Epicardial Potentials Research Articles

Tensor cardiography: A novel ECG analysis of deviations in collective myocardial action potential transitions based on point processes and cumulative distribution functions.

To improve clinical diagnoses, assessments of potential cardiac disease risk, and predictions of lethal arrhythmias, the analysis of electrocardiograms (ECGs) requires a more accurate method of weighting waveforms to efficiently detect abnormalities that appear as minute strains in the waveforms. In addition, the inverse problem of estimating the myocardial action potential from the ECG has been a longstanding challenge. To analyze the variance of the ECG waveforms and to estimate collective myocardial action potentials (APs) from the ECG, we designed a model equation incorporating the probability densities of Gaussian functions of time-series point processes in the cardiac cycle and dipoles of the collective APs in the myocardium. The equation, which involves taking the difference between the cumulative distribution functions (CDFs) that represent positive endocardial and negative epicardial potentials, fits both R and T waves. The mean, standard deviation, weights, and level of each cumulative distribution function (CDF) are metrics for the variance of the transition state of the collective myocardial AP. Clinical ECGs of myocardial ischemia during coronary intervention show abnormalities in the aforementioned specific elements of the tensor associated with repolarization transition variance earlier than in conventional indicators of ischemia. The tensor can be used to evaluate the beat-to-beat dynamic repolarization changes between the ventricular epi and endocardium in terms of the Mahalanobis distance (MD). This tensor-based cardiography that uses the differences between CDFs to show changes in collective myocardial APs has the potential to be a new analysis tool for ECGs.

Investigation into the importance of using natural PVCs and pathological models for potential-based ECGI validation.

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 (8mM) 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 ± 11mm). 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 ± 12mm). 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.

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.

Abstract 11481: Non-Invasive Electrocardiographic Mapping of the Human Heart Through a Novel 'Cardiac Magnetic Resonance-Electrocardiographic Imaging' Solution for High Throughput Use

Background: Electrocardiographic imaging (ECGI) non-invasively maps the heart’s electrical activity through multiple leads on the body surface. Cardiologists need a safe, quick, affordable and re-usable ECGI method to apply to patients undergoing cardiovascular magnetic resonance (CMR), but current solutions are not suitable for high-throughput use. We developed a CMR-ECGI vest for high-throughput use and report the first in vivo results. Methods: We designed and fabricated the CMR-ECGI vest from cotton, containing 256 square (2x2cm) dry textile electrodes each tagged with a localisation marker ( Fig 1 ). Body surface potentials were recorded and co-registered with heart-torso geometries obtained from CMR ( Fig 2 ). Epicardial unipolar potentials were reconstructed using state-of-the-art ECGI algorithms (YR Lab) and local activation and repolarization times were computed using standard methods. Results: Ten healthy volunteers with normal resting ECGs were recruited (34±10years; 60% male). A recumbent 5-minute ECGI recording was performed (preparation time ~15 minutes for montage and doffing). 3 Tesla CMR provided baseline parameters (left ventricular ejection fraction [LVEF] 75±5%, right ventricular [RV] EF 57±5%, native T1 1275±23ms, T2 42±1ms) and showed no clinically significant late gadolinium enhancement. ECGI showed that the sites of earliest and latest activation were the basal RV ( Fig 3A ) and basal-lateral LV respectively ( Fig 3B ). Total duration of epicardial activation and repolarization was 73.3±8.9ms and 195±35.2ms, respectively. These epicardial activation patterns in health are in line with previously described ECGI data. Conclusions: We have developed a re-usable and high-throughput CMR-ECGI solution that is safe and well-tolerated in vivo . This technology is now available for large-scale clinical research use to provide deeper insights into the pathophysiology of arrhythmogenesis, through seamless integration with CMR.

3D Cardiac Computational Model for Evaluating the Progression of Myocardial Ischemia in a Supply-Demand Paradigm.

