared to invasive recordings significantly increased from R = 0.73 (activation) and R = 0.58 (recovery) with the temporal-only method to R = 0.79 (activation) and R = 0.72 (recovery) with the novel approach. Localization of the pacing origin of paced beats improved significantly from 36 mm mean error with the temporal-only approach to 23 mm with the spatiotemporal approach. CONCLUSION The spatiotemporal method to compute activation and recovery times from EGMs outperformed the traditional temporal-only approach in which spatial information was not taken into account.
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Affiliation(s)
- Matthijs Cluitmans
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands.
| | - Jaume Coll-Font
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | | | | | - Uyên Châu Nguyên
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| | - Rachel Ter Bekke
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| | - Paul G A Volders
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| | - Dana Brooks
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
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Schuler S, Schaufelberger M, Bear LR, Bergquist JA, Cluitmans MJM, Coll-Font J, Onak ON, Zenger B, Loewe A, MacLeod RS, Brooks DH, Dossel O. Reducing Line-of-block Artifacts in Cardiac Activation Maps Estimated Using ECG Imaging: A Comparison of Source Models and Estimation Methods. IEEE Trans Biomed Eng 2021; 69:2041-2052. [PMID: 34905487 DOI: 10.1109/tbme.2021.3135154] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE To investigate cardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoBs. METHODS Body surface potentials were computed for 137 simulated ventricular excitations. Subsequently, the inverse problem was solved to obtain extracellular potentials (EP) and transmembrane voltages (TMV). From these, activation times (AT) were estimated using four methods and compared to the ground truth. This process was evaluated with two cardiac mesh resolutions. Factors contributing to LoB artifacts were identified by analyzing the impact of spatial and temporal smoothing on the morphology of source signals. RESULTS AT estimation using a spatiotemporal derivative performed better than using a temporal derivative. Compared to deflection-based AT estimation, correlation-based methods were less prone to LoB artifacts but performed worse in identifying real LoBs. Temporal smoothing could eliminate artifacts for TMVs but not for EPs, which could be linked to their temporal morphology. TMVs led to more accurate ATs on the septum than EPs. Mesh resolution had a negligible effect on inverse reconstructions, but small distances were important for cross-correlation-based estimation of AT delays. CONCLUSION LoB artifacts are mainly caused by the inherent spatial smoothing effect of the inverse reconstruction. Among the configurations evaluated, only deflection-based AT estimation in combination with TMVs and strong temporal smoothing can prevent LoB artifacts, while preserving real LoBs. SIGNIFICANCE Regions of slow conduction are of considerable clinical interest and LoB artifacts observed in non-invasive ATs can lead to misinterpretations. We addressed this problem by identifying factors causing such artifacts and methods to reduce them.
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Han B, Trew ML, Zgierski-Johnston CM. Cardiac Conduction Velocity, Remodeling and Arrhythmogenesis. Cells 2021; 10:cells10112923. [PMID: 34831145 PMCID: PMC8616078 DOI: 10.3390/cells10112923] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 10/14/2021] [Accepted: 10/22/2021] [Indexed: 02/06/2023] Open
Abstract
Cardiac electrophysiological disorders, in particular arrhythmias, are a key cause of morbidity and mortality throughout the world. There are two basic requirements for arrhythmogenesis: an underlying substrate and a trigger. Altered conduction velocity (CV) provides a key substrate for arrhythmogenesis, with slowed CV increasing the probability of re-entrant arrhythmias by reducing the length scale over which re-entry can occur. In this review, we examine methods to measure cardiac CV in vivo and ex vivo, discuss underlying determinants of CV, and address how pathological variations alter CV, potentially increasing arrhythmogenic risk. Finally, we will highlight future directions both for methodologies to measure CV and for possible treatments to restore normal CV.
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Affiliation(s)
- Bo Han
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg-Bad Krozingen, 79110 Freiburg im Breisgau, Germany;
- Faculty of Medicine, University of Freiburg, 79110 Freiburg im Breisgau, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, 79104 Freiburg im Breisgau, Germany
- Department of Cardiovascular Surgery, The Fourth People’s Hospital of Jinan, 250031 Jinan, China
| | - Mark L. Trew
- Auckland Bioengineering Institute, University of Auckland, Auckland 1010, New Zealand;
| | - Callum M. Zgierski-Johnston
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg-Bad Krozingen, 79110 Freiburg im Breisgau, Germany;
- Faculty of Medicine, University of Freiburg, 79110 Freiburg im Breisgau, Germany
- Correspondence:
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Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS. Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation. FUNCTIONAL IMAGING AND MODELING OF THE HEART : ... INTERNATIONAL WORKSHOP, FIMH ..., PROCEEDINGS. FIMH 2021; 12738:493-502. [PMID: 34447971 PMCID: PMC8385662 DOI: 10.1007/978-3-030-78710-3_47] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Electrocardiographic imaging (ECGI) is an effective tool for noninvasive diagnosis of a range of cardiac dysfunctions. ECGI leverages a model of how cardiac bioelectric sources appear on the torso surface (the forward problem) and uses recorded body surface potential signals to reconstruct the bioelectric source (the inverse problem). Solutions to the inverse problem are sensitive to noise and variations in the body surface potential (BSP) recordings such as those caused by changes or errors in cardiac position. Techniques such as signal averaging seek to improve ECGI solutions by incorporating BSP signals from multiple heartbeats into an averaged BSP with a higher SNR to use when estimating the cardiac bioelectric source. However, signal averaging is limited when it comes to addressing sources of BSP variability such as beat to beat differences in the forward solution. We present a novel joint inverse formulation to solve for the cardiac source given multiple BSP recordings and known changes in the forward solution, here changes in the heart position. We report improved ECGI accuracy over signal averaging and averaged individual inverse solutions using this joint inverse formulation across multiple activation sequence types and regularization techniques with measured canine data and simulated heart motion. Our joint inverse formulation builds upon established techniques and consequently can easily be applied with many existing regularization techniques, source models, and forward problem formulations.
