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Keywords = electrocardiographic imaging (ECGi)

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19 pages, 13145 KiB  
Article
AI-Powered Noninvasive Electrocardiographic Imaging Using the Priori-to-Attention Network (P2AN) for Wearable Health Monitoring
by Shijie He, Hanrui Dong, Xianbin Zhang, Richard Millham, Lin Xu and Wanqing Wu
Sensors 2025, 25(6), 1810; https://doi.org/10.3390/s25061810 - 14 Mar 2025
Viewed by 809
Abstract
The rapid development of smart wearable devices has significantly advanced noninvasive, continuous health monitoring, enabling real-time collection of vital biosignals. Electrocardiographic imaging (ECGI), a noninvasive technique that reconstructs transmembrane potential (TMP) from body surface potential, has emerged as a promising method for reflecting [...] Read more.
The rapid development of smart wearable devices has significantly advanced noninvasive, continuous health monitoring, enabling real-time collection of vital biosignals. Electrocardiographic imaging (ECGI), a noninvasive technique that reconstructs transmembrane potential (TMP) from body surface potential, has emerged as a promising method for reflecting cardiac electrical activity. However, the ECG inverse problem’s inherent instability has hindered its practical application. To address this, we introduce a novel Priori-to-Attention Network (P2AN) that enhances the stability of ECGI solutions. By leveraging the one-dimensional nature of electrical signals and the body’s electrical propagation properties, P2AN uses small-scale convolutions for attention computation, integrating a priori physiological knowledge via cross-attention mechanisms. This approach eliminates the need for clinical TMP measurements and improves solution accuracy through normalization constraints. We evaluate the method’s effectiveness in diagnosing myocardial ischemia and ventricular hypertrophy, demonstrating significant improvements in TMP reconstruction and lesion localization. Moreover, P2AN exhibits high robustness in noisy environments, making it highly suitable for integration with wearable electrocardiographic clothing. By improving spatiotemporal accuracy and noise resilience, P2AN offers a promising solution for noninvasive, real-time cardiovascular monitoring using AI-powered wearable devices. Full article
(This article belongs to the Special Issue Advances in ECG/EEG Monitoring)
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13 pages, 5691 KiB  
Case Report
Fusion Imaging of Non-Invasive and Invasive Cardiac Electroanatomic Mapping in Patients with Ventricular Ectopic Beats: A Feasibility Analysis in a Case Series
by Matilda Muça, Stepan Zubarev, Dirk Bastian, Janusch Walaschek, Veronica Buia, Harald Rittger, Arsenii Dokuchaev, Thomas Bayer and Laura Vitali-Serdoz
Diagnostics 2024, 14(6), 622; https://doi.org/10.3390/diagnostics14060622 - 15 Mar 2024
Cited by 1 | Viewed by 1574
Abstract
In patients with premature ventricular contractions (PVCs), non-invasive mapping could locate the PVCs’ origin on a personalized 3-dimensional (3D) heart model and, thus, facilitate catheter ablation therapy planning. The aim of our report is to evaluate its accuracy compared to invasive mapping in [...] Read more.
In patients with premature ventricular contractions (PVCs), non-invasive mapping could locate the PVCs’ origin on a personalized 3-dimensional (3D) heart model and, thus, facilitate catheter ablation therapy planning. The aim of our report is to evaluate its accuracy compared to invasive mapping in terms of assessing the PVCs’ early activation zone (EAZ). For this purpose, non-invasive electrocardiographic imaging (ECGI) was performed using the Amycard 01C system (EP Solutions SA, Switzerland) in three cases. In the first step, a multichannel ECG (up to 224 electrodes) was recorded, and the dominant PVCs were registered. Afterward, a cardiac computed tomography (in two cases) or magnetic resonance imaging (in one case) investigation was carried out acquiring non-contrast torso scans for 8-electrode strip visualization and contrast heart acquisition. For the reconstructed epi/endocardial meshes of the heart, non-invasive isochronal maps were generated for the selected multichannel ECG fragments. Then, the patients underwent an invasive electrophysiological study, and the PVCs’ activation was evaluated by a 3D mapping system (EnSite NavX Precision, Abbott). Finally, using custom-written software, we performed 3D fusion of the non-invasive and invasive models and compared the resulting isochronal maps. A qualitative analysis in each case showed the same early localization of the dominant PVC on the endocardial surface when comparing the non-invasive and invasive isochronal maps. The distance from the EAZ to the mitral or tricuspid annulus was comparable in the invasive/non-invasive data (36/41 mm in case N1, 73/75 mm in case N2, 9/12 mm in case N3). The area of EAZ was also similar between the invasive/non-invasive maps (4.3/4.5 cm2 in case N1, 7.1/7.0 cm2 in case N2, 0.4/0.6 cm2 in case N3). The distances from the non-invasive to invasive earliest activation site were 4 mm in case N1, 7 mm in case N2, and 4 mm in case N3. Such results were appropriate to trust the clinical value of the preoperative data in these cases. In conclusion, the non-invasive identification of PVCs before an invasive electrophysiological study can guide clinical and interventional decisions, demonstrating appropriate accuracy in the estimation of focus origin. Full article