In this paper, we present a cardiac computational framework aimed at simulating the effects of ischemia on cardiac potentials and hemodynamics. Proposed cardiac model uses an image based pipeline for modeling and analysis of the ischemic condition in-silico. We compute epicardial potential as well as body surface potential (BSP) for acute ischemic conditions based on data from animal model while varying both local coronary supply and global metabolic demand. Single lead ECG equivalent signal processed from computed BSP is used to drive a lumped hemodynamic model and derive left ventricular dynamics. Computational framework combining 3d structural information from image data and integrating electrophysiology and hemodynamics functionality is aimed to evaluate additional cardiac markers along with conventional electrical markers visible during acute ischemia and give a broader understanding of ischemic manifestation leading to pathophysiological changes. Simulation of epicardial to bodysurface potential followed by estimation of hemodynamic parameters like ejection fraction, contractility, blood pressure, etc, would help to infer subtle changes detectable beyond conventional ST segment changes.

Comparison of electrical dyssynchrony parameters between electrocardiographic imaging and a simulated ECG belt

AimsElectrocardiographic imaging (ECGi) and the ECG belt are body surface potential mapping systems which can assess electrical dyssynchrony in patients undergoing cardiac resynchronization therapy (CRT). ECGi-derived dyssynchrony metrics are calculated from reconstructed epicardial potentials based on body surface potentials combined with a thoracic CT scan, while the ECG belt relies on body surface potentials alone. The relationship between dyssynchrony metrics from these two systems is unknown. In this study we aim to compare intra-ventricular and inter-ventricular dyssynchrony metrics between ECGi and the ECG belt. MethodsSeventeen patients underwent ECGi after CRT. A subsample of 40 body surface potentials was used to simulate the ECG belt. ECGi dyssynchrony metrics, calculated from reconstructed epicardial potentials, and ECG belt dyssynchrony metrics, calculated from the sampled body surface potentials were compared. ResultsThere was a strong positive correlation between ECGi left ventricular activation time (LVAT) and ECG belt left thorax activation time (LTAT) (R = 0.88 ; P < 0.001) and between ECGi standard deviation of activation times (SDAT) and ECG belt-SDAT (R = 0.76; P < 0.001) during intrinsic rhythm. The correlation for both pairs was also strong during biventricular pacing. Ventricular electrical uncoupling, a well validated ECGi inter-ventricular dyssynchrony metric, correlated strongly with ECG belt-SDAT during intrinsic rhythm (R = 0.76; P < 0.001) but not biventricular pacing (R = 0.29; P = 0.26). Cranial or caudal displacement of the simulated ECG belt did not affect LTAT or SDAT. ConclusionECGi- and ECG belt-derived intra-ventricular and inter-ventricular dyssynchrony metrics were strongly correlated. The ECG belt may offer comparable dyssynchrony assessment to ECGi, with associated practical and cost advantages.

Electrocardiographic Imaging: A Comparison of Iterative Solvers.

Cardiac disease is a leading cause of morbidity and mortality in developed countries. Currently, non-invasive techniques that can identify patients at risk and provide accurate diagnosis and ablation guidance therapy are under development. One of these is electrocardiographic imaging (ECGI). In ECGI, the first step is to formulate a forward problem that relates the unknown potential sources on the cardiac surface to the measured body surface potentials. Then, the unknown potential sources on the cardiac surface are reconstructed through the solution of an inverse problem. Unfortunately, ECGI still lacks accuracy due to the underlying inverse problem being ill-posed, and this consequently imposes limitations on the understanding and treatment of many cardiac diseases. Therefore, it is necessary to improve the solution of the inverse problem. In this work, we transfer and adapt four inverse problem methods to the ECGI setting: algebraic reconstruction technique (ART), random ART, ART Split Bregman (ART-SB) and range restricted generalized minimal residual (RRGMRES) method. We test all these methods with data from the Experimental Data and Geometric Analysis Repository (EDGAR) and compare their solution with the recorded epicardial potentials provided by EDGAR and a generalized minimal residual (GMRES) iterative method computed solution. Activation maps are also computed and compared. The results show that ART achieved the most stable solutions and, for some datasets, returned the best reconstruction. Differences between the solutions derived from ART and random ART are almost negligible, and the accuracy of their solutions is followed by RRGMRES, ART-SB and finally the GMRES (which returned the worst reconstructions). The RRGMRES method provided the best reconstruction for some datasets but appeared to be less stable than ART when comparing different datasets. In conclusion, we show that the proposed methods (ART, random ART, and RRGMRES) improve the GMRES solution, which has been suggested as inverse problem solution for ECGI.

