Functional substrate mapping of atrium in patients with atrial scar: A novel method to predict critical isthmus of atrial tachycardia.

Atrial tachycardia (AT) is a common rhythm disorder, especially in patients with atrial structural abnormalities. Although voltage mapping can provide a general picture of structural alterations which are mainly secondary to prior ablations, surgery or pressure/volume overload, data is scarce regarding the functional characteristics of low voltage regions in the atrium to predict critical isthmus of ATs. Recently, functional substrate mapping (FSM) emerged as a potential tool to evaluate the functionality of structurally altered regions in the atrium to predict critical sites of reentry. Current evidence suggested a clear association between deceleration zones of isochronal late activation mapping (ILAM) during sinus/paced rhythm and critical isthmus of reentry in patients with left AT. Therefore, these areas seem to be potential ablation targets even not detected during AT. Furthermore, abnormal conduction detected by ILAM may also have a role to identify the potential substrate and predict atrial fibrillation outcome after pulmonary vein isolation. Despite these promising findings, the utility of such an approach needs to be evaluated in large-scale comparative studies. In this review, we aimed to share our experience and review the current literature regarding the use of FSM during sinus/paced rhythm in the prediction of re-entrant ATs and discuss future implications and potential use in patients with atrial low-voltage areas.

Characterization of conduction system activation in the postinfarct ventricle using ripple mapping.

BACKGROUND: Three-dimensional (3D) mapping of the ventricular conduction system is challenging. OBJECTIVE: The purpose of this study was to use ripple mapping to distinguish conduction system activation to that of adjacent myocardium in order to characterize the conduction system in the postinfarct left ventricle (LV). METHODS: High-density mapping (PentaRay, CARTO) was performed during normal rhythm in patients undergoing ventricular tachycardia ablation. Ripple maps were viewed from the end of the P wave to QRS onset in 1-ms increments. Clusters of >3 ripple bars were interrogated for the presence of Purkinje potentials, which were tagged on the 3D geometry. Repeating this process allowed conduction system delineation. RESULTS: Maps were reviewed in 24 patients (mean 3112 ± 613 points). There were 150.9 ± 24.5 Purkinje potentials per map, at the left posterior fascicle (LPF) in 22 patients (92%) and at the left anterior fascicle (LAF) in 15 patients (63%). The LAF was shorter (41.4 vs 68.8 mm; P = .0005) and activated for a shorter duration (40.6 vs 64.9 ms; P = .002) than the LPF. Fourteen of 24 patients had left bundle branch block (LBBB), with 11 of 14 (78%) having Purkinje potential-associated breakout. There were fewer breakouts from the conduction system during LBBB (1.8 vs 3.4; 1.6 ± 0.6; P = .039) and an inverse correlation between breakout sites and QRS duration (P = .0035). CONCLUSION: We applied ripple mapping to present a detailed electroanatomic characterization of the conduction system in the postinfarct LV. Patients with broader QRS had fewer LV breakout sites from the conduction system. However, there was 3D mapping evidence of LV breakout from an intact conduction system in the majority of patients with LBBB.

A reduced complexity ECG imaging model for regularized inversion optimization.

The resolution of the inverse problem of electrocardiography represents a major interest in the diagnosis and catheter-based therapy of cardiac arrhythmia. In this context, the ability to simulate several cardiac electrical behaviors was crucial for evaluating and comparing the performance of inversion methods. For this application, existing models are either too complex or do not produce realistic cardiac patterns. In this work, a low-resolution heart-torso model generating realistic whole heart cardiac mappings and electrocardiograms in healthy and pathological cases is designed. This model was built upon a simplified heart-torso geometry and implements the monodomain formalism by using the finite element method. In addition, a model reduction step through a sensitivity analysis was proposed where parameters were identified using an evolutionary optimization approach. Finally, the study illustrates the usefulness of the proposed model by comparing the performance of different variants of Tikhonov-based inversion methods for the determination of the regularization parameter in healthy, ischemic and ventricular tachycardia scenarios. First, results of the sensitivity analysis show that among 58 parameters only 25 are influent. Note also that the level of influence of the parameters depends on the heart region. Besides, the synthesized electrocardiograms globally present the same characteristic shape compared to the reference once with a correlation value that reaches 88%. Regarding inverse problem, results highlight that only Robust Generalized Cross Validation and Discrepancy Principle provide best performance, with a quasi-perfect success rate for both, and a respective relative error, between the generated electrocardiograms to the reference one, of 0.75 and 0.62.