(This article belongs to the Special Issue Diagnosis and Prognosis of Heart Disease)
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13 pages, 2289 KiB  
Review
Current Role of Electrocardiographic Imaging in Patient Selection for Cardiac Resynchronization Therapy
by Saer Abu-Alrub, Marc Strik, Peter Huntjens, Michel Haïssaguerre, Romain Eschalier, Pierre Bordachar and Sylvain Ploux
J. Cardiovasc. Dev. Dis. 2024, 11(1), 24; https://doi.org/10.3390/jcdd11010024 - 15 Jan 2024
Viewed by 2395
Abstract
Cardiac resynchronization therapy (CRT) is a recognized therapy for heart failure with altered ejection fraction and abnormal left ventricular activation time. Since the introduction of the therapy, a 30% rate of non-responders is observed and unchanged. The 12-lead ECG remains the only recommended [...] Read more.
Cardiac resynchronization therapy (CRT) is a recognized therapy for heart failure with altered ejection fraction and abnormal left ventricular activation time. Since the introduction of the therapy, a 30% rate of non-responders is observed and unchanged. The 12-lead ECG remains the only recommended tool for patient selection to CRT. The 12-lead ECG is, however, limited in its inability to provide a precise pattern of regional electrical activity. Electrocardiographic imaging (ECGi) provides a non-invasive detailed mapping of cardiac activation and therefore appears as a promising tool for CRT candidates. The non-invasive ventricular activation maps acquired by ECGi have been primarily explored for the diagnosis and guidance of therapy in patients with atrial or ventricular tachyarrhythmia. However, the accuracy of the system in this field is lacking and needs further improvement before considering a clinical application. On the other hand, its use for patient selection for CRT is encouraging. In this review, we introduce the technical considerations and we describe how ECGi can precisely characterize ventricular activation, especially in patients with left bundle branch block, thus identifying the electrical substrate responsive to CRT. Full article
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18 pages, 6830 KiB  
Article
Solving Inverse Electrocardiographic Mapping Using Machine Learning and Deep Learning Frameworks
by Ke-Wei Chen, Laura Bear and Che-Wei Lin
Sensors 2022, 22(6), 2331; https://doi.org/10.3390/s22062331 - 17 Mar 2022
Cited by 17 | Viewed by 4332
Abstract
Electrocardiographic imaging (ECGi) reconstructs electrograms at the heart’s surface using the potentials recorded at the body’s surface. This is called the inverse problem of electrocardiography. This study aimed to improve on the current solution methods using machine learning and deep learning frameworks. Electrocardiograms [...] Read more.
Electrocardiographic imaging (ECGi) reconstructs electrograms at the heart’s surface using the potentials recorded at the body’s surface. This is called the inverse problem of electrocardiography. This study aimed to improve on the current solution methods using machine learning and deep learning frameworks. Electrocardiograms were simultaneously recorded from pigs’ ventricles and their body surfaces. The Fully Connected Neural network (FCN), Long Short-term Memory (LSTM), Convolutional Neural Network (CNN) methods were used for constructing the model. A method is developed to align the data across different pigs. We evaluated the method using leave-one-out cross-validation. For the best result, the overall median of the correlation coefficient of the predicted ECG wave was 0.74. This study demonstrated that a neural network can be used to solve the inverse problem of ECGi with relatively small datasets, with an accuracy compatible with current standard methods. Full article
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14 pages, 3440 KiB  
Article
Personalized Evaluation of Atrial Complexity of Patients Undergoing Atrial Fibrillation Ablation: A Clinical Computational Study
by Ana María Sánchez de la Nava, Ana González Mansilla, Esteban González-Torrecilla, Pablo Ávila, Tomás Datino, Javier Bermejo, Ángel Arenal, Francisco Fernández-Avilés and Felipe Atienza
Biology 2021, 10(9), 838; https://doi.org/10.3390/biology10090838 - 28 Aug 2021
Cited by 6 | Viewed by 2476
Abstract
Current clinical guidelines establish Pulmonary Vein (PV) isolation as the indicated treatment for Atrial Fibrillation (AF). However, AF can also be triggered or sustained due to atrial drivers located elsewhere in the atria. We designed a new simulation workflow based on personalized computer [...] Read more.