Electrocardiographic imaging including intracardiac information to achieve accurate global mapping during atrial fibrillation

Atrial fibrillation (AF) is characterized by complex and irregular propagation patterns. Noninvasive electrocardiographic imaging (ECGI) has been tested during AF conditions with promising results. However, current regularization methods face important challenges in this type of unstable electrical activity scenarios. Combination of intracardiac and non-invasive simultaneous recordings could improve ECGI performance and allow real-time global mapping of complex AF patterns. In this work, we propose an ECGI method that incorporates intracardiac measurements as a constraint in a reformulation of the classical Tikhonov method. We used realistic mathematical models of atria and torso that simulates a wide number of epicardial electrical activity patterns. Body surface potentials were obtained from simulated electrograms (EGMs) by using Boundary Element Method and corrupted with Gaussian noise. Epicardial potentials were estimated using inverse problem with Tikhonov regularization, including intracavitary information as a second constraint. Results showed that first-order Constrained Tikhonov formulation provided more reliable reconstructions than the classical Tikhonov approach in AF conditions using at least 32 uniformly distributed endocardial EGMs (CC between 0.87 and 0.28, depending on the AF complexity). Constrained Tikhonov provided more accurate spatial mass functions (SMF) of PS locations (CCSMF between 0.24 and 0.86). This methodology was tested on real patient data, obtaining a mean DF RMSE of 0.85 Hz, outperforming the classical Tikhonov approach. Limitations of this study include the fact that the model considered endocardium and epicardium as a single layer. Further research will include endocardium–epicardium bilayer model approximations and validation using more real patient data.

Visualization of Cardiac Vectors using Electrocardiography and Magnetocardiography

In this paper, an attempt is made to simulate and compare spatio-temporal VCG and VMCG derived from epicardial potentials. Electric (EHV) and Magnetic heart vectors (MHV) are computed from the ECG and MCG at various time instants and their orientations with respect to time are found to show a reasonable tilt of 90 to 100 degrees. The complimentary information with reference to the orientation of cardiac vector offered by MHV could be attributed to its sensitivity to intracellular myocardial currents, while EHV exhibits the orientation associated with only the extracellular currents owing to volume conduction. By comparing the orientations of EHV and MHV generated from a simulated equivalent current dipole model, the present work demonstrates the usefulness of these spatiotemporal vectors in tracing the cardiac current flow inside the thorax for a healthy heart. It could be thus expected that clinically relevant information could be obtained if the present analysis is extended to highly complex and irregular cardiac activation sequences that could be seen in arrhythmia and myocardial infarction. The main contribution of this paper is to mathematically model and derive the magnetic heart vectors from the MCG system extracted from IGCAR lab and verify it with the conventional VCG extraction..

IRN-MLSQR: An improved iterative reweight norm approach to the inverse problem of electrocardiography incorporating factorization-free preconditioned LSQR

The inverse problem of electrocardiography (ECG) of computing epicardial potentials from body surface potentials, is an ill-posed problem and needs to be solved by regularization techniques. The L2-norm regularization can cause considerable smoothing of the solution, while the L1-norm scheme promotes a solution with sharp boundaries/gradients between piecewise smooth regions, so L1-norm is widely used in the ECG inverse problem. However, large amount of computation and long computation time are needed in the L1-norm scheme. In this paper, by combining iterative reweight norm (IRN) with a factorization-free preconditioned LSQR algorithm (MLSQR), a new IRN-MLSQR method was proposed to accelerate the convergence speed of the L1-norm scheme. We validated the IRN-MLSQR method using experimental data from isolated canine hearts and clinical procedures in the electrophysiology laboratory. The results showed that the IRN-MLSQR method can significantly reduce the number of iterations and operation time while ensuring the calculation accuracy. The number of iterations of the IRN-MLSQR method is about 60%–70% that of the conventional IRN method, and at the same time, the accuracy of the solution is almost the same as that of the conventional IRN method. The proposed IRN-MLSQR method may be used as a new approach to the inverse problem of ECG.