An expert review of the inverse problem in electrocardiographic imaging for the non-invasive identification of atrial fibrillation drivers.

BACKGROUND AND OBJECTIVE: Electrocardiographic imaging (ECGI) has emerged as a non-invasive approach to identify atrial fibrillation (AF) driver sources. This paper aims to collect and review the current research literature on the ECGI inverse problem, summarize the research progress, and propose potential research directions for the future. METHODS AND RESULTS: The effectiveness and feasibility of using ECGI to map AF driver sources may be influenced by several factors, such as inaccuracies in the atrial model due to heart movement or deformation, noise interference in high-density body surface potential (BSP), inconvenient and time-consuming BSP acquisition, errors in solving the inverse problem, and incomplete interpretation of the AF driving source information derived from the reconstructed epicardial potential. We review the current research progress on these factors and discuss possible improvement directions. Additionally, we highlight the limitations of ECGI itself, including the lack of a gold standard to validate the accuracy of ECGI technology in locating AF drivers and the challenges associated with guiding AF ablation based on post-processed epicardial potentials due to the intrinsic difference between epicardial and endocardial potentials. CONCLUSIONS: Before performing ablation, ECGI can provide operators with predictive information about the underlying locations of AF driver by non-invasively and globally mapping the biatrial electrical activity. In the future, endocardial catheter mapping technology may benefit from the use of ECGI to enhance the diagnosis and ablation of AF.

Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location.

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: Multiple­lead 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.

Electrocardiographic imaging in the atria.

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.

A Patchwork Method to Improve the Performance of Current Methods for Solving the Inverse Problem of Electrocardiography.

OBJECTIVE: Noninvasive electrocardiographic imaging (ECGI) reconstructs cardiac electrical activity from body surface potential measurements. However, current methods have demonstrated inaccuracies in reconstructing sinus rhythm, and in particular breakthrough sites. This study aims to combine existing inverse algorithms, making the most of their advantages while minimizing their limitations. METHOD: The "patchwork method" (PM) combines two classical numerical methods for ECGI: the method of fundamental solutions (MFS) and the finite-element method (FEM). We assume that the method with the smallest residual in the predicted torso potentials, computed using the boundary element method (BEM), provides the most accurate solution. The PM selects for each heart node and time step the method whose estimated reconstruction error is smallest. The performance of the PM was evaluated using simulated ectopic and normal ventricular beats. RESULTS: Cardiac potentials and activation maps obtained with the PM (CC = 0.63 ± 0.01 and 0.61 ± 0.05 respectively) were more accurate than MFS (CC = 0.61 ± 0.01 and 0.48 ± 0.05 respectively), FEM (CC = 0.58 ± 0.01 and 0.51 ± 0.02 respectively) or BEM (CC = 0.57 ± 0.02 and 0.49 ± 0.02 respectively). The PM also located all epicardial breakthrough sites, whereas the traditional numerical methods usually missed one. Furthermore, the PM showed its robustness and stability in the presence of Gaussian noise added to the torso potentials. CONCLUSION: The PM overcomes some of the limitations of classical numerical methods, improving the accuracy of mapping important features of activation during sinus rhythm and paced beats. SIGNIFICANCE: This novel method for optimizing ECGI solutions opens a new avenue for improving not only ECGI but also other inverse problems.

Comfortable Body Surface Potential Mapping by Means of a Dry Electrode Belt.

Body Surface Potential Mapping is the spatial high-resolution acquisition of cardiac electrical activity from the thorax surface. The method is used to record more comprehensive cardiac information than conventional ECG measurement approaches. Although Body Surface Potential Mapping is well-known and is technically feasible, it is rarely used in clinical environments. One reason for this is the cumbersome procedure of a measurement. The placement of many adhesive gel electrodes and the contacting with many cables are particularly problematic. These limit both patients and medical staff. Therefore, the goal of this work is to technically simplify Body Surface Potential Mapping so that it would be applicable under clinical conditions. For this purpose, we present a new measurement approach in which only a narrow elastic belt is placed around the thorax to measure the electrical activity of the heart. This belt is equipped with an array of reusable gold-plated dry electrodes. With these dry electrodes, the differential voltages are measured in the horizontal and vertical directions. Afterwards, an approximation of the geometrical potential distribution on the thorax is obtained from these measurements. The results are then visualized as videos or image series or used for further analysis. A subject measurement demonstrates the applicability of this novel approach. It is shown that the obtained Body Surface Potential Maps are very similar to those found in the literature, despite a reduced spatial measurement range. This approach is not only applicable for clinical applications but also suitable for monitoring during physiological training.