Current clinical guidelines establish Pulmonary Vein (PV) isolation as the indicated treatment for Atrial Fibrillation (AF). However, AF can also be triggered or sustained due to atrial drivers located elsewhere in the atria. We designed a new simulation workflow based on personalized computer simulations to characterize AF complexity of patients undergoing PV ablation, validated with non-invasive electrocardiographic imaging and evaluated at one year after ablation. We included 30 patients using atrial anatomies segmented from MRI and simulated an automata model for the electrical modelling, consisting of three states (resting, excited and refractory). In total, 100 different scenarios were simulated per anatomy varying rotor number and location. The 3 states were calibrated with Koivumaki action potential, entropy maps were obtained from the electrograms and compared with ECGi for each patient to analyze PV isolation outcome. The completion of the workflow indicated that successful AF ablation occurred in patients with rotors mainly located at the PV antrum, while unsuccessful procedures presented greater number of driving sites outside the PV area. The number of rotors attached to the PV was significantly higher in patients with favorable long-term ablation outcome (1-year freedom from AF: 1.61 ± 0.21 vs. AF recurrence: 1.40 ± 0.20; p-value = 0.018). The presented workflow could improve patient stratification for PV ablation by screening the complexity of the atria. Full article
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19 pages, 3999 KiB  
Article
Excitation and Contraction of the Failing Human Heart In Situ and Effects of Cardiac Resynchronization Therapy: Application of Electrocardiographic Imaging and Speckle Tracking Echo-Cardiography
by Christopher M. Andrews, Gautam K. Singh and Yoram Rudy
Hearts 2021, 2(3), 331-349; https://doi.org/10.3390/hearts2030027 - 23 Jul 2021
Cited by 1 | Viewed by 4008
Abstract
Despite the success of cardiac resynchronization therapy (CRT) for treating heart failure (HF), the rate of nonresponders remains 30%. Improvements to CRT require understanding of reverse remodeling and the relationship between electrical and mechanical measures of synchrony. The objective was to utilize electrocardiographic [...] Read more.
Despite the success of cardiac resynchronization therapy (CRT) for treating heart failure (HF), the rate of nonresponders remains 30%. Improvements to CRT require understanding of reverse remodeling and the relationship between electrical and mechanical measures of synchrony. The objective was to utilize electrocardiographic imaging (ECGI, a method for noninvasive cardiac electrophysiology mapping) and speckle tracking echocardiography (STE) to study the physiology of HF and reverse remodeling induced by CRT. We imaged 30 patients (63% male, mean age 63.7 years) longitudinally using ECGI and STE. We quantified CRT-induced remodeling of electromechanical parameters and evaluated a novel index, the electromechanical delay (EMD, the delay from activation to peak contraction). We also measured dyssynchrony using ECGI and STE and compared their effectiveness for predicting response to CRT. EMD values were elevated in HF patients compared to controls. However, the EMD values were dependent on the activation sequence (CRT-paced vs. un-paced), indicating that the EMD is not intrinsic to the local tissue, but is influenced by factors such as opposing wall contractions. After 6 months of CRT, patients had increased contraction in native rhythm compared to baseline pre-CRT (baseline: −8.55%, 6 months: −10.14%, p = 0.008). They also had prolonged repolarization at the location of the LV pacing lead. The pre-CRT delay between mean lateral LV and RV electrical activation time was the best predictor of beneficial reduction in LV end systolic volume by CRT (Spearman’s Rho: −0.722, p < 0.001); it outperformed mechanical indices and 12-lead ECG criteria. HF patients have abnormal EMD. The EMD depends upon the activation sequence and is not predictive of response to CRT. ECGI-measured LV activation delay is an effective index for CRT patient selection. CRT causes persistent improvements in contractile function. Full article
(This article belongs to the Special Issue The Application of Computer Techniques to ECG Interpretation)
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28 pages, 5764 KiB  
Article
Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials
by Raúl Caulier-Cisterna, Margarita Sanromán-Junquera, Sergio Muñoz-Romero, Manuel Blanco-Velasco, Rebeca Goya-Esteban, Arcadi García-Alberola and José Luis Rojo-Álvarez
Sensors 2020, 20(11), 3131; https://doi.org/10.3390/s20113131 - 1 Jun 2020
Cited by 7 | Viewed by 3741
Abstract
During the last years, Electrocardiographic Imaging (ECGI) has emerged as a powerful and promising clinical tool to support cardiologists. Starting from a plurality of potential measurements on the torso, ECGI yields a noninvasive estimation of their causing potentials on the epicardium. This unprecedented [...] Read more.
During the last years, Electrocardiographic Imaging (ECGI) has emerged as a powerful and promising clinical tool to support cardiologists. Starting from a plurality of potential measurements on the torso, ECGI yields a noninvasive estimation of their causing potentials on the epicardium. This unprecedented amount of measured cardiac signals needs to be conditioned and adapted to current knowledge and methods in cardiac electrophysiology in order to maximize its support to the clinical practice. In this setting, many cardiac indices are defined in terms of the so-called bipolar electrograms, which correspond with differential potentials between two spatially close potential measurements. Our aim was to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology. For this purpose, we first analyzed the basic stages of conventional cardiac signal processing and scrutinized the implications of the spatial-temporal nature of signals in ECGI scenarios. Specifically, the stages of baseline wander removal, low-pass filtering, and beat segmentation and synchronization were considered. We also aimed to establish a mathematical operator to provide suitable bipolar electrograms from the ECGI-estimated epicardium potentials. Results were obtained on data from an infarction patient and from a healthy subject. First, the low-frequency and high-frequency noises are shown to be non-independently distributed in the ECGI-estimated recordings due to their spatial dimension. Second, bipolar electrograms are better estimated when using the criterion of the maximum-amplitude difference between spatial neighbors, but also a temporal delay in discrete time of about 40 samples has to be included to obtain the usual morphology in clinical bipolar electrograms from catheters. We conclude that spatial-temporal digital signal processing and bipolar electrograms can pave the way towards the usefulness of ECGI recordings in the cardiological clinical practice. The companion paper is devoted to analyzing clinical indices obtained from ECGI epicardial electrograms measuring waveform variability and repolarization tissue properties. Full article
(This article belongs to the Special Issue Recent Advances in ECG Monitoring)
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24 pages, 12555 KiB  
Article
Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (II): Electrogram Clustering and T-Wave Alternans
by Raúl Caulier-Cisterna, Manuel Blanco-Velasco, Rebeca Goya-Esteban, Sergio Muñoz-Romero, Margarita Sanromán-Junquera, Arcadi García-Alberola and José Luis Rojo-Álvarez
Sensors 2020, 20(11), 3070; https://doi.org/10.3390/s20113070 - 29 May 2020
Cited by 5 | Viewed by 3306
Abstract
During the last years, attention and controversy have been present for the first commercially available equipment being used in Electrocardiographic Imaging (ECGI), a new cardiac diagnostic tool which opens up a new field of diagnostic possibilities. Previous knowledge and criteria of cardiologists using [...] Read more.
During the last years, attention and controversy have been present for the first commercially available equipment being used in Electrocardiographic Imaging (ECGI), a new cardiac diagnostic tool which opens up a new field of diagnostic possibilities. Previous knowledge and criteria of cardiologists using intracardiac Electrograms (EGM) should be revisited from the newly available spatial–temporal potentials, and digital signal processing should be readapted to this new data structure. Aiming to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology, we previously presented two results: First, spatial consistency can be observed even for very basic cardiac signal processing stages (such as baseline wander and low-pass filtering); second, useful bipolar EGMs can be obtained by a digital processing operator searching for the maximum amplitude and including a time delay. In addition, this work aims to demonstrate the functionality of ECGI for cardiac electrophysiology from a twofold view, namely, through the analysis of the EGM waveforms, and by studying the ventricular repolarization properties. The former is scrutinized in terms of the clustering properties of the unipolar an bipolar EGM waveforms, in control and myocardial infarction subjects, and the latter is analyzed using the properties of T-wave alternans (TWA) in control and in Long-QT syndrome (LQTS) example subjects. Clustered regions of the EGMs were spatially consistent and congruent with the presence of infarcted tissue in unipolar EGMs, and bipolar EGMs with adequate signal processing operators hold this consistency and yielded a larger, yet moderate, number of spatial–temporal regions. TWA was not present in control compared with an LQTS subject in terms of the estimated alternans amplitude from the unipolar EGMs, however, higher spatial–temporal variation was present in LQTS torso and epicardium measurements, which was consistent through three different methods of alternans estimation. We conclude that spatial–temporal analysis of EGMs in ECGI will pave the way towards enhanced usefulness in the clinical practice, so that atomic signal processing approach should be conveniently revisited to be able to deal with the great amount of information that ECGI conveys for the clinician. Full article
(This article belongs to the Special Issue Recent Advances in ECG Monitoring)
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