P436The impact of filter settings on morphology of unipolar fibrillation potentials

Abstract Funding Acknowledgements N.M.S. de Groot, MD, PhD was supported by CVON-AFFIP (914728), NWO-Vidi (91717339) and Biosense Webster USA (ICD 783454). Background Using unipolar atrial electrogram morphology as guidance for ablative therapy is regaining interest. Although standardly used in clinical practice during ablative therapy, the impact of filter settings on morphology of unipolar AF potentials is unknown. Purpose This study aims to elucidate consequences of high-pass, low-pass and notch filtering on unipolar atrial fibrillation (AF) potentials. Methods Thirty different filter settings were applied to high-resolution epicardial AF potentials recorded from ten patients. . Local activation times were determined by marking deflections with slope ≤-0.05mV/ms and amplitude ≥0.3mV. Fibrillation potentials were analyzed for peak-to-peak amplitude (mV), number of deflections (f) and fractionation delay time (FDT, interval between first and last deflection), and classified as single potential (SP, f = 1), double potential (DP, f = 2) or complex fractionated potential (CP, f ≥ 3). Results In total, 3000 seconds of AF recordings were analyzed, containing 255,7045 fibrillation potentials. Changing high-pass filtering from 0.5 up to 100 Hz decreased the number of detected fibrillation potentials (with 25-65%), median deflection amplitude (min-max 0.59-0.96 to 0.44-0.57 mV), percentage of DP (25.8-32.9 to 22.5-31.6%) and CP (15.9-36.0 to 7.3-37.8%) as well as median FDT (16-25 to 11-15 ms) (all p &amp;lt; 0.01). Gradually changing low-pass filtering from 400 Hz to 20 Hz induced an exponential decrease in fibrillation potentials (to 0%), percentage of DP (25.8-32.9 to 0%) and CP (15.9-36.0 to 0%), whereas deflection amplitude, percentage of SP and median FDT exponentially increased (0.59-0.96 to 1.82-2.39 mV, 36.1-57.6 to 100%, 16-25 to 33-38 ms, respectively) (all p &amp;lt; 0.01). Notch filtering at 50 Hz decreased the number of detected fibrillation potentials (with ∼1%), median deflection amplitude (0.59-0.96 to 0.59-0.95 mV) (both p &amp;lt; 0.01), whereas the percentage of CP increased (15.9-36.0 to 16.2-37.0%, p = 0.016). Conclusions Filtering significantly impacted of unipolar fibrillation potentials and decreased the number of detected potentials, becoming a potential source of error in identification of LATs, low-voltage areas, fractionated potentials and thus ablative targets during mapping. Potentials (%) Amplitude (mV) SP (%) DP (%) CFP (%) FDT (ms) Default (0.5-400 Hz) 100 0.59-0.96 36.1-57.6 25.8-32.9 15.9-36.0 16.0-25.0 High-pass filtering Decreased Decreased Increased Decreased Decreased Decreased Low-pass filtering Decreased Increased Increased Decreased Decreased Increased Notch filtering Decreased Decreased p = NS p = NS Increased p = NS Impact of filtering on morphology parameters Abstract Figure. Impact of filtering on AF morphology

The Impact of Filter Settings on Morphology of Unipolar Fibrillation Potentials

Using unipolar atrial electrogram morphology as guidance for ablative therapy is regaining interest. Although standardly used in clinical practice during ablative therapy, the impact of filter settings on morphology of unipolar AF potentials is unknown. Thirty different filters were applied to 2,557,045 high-resolution epicardial AF potentials recorded from ten patients. Deflections with slope ≤ − 0.05 mV/ms and amplitude ≥ 0.3 mV were marked. High-pass filtering decreased the number of detected potentials, deflection amplitude, and percentage of fractionated potentials (≥ 2 deflections) as well as fractionation delay time (FDT) and increased percentage of single potentials. Low-pass filtering decreased the number of potentials, percentage of fractionated potentials, whereas deflection amplitude, percentage of single potentials, and FDT increased. Notch filtering (50 Hz) decreased the number of potentials and deflection amplitude, whereas the percentage of complex fractionated potentials (≥ 3 deflections) increased. Filtering significantly impacted morphology of unipolar fibrillation potentials, becoming a potential source of error in identification of ablative targets.Graphical Impact of filtering on morphology of unipolar AF potentials. High-pass, low-pass and notch filters were applied to 2,557,045 high-resolution epicardial AF potentials recorded from ten patients. Filtering significantly impacted AF potential morphology, i.e., number of detected potentials, peak-to-peak amplitude, number of deflections, and fractionation delay time. CFP, complex fractionated potential (≥ 3 deflections); DP, double potential (two deflections); FDT, fractionation delay time; SP, single potential (one deflection).

Effect of Torso Non-Homogeneities in the quasi-static inverse problems arising in electrocardiology

Abstract In the present paper, an homogeneous and non-homogeneous inverse problem constrained by the stationary problem in electrocardiology representing the heart, lungs surfaces, and torso model is investigated. Our goal is to reconstruct the electrical potentials on the surface of the heart from the information obtained non invasively on the torso surface. The existence and uniqueness of solution for the heart-torso problem and the related inverse problem is assessed, and the primal and dual problems are discretized using a finite element method. We present some preliminary numerical experiments using an efficient implementation of the proposed scheme in homogeneous and non-homogeneous cases. Finally, we demonstrate the effect of the non-homogeneity on the reconstructed epicardial potential and show that the inverse ECG problem cannot be solved by the classical BEM (boundary element method).

P6591Arrhythmogenic effects of non-steroidal anti-inflammatory drugs (NSAID)

Abstract Background Clinical and experimental data suggest potential deleterious effects of non-steroidal anti-inflammatory drugs (NSAID) in cardiac disease. The aim of the present study was to characterize potential direct arrhythmogenic effects of ibuprofen or indometacin on cardiac electrophysiology. Methods and results In 13 isolated rabbit hearts, indometacin was administered in increasing concentrations (10, 30 and 50μM) after obtaining baseline data. In further 13 hearts, ibuprofen was infused (10, 30 and 50μM). Eight endo- and epicardial monophasic action potentials and a simultaneously recorded 12-lead ECG showed a significant decrease of QT-interval in indometacin- (50μM: −60ms, p&lt;0.05) and ibuprofen-treated hearts (50μM: −81ms, p&lt;0.01). This was accompanied by a similar decrease of action potential duration (APD). Effective refractory period (ERP) was also reduced by indometacin (−24ms, p&lt;0.05) and ibuprofen (−22ms, p&lt;0.05) while spatial dispersion of repolarisation remained stable with both drugs. Programmed ventricular stimulation and burst stimulation were employed for provocation of ventricular arrhythmias. In the indomethacin group 7 episodes of ventricular arrhythmias were inducible at baseline. The incidence was increased to 22 (10μM), 37 (30μM) and 51 (50μM) with higher concentrations of indometacin. In the ibuprofen group 15 episodes were inducible at baseline. After infusion of 10μM ibuprofen, also 15 episodes of ventricular arrhythmias occurred while 34 episodes were inducible with 30μM ibuprofen. Conclusion Infusion of the NSAID ibuprofen and indometacin resulted in a significant abbreviation of myocardial repolarization and a shortening of ventricular refractory periods. This resulted in an enhanced inducibility of ventricular arrhythmias and may contribute to the proposed deleterious effects of NSAID in the presence of cardiac disease.

P1600Querecetin prevents electrophysiolgical remodeling and reperfusion arrhythmias in dysmetabolic rats

Abstract Background Severe arrhythmias during reperfusion of myocardial infarctions are associated with increased mortality. High fat and fructose diet (HFFD) increases arrhythmic risk and predispose to diseases such as diabetes, hypertension, and dyslipidemia. Quercetin is a bioactive flavonol found in grapes and grapes derived products. This flavonoid has been proposed to prevent cardiovascular disease, but little is known about its electrophysiological properties. Objective To evaluate the electrophysiological effects of chronic quercetin administration in rats with increased arrhythmogenesis during the reperfusion due to a HFFD. Methods Male Wistar rats were fed for six weeks with control diet (C), HFFD (20% fat and 20% fructose w/w), HFFD supplemented with quercetin in a dose of 20 mg/kg/day (HFFDQ) or quercetin alone (Q). Isolated hearts were perfused with a Krebs-Henseleit solution and after 15 min stabilization, submitted to 10 min of regional ischemia followed by10 min of reperfusion. Epicardial action potential and arrhythmic events were analyzed. Results HFFD and HFFDQ developed metabolic syndrome, but action potential at 90% of repolarization lengthening only increased in HFFD (78±4 vs 55±3 ms, P&lt;0.01 by ANOVAII). HFFD increased ventricular fibrillation incidence (HFFD 8 of 9; C 2 of 9 P=0.0152 by Fisher Exact test). Both groups treated with quercetin had low arrhythmic incidence (HFFDQ 2 of 10 and Q 1 of 9; P&lt;0.0055 and P&lt;0.0034, respectively when compared with HFFD). The severity of arrhythmias persisted high during reperfusion only in HFFD. Other less severe arrhythmias like salvos and extra beats occurred in similar proportion in the three other groups. Conclusion The above results confirm that a HFFD facilitates the occurrence of severe arrhythmias during reperfusion. Quercetin reduces arrhythmias and electrophysiological remodeling despite metabolic syndrome. Since quercetin is one of the most abundant dietary flavonoids, our results reinforce its nutraceutical potential. Acknowledgement/Funding I+D+i UNCuyo 2015

Noninvasive Mapping and Electrocardiographic Imaging in Atrial and Ventricular Arrhythmias (CardioInsight).

Electrocardiographic imaging is a mapping technique aiming to noninvasively characterize cardiac electrical activity using signals collected from the torso to reconstruct epicardial potentials. Its efficacy has been demonstrated clinically, from mapping premature ventricular complexes and accessory pathways to of complex arrhythmias. Electrocardiographic imaging uses a standardized workflow. Signals should be checked manually to avoid automatic processing errors. Reentry is confirmed in the presence of local activation covering the arrhythmia cycle length. Focal breakthroughs demonstrate a QS pattern associated with centrifugal activation. Electrocardiographic imaging offers a unique opportunity to better understand the mechanism of cardiac arrhythmias and guide ablation.

ML and MAP estimation of parameters for the Kalman filter and smoother applied to electrocardiographic imaging

In electrocardiographic imaging (ECGI), one solves the inverse problem of electrocardiography (ECG) to reconstruct equivalent cardiac sources based on the body surface potential measurements and a mathematical model of the torso. Due to attenuation and spatial smoothing within the torso, this inverse problem is ill-posed. Among many regularization approaches used in the ECG literature to overcome this ill-posedness, statistical techniques have received great attention because of their flexibility to represent the data, and ability to provide performance evaluation tools for quantification of uncertainties and errors in the model. However, despite their potential to accurately reconstruct the equivalent cardiac sources, one major challenge in these methods is how to best utilize the prior information available in terms of training data. In this paper, we address the question of how to define the prior probability distributions (pdf) of the sources and the error terms so that we can obtain more accurate and robust inverse solutions. We employ two methods, maximum likelihood (ML) and maximum a posteriori (MAP), for estimating the model parameters such as the prior pdfs, error pdfs, and the state-transition matrix, based on the same training data. These model parameters are then used for the state-space representation and estimation of the epicardial potentials, which constitute the equivalent cardiac sources in this study. The performances of ML- and MAP-based model parameter estimation methods are evaluated qualitatively and quantitatively at various noise levels and geometric disturbances using two different simulated datasets. Bayesian MAP estimation, which is also a well-known statistical inversion technique, and Tikhonov regularization, which