Generalization and Regularization for Inverse Cardiac Estimators.

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.

High-resolution structure-function mapping of intact hearts reveals altered sympathetic control of infarct border zones.

Remodeling of injured sympathetic nerves on the heart after myocardial infarction (MI) contributes to adverse outcomes such as sudden arrhythmic death, yet the underlying structural mechanisms are poorly understood. We sought to examine microstructural changes on the heart after MI and to directly link these changes with electrical dysfunction. We developed a high-resolution pipeline for anatomically precise alignment of electrical maps with structural myofiber and nerve-fiber maps created by customized computer vision algorithms. Using this integrative approach in a mouse model, we identified distinct structure-function correlates to objectively delineate the infarct border zone, a known source of arrhythmias after MI. During tyramine-induced sympathetic nerve activation, we demonstrated regional patterns of altered electrical conduction aligned directly with altered neuroeffector junction distribution, pointing to potential neural substrates for cardiac arrhythmia. This study establishes a synergistic framework for examining structure-function relationships after MI with microscopic precision that has potential to advance understanding of arrhythmogenic mechanisms.

Modeling the His-Purkinje Effect in Non-invasive Estimation of Endocardial and Epicardial Ventricular Activation.

Inverse electrocardiography (iECG) estimates epi- and endocardial electrical activity from body surface potentials maps (BSPM). In individuals at risk for cardiomyopathy, non-invasive estimation of normal ventricular activation may provide valuable information to aid risk stratification to prevent sudden cardiac death. However, multiple simultaneous activation wavefronts initiated by the His-Purkinje system, severely complicate iECG. To improve the estimation of normal ventricular activation, the iECG method should accurately mimic the effect of the His-Purkinje system, which is not taken into account in the previously published multi-focal iECG. Therefore, we introduce the novel multi-wave iECG method and report on its performance. Multi-wave iECG and multi-focal iECG were tested in four patients undergoing invasive electro-anatomical mapping during normal ventricular activation. In each subject, 67-electrode BSPM were recorded and used as input for both iECG methods. The iECG and invasive local activation timing (LAT) maps were compared. Median epicardial inter-map correlation coefficient (CC) between invasive LAT maps and estimated multi-wave iECG versus multi-focal iECG was 0.61 versus 0.31. Endocardial inter-map CC was 0.54 respectively 0.22. Modeling the His-Purkinje system resulted in a physiologically realistic and robust non-invasive estimation of normal ventricular activation, which might enable the early detection of cardiac disease during normal sinus rhythm.

Spatiotemporal approximation of cardiac activation and recovery isochrones.

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.

Reconstruction of cardiac position using body surface potentials.

Electrocardiographic imaging (ECGI) is a noninvasive technique to assess the bioelectric activity of the heart which has been applied to aid in clinical diagnosis and management of cardiac dysfunction. ECGI is built on mathematical models that take into account several patient specific factors including the position of the heart within the torso. Errors in the localization of the heart within the torso, as might arise due to natural changes in heart position from respiration or changes in body position, contribute to errors in ECGI reconstructions of the cardiac activity, thereby reducing the clinical utility of ECGI. In this study we present a novel method for the reconstruction of cardiac geometry utilizing noninvasively acquired body surface potential measurements. Our geometric correction method simultaneously estimates the cardiac position over a series of heartbeats by leveraging an iterative approach which alternates between estimating the cardiac bioelectric source across all heartbeats and then estimating cardiac positions for each heartbeat. We demonstrate that our geometric correction method is able to reduce geometric error and improve ECGI accuracy in a wide range of testing scenarios. We examine the performance of our geometric correction method using different activation sequences, ranges of cardiac motion, and body surface electrode configurations. We find that after geometric correction resulting ECGI solution accuracy is improved and variability of the ECGI solutions between heartbeats is substantially reduced.

A Novel Data-Adaptive Regression Framework Based on Multivariate Adaptive Regression Splines for Electrocardiographic Imaging.

