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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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Pilia N, Schuler S, Rees M, Moik G, Potyagaylo D, Dössel O, Loewe A. Non-invasive localization of the ventricular excitation origin without patient-specific geometries using deep learning. Artif Intell Med 2023; 143:102619. [PMID: 37673581 DOI: 10.1016/j.artmed.2023.102619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 06/18/2023] [Accepted: 06/24/2023] [Indexed: 09/08/2023]
Abstract
Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categorized as sudden cardiac death, which can be related to ventricular tachycardia (VT). This type of arrhythmia can be caused by focal activation sources outside the sinus node. Catheter ablation of these foci is a curative treatment in order to inactivate the abnormal triggering activity. However, the localization procedure is usually time-consuming and requires an invasive procedure in the catheter lab. To facilitate and expedite the treatment, we present two novel localization support techniques based on convolutional neural networks (CNNs) that address these clinical needs. In contrast to existing methods, our approaches were designed to be independent of the patient-specific geometry and directly applicable to surface ECG signals, while also delivering a binary transmural position. Moreover, one of the method's outputs can be interpreted as several ranked solutions. The CNNs were trained on a dataset containing only simulated data and evaluated both on simulated test data and clinical data. On a novel large and open simulated dataset, the median test error was below 3 mm. The median localization error on the unseen clinical data ranged from 32 mm to 41 mm without optimizing the pre-processing and CNN to the clinical data. Interpreting the output of one of the approaches as ranked solutions, the best median error of the top-3 solutions decreased to 20 mm on the clinical data. The transmural position was correctly detected in up to 82% of all clinical cases. These results demonstrate a proof of principle to utilize CNNs to localize the activation source without the intrinsic need for patient-specific geometrical information. Furthermore, providing multiple solutions can assist physicians in identifying the true activation source amongst more than one possible location. With further optimization to clinical data, these methods have high potential to accelerate clinical interventions, replace certain steps within these procedures and consequently reduce procedural risk and improve VT patient outcomes.
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Affiliation(s)
- Nicolas Pilia
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Maike Rees
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gerald Moik
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | | | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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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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Bear LR, Bergquist JA, Abell E, Cochet H, MacLeod RS, Dubois R, Serinagaoglu Y. Investigation into the importance of using natural PVCs and pathological models for potential-based ECGI validation. Front Physiol 2023; 14:1198002. [PMID: 37275229 PMCID: PMC10232953 DOI: 10.3389/fphys.2023.1198002] [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: 04/28/2023] [Indexed: 06/07/2023] Open
Abstract
Introduction: Premature ventricular contractions (PVCs) are one of the most commonly targeted pathologies for ECGI validation, often through ventricular stimulation to mimic the ectopic beat. However, it remains unclear if such stimulated beats faithfully reproduce spontaneously occurring PVCs, particularly in the case of the R-on-T phenomenon. The objective of this study was to determine the differences in ECGI accuracy when reconstructing spontaneous PVCs as compared to ventricular-stimulated beats and to explore the impact of pathophysiological perturbation on this reconstruction accuracy. Methods: Langendorff-perfused pig hearts (n = 3) were suspended in a human torso-shaped tank, and local hyperkalemia was induced through perfusion of a high-K+ solution (8 mM) into the LAD. Recordings were taken simultaneously from the heart and tank surfaces during ventricular pacing and during spontaneous PVCs (including R-on-T), both at baseline and high K+. Epicardial potentials were reconstructed from torso potentials using ECGI. Results: Spontaneously occurring PVCs were better reconstructed than stimulated beats at baseline in terms of electrogram morphology [correlation coefficient (CC) = 0.74 ± 0.05 vs. CC = 0.60 ± 0.10], potential maps (CC = 0.61 ± 0.06 vs. CC = 0.51 ± 0.12), and activation time maps (CC = 0.86 ± 0.07 vs. 0.76 ± 0.10), though there was no difference in the localization error (LE) of epicardial origin (LE = 14 ± 6 vs. 15 ± 11 mm). High K+ perfusion reduced the accuracy of ECGI reconstructions in terms of electrogram morphology (CC = 0.68 ± 0.10) and AT maps (CC = 0.70 ± 0.12 and 0.59 ± 0.23) for isolated PVCs and paced beats, respectively. LE trended worse, but the change was not significant (LE = 17 ± 9 and 20 ± 12 mm). Spontaneous PVCs were less well when the R-on-T phenomenon occurred and the activation wavefronts encountered a line of block. Conclusion: This study demonstrates the differences in ECGI accuracy between spontaneous PVCs and ventricular-paced beats. We also observed a reduction in this accuracy near regions of electrically inactive tissue. These results highlight the need for more physiologically realistic experimental models when evaluating the accuracy of ECGI methods. In particular, reconstruction accuracy needs to be further evaluated in the presence of R-on-T or isolated PVCs, particularly when encountering obstacles (functional or anatomical) which cause line of block and re-entry.
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Affiliation(s)
- Laura R. Bear
- IHU-Liryc, Heart Rhythm Disease Institute, Foundation Bordeaux Université, Bordeaux, France
- University Bordeaux, CRCTB, Bordeaux, France
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Jake A. Bergquist
- Scientific Computing and Imaging Institute, University of Utah, Salt LakeCity, UT, United States
- Norra Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt LakeCity, UT, United States
- Department of Biomedical Engineering, University of Utah, Salt LakeCity, UT, United States
| | - Emma Abell
- IHU-Liryc, Heart Rhythm Disease Institute, Foundation Bordeaux Université, Bordeaux, France
- University Bordeaux, CRCTB, Bordeaux, France
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Hubert Cochet
- IHU-Liryc, Heart Rhythm Disease Institute, Foundation Bordeaux Université, Bordeaux, France
- University Bordeaux, CRCTB, Bordeaux, France
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
- Bordeaux University Hospital (CHU), Pessac, France
| | - Rob S. MacLeod
- Scientific Computing and Imaging Institute, University of Utah, Salt LakeCity, UT, United States
- Norra Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt LakeCity, UT, United States
- Department of Biomedical Engineering, University of Utah, Salt LakeCity, UT, United States
| | - Remi Dubois
- IHU-Liryc, Heart Rhythm Disease Institute, Foundation Bordeaux Université, Bordeaux, France
- University Bordeaux, CRCTB, Bordeaux, France
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Yesim Serinagaoglu
- Electrical-Electronics Engineering Department, Middle East Technical University, Ankara, Türkiye
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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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Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS. Reconstruction of cardiac position using body surface potentials. Comput Biol Med 2022; 142:105174. [DOI: 10.1016/j.compbiomed.2021.105174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/22/2021] [Accepted: 12/23/2021] [Indexed: 11/03/2022]
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