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Affiliation(s)
- Jake A Bergquist
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Jaume Coll-Font
- Cardiovascular Bioengineering & Imaging Lab, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, USA
| | - Brian Zenger
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Lindsay C Rupp
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Wilson W Good
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Dana H Brooks
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| | - Rob S MacLeod
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
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Bear LR, Cluitmans M, Abell E, Rogier J, Labrousse L, Cheng LK, LeGrice I, Lever N, Sands GB, Smaill B, Haïssaguerre M, Bernus O, Coronel R, Dubois R. Electrocardiographic Imaging of Repolarization Abnormalities. J Am Heart Assoc 2021; 10:e020153. [PMID: 33880931 PMCID: PMC8200734 DOI: 10.1161/jaha.120.020153] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Background Dispersion and gradients in repolarization have been associated with life‐threatening arrhythmias, but are difficult to quantify precisely from surface electrocardiography. The objective of this study was to evaluate electrocardiographic imaging (ECGI) to noninvasively detect repolarization‐based abnormalities. Methods and Results Ex vivo data were obtained from Langendorff‐perfused pig hearts (n=8) and a human donor heart. Unipolar electrograms were recorded simultaneously during sinus rhythm from an epicardial sock and the torso‐shaped tank within which the heart was suspended. Regional repolarization heterogeneities were introduced through perfusion of dofetilide and pinacidil into separate perfusion beds. In vivo data included torso and epicardial potentials recorded simultaneously in anesthetized, closed‐chest pigs (n=5), during sinus rhythm, and ventricular pacing. For both data sets, ECGI accurately reconstructed T‐wave electrogram morphologies when compared with those recorded by the sock (ex vivo: correlation coefficient, 0.85 [0.52–0.96], in vivo: correlation coefficient, 0.86 [0.52–0.96]) and repolarization time maps (ex‐vivo: correlation coefficient, 0.73 [0.63–0.83], in vivo: correlation coefficient, 0.76 [0.67–0.82]). ECGI‐reconstructed repolarization time distributions were strongly correlated to those measured by the sock (both data sets, R2 ≥0.92). Although the position of the gradient was slightly shifted by 8.3 (0–13.9) mm, the mean, max, and SD between ECGI and recorded gradient values were highly correlated (R2=0.87, 0.75, and 0.86 respectively). There was no significant difference in ECGI accuracy between ex vivo and in vivo data. Conclusions ECGI reliably and accurately maps potentially critical repolarization abnormalities. This noninvasive approach allows imaging and quantifying individual parameters of abnormal repolarization‐based substrates in patients with arrhythmogenesis, to improve diagnosis and risk stratification.
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Affiliation(s)
- Laura R Bear
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
| | - Matthijs Cluitmans
- CARIM School for Cardiovascular Diseases Maastricht UMC Maastricht Netherlands
| | - Emma Abell
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
| | | | - Louis Labrousse
- IHU-LIRYCFondation Bordeaux Université Pessac France.,Department of Cardiac Surgery CHU Pessac France
| | - Leo K Cheng
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Ian LeGrice
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Nigel Lever
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Gregory B Sands
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Bruce Smaill
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Michel Haïssaguerre
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France.,Department of Cardiac Electrophysiology and Stimulation Bordeaux University Hospital (CHU) Pessac France
| | - Olivier Bernus
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
| | - Ruben Coronel
- IHU-LIRYCFondation Bordeaux Université Pessac France.,Department of Experimental Cardiology Academic Medical Center Amsterdam the Netherlands
| | - Rémi Dubois
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
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14
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Meo M, Bonizzi P, Bear LR, Cluitmans M, Abell E, Haïssaguerre M, Bernus O, Dubois R. Body Surface Mapping of Ventricular Repolarization Heterogeneity: An Ex-vivo Multiparameter Study. Front Physiol 2020; 11:933. [PMID: 32903614 PMCID: PMC7438571 DOI: 10.3389/fphys.2020.00933] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 07/10/2020] [Indexed: 12/15/2022] Open
Abstract
Background Increased heterogeneity of ventricular repolarization is associated with life-threatening arrhythmia and sudden cardiac death (SCD). T-wave analysis through body surface potential mapping (BSPM) is a promising tool for risk stratification, but the clinical effectiveness of current electrocardiographic indices is still unclear, with limited experimental validation. This study aims to investigate performance of non-invasive state-of-the-art and novel T-wave markers for repolarization dispersion in an ex vivo model. Methods Langendorff-perfused pig hearts (N = 7) were suspended in a human-shaped 256-electrode torso tank. Tank potentials were recorded during sinus rhythm before and after introducing repolarization inhomogeneities through local perfusion with dofetilide and/or pinacidil. Drug-induced repolarization gradients were investigated from BSPMs at different experiment phases. Dispersion of electrical recovery was quantified by duration parameters, i.e., the time interval between the peak and the offset of T-wave (TPEAK-TEND) and QT interval, and variability over time and electrodes was also assessed. The degree of T-wave symmetry to the peak was quantified by the ratio between the terminal and initial portions of T-wave area (Asy). Morphological variability between left and right BSPM electrodes was measured by dynamic time warping (DTW). Finally, T-wave organization was assessed by the complexity of repolarization index (CR), i.e., the amount of energy non-preserved by the dominant eigenvector computed by principal component analysis (PCA), and the error between each multilead T-wave and its 3D PCA approximation (NMSE). Body surface indices were compared with global measures of epicardial dispersion of repolarization, and with local gradients between adjacent ventricular sites. Results After drug intervention, both regional and global repolarization heterogeneity were significantly enhanced. On the body surface, TPEAK-TEND was significantly prolonged and less stable in time in all experiments, while QT interval showed higher variability across the interventions in terms of duration and spatial dispersion. The rising slope of the repolarization profile was steeper, and T-waves were more asymmetric than at baseline. Interventricular shape dissimilarity was enhanced by repolarization gradients according to DTW. Organized T-wave patterns were associated with abnormal repolarization, and they were properly described by the first principal components. Conclusion Repolarization heterogeneity significantly affects T-wave properties, and can be non-invasively captured by BSPM-based metrics.
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Affiliation(s)
- Marianna Meo
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France.,University of Bordeaux, CRCTB, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
| | - Pietro Bonizzi
- Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands
| | - Laura R Bear
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France.,University of Bordeaux, CRCTB, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
| | - Matthijs Cluitmans
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, Netherlands
| | - Emma Abell
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France.,University of Bordeaux, CRCTB, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
| | - Michel Haïssaguerre
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France.,University of Bordeaux, CRCTB, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France.,Bordeaux University Hospital (CHU), Electrophysiology and Ablation Unit, Pessac, France
| | - Olivier Bernus
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France.,University of Bordeaux, CRCTB, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
| | - Rémi Dubois
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France.,University of Bordeaux, CRCTB, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
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15
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Schaufelberger M, Schuler S, Bear L, Cluitmans M, Coll-Font J, Onak ÖN, Dössel O, Brooks D. Comparison of Activation Times Estimation for Potential-Based ECG Imaging. COMPUTING IN CARDIOLOGY 2019; 46:10.22489/cinc.2019.379. [PMID: 32190705 PMCID: PMC7079739 DOI: 10.22489/cinc.2019.379] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Activation times (AT) describe the sequence of cardiac depolarization and represent one of the most important parameters for analysis of cardiac electrical activity. However, estimation of ATs can be challenging due to multiple sources of noise such as fractionation or baseline wander. If ATs are estimated from signals reconstructed using electrocardiographic imaging (ECGI), additional problems can arise from over-smoothing or due to ambiguities in the inverse problem. Often, resulting AT maps show falsely homogeneous regions or artificial lines of block. As ATs are not only important clinically, but are also commonly used for evaluation of ECGI methods, it is important to understand where these errors come from. We present results from a community effort to compare methods for AT estimation on a common dataset of simulated ventricular pacings. ECGI reconstructions were performed using three different surface source models: transmembrane voltages, epi-endo potentials and pericardial potentials, all using 2nd-order Tikhonov and 6 different regularization parameters. ATs were then estimated by the community participants and compared to the ground truth. While the pacing site had the largest effect on AT correlation coefficients (CC larger for lateral than for septal pacings), there were also differences between methods and source models that were poorly reflected in CCs. Results indicate that artificial lines of block are most severe for purely temporal methods. Compared to the other source models, ATs estimated from transmembrane voltages are more precise and less prone to artifacts.
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Affiliation(s)
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Laura Bear
- IHU-LIRYC Electrophysiology and Heart Modeling Institute, Pessac-Bordeaux, France
| | - Matthijs Cluitmans
- Maastricht School for Cardiovascular Diseases, Maastricht UMC, Maastricht, Netherlands
| | - Jaume Coll-Font
- Department of Electrical & Computer Engineering, Northeastern University, Boston, USA
| | | | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Dana Brooks
- Department of Electrical & Computer Engineering, Northeastern University, Boston, USA
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