OBJECTIVE: Noninvasive electrocardiographic imaging (ECGI) is a promising tool for revealing crucial cardiac electrical events with diagnostic potential. We propose a novel nonparametric regression framework based on multivariate adaptive regression splines (MARS) for ECGI. METHODS: The inverse problem was solved by using the regression model trained with body surface potentials (BSP) and corresponding electrograms (EGM). Simulated data as well as experimental data from torso-tank experiments were used to assess the performance of the proposed method. The robustness of the method to measurement noise and geometric errors were assessed in terms of electrogram reconstruction quality, activation time accuracy, and localization error metrics. The methods were compared with Tikhonov regularization and neural network (NN)-based methods. The resulting mapping functions between the BSPs and EGMs were also used to evaluate the most influential measurement leads. RESULTS: MARS-based method outperformed Tikhonov regularization in terms of reconstruction accuracy and robustness to measurement noise. The effects of geometric errors were remedied to some extent by enriching the training set composition including model errors. The MARS-based method had a comparable performance with NN-based methods, which require the adjustment of many parameters. CONCLUSION: MARS-based method successfully discovers the inverse mapping functions between the BSPs and EGMs yielding accurate reconstructions, and quantifies the contribution of each BSP lead. SIGNIFICANCE: MARS-based method is adaptive, requires fewer parameter adjustments than NN-based methods, and is robust to errors. Thus, it can be a feasible data-driven approach for accurately solving inverse imaging problems.

Utilising electroanatomic mapping during ablation in patients with CHD to reduce radiation exposure.

BACKGROUND: Patients with CHD can be exposed to high levels of cumulative ionising radiation. Utilisation of electroanatomic mapping during catheter ablation leads to reduced radiation exposure in the general population but has not been well studied in patients with CHD. This study evaluated the radiation sparing benefit of using three-dimensional mapping in patients with CHD. METHODS: Data were retrospectively collected from the Catheter Ablation with Reduction or Elimination of Fluoroscopy multi-institutional registry. Patients with CHD were selected. Those with previous ablations, concurrent diagnostic or interventional catheterisation and unknown arrhythmogenic foci were excluded. The control cohort was matched for operating physician, arrhythmia mechanism, arrhythmia location, weight and age. The procedure time, rate of fluoroscopy use, fluoroscopy time, procedural success, complications, and distribution of procedures per year were compared between the two groups. RESULTS: Fifty-six patients with congenital heart disease and 56 matched patients without CHD were included. The mean total procedure time was significantly higher in patients with CHD (212.6 versus 169.5 minutes, p = 0.003). Their median total fluoroscopy time was 4.4 minutes (compared to 1.8 minutes), and their rate of fluoroscopy use was 23% (compared to 13%). The acute success and minor complication rates were similar and no major complications occurred. CONCLUSIONS: With the use of electroanatomic mapping during catheter ablation, fluoroscopy use can be reduced in patients with CHD. The majority of patients with CHD received zero fluoroscopy.

Ventricular arrhythmias ablated successfully in the subvalvular interleaflet triangle between the right and left coronary cusps: Electrophysiological characteristics and catheter ablation.

BACKGROUND: Ventricular arrhythmias (VAs) ablated successfully at the right-left subvalvular interleaflet triangle (R-L ILT) between right and left coronary cusps have not been fully characterized. OBJECTIVE: The purpose of this study was to investigate the electrophysiological characteristics of these VAs and their relationships with the left ventricular (LV) summit. METHODS: Twenty-eight VAs ablated successfully at the R-L ILT were studied. RESULTS: Ninety-six percent of VAs had an early precordial electrocardiographic transition. R-wave amplitude in lead V1 was relatively high (RS morphology, R-wave amplitude 0.35 ± 0.09 mV; R/S ratio 0.35 ± 0.27), whereas the morphology of lead I was R-shaped in 71% and M-shaped in 50% of VAs. Earliest potential was recorded at the R-L ILT in 13 of 28 patients and the left pulmonary sinus cusp (LC) in 6 of 28 patients. Mapping the summit communicating vein (summit-CV) failed because of anatomic or instrumental limitations in these 19 patients. In the other 9 patients, earliest potential was successfully recorded at the summit-CV, while perfect pacemapping was achieved. Poor pace mapping was achieved at the R-L ILT or LC in most patients (27/28). Target site was located at the top of the R-L ILT in all cases. A presystolic potential was present at the target site in 18 of 28 patients. A U-curve via the retrograde method was conventionally used to reach the top of the R-L ILT. CONCLUSION: VAs ablated successfully at the R-L ILT have unique electrophysiological characteristics, and R-L ILT may be an endocardial anatomic ablation target for VAs originating from the base of the LV summit.

Substrate Characterization and Outcomes of Ventricular Tachycardia Ablation in TTN (Titin) Cardiomyopathy: A Multicenter Study.

[Figure: see text].

Propagation Vectors Facilitate Differentiation Between Conduction Block, Slow Conduction, and Wavefront Collision.

[Figure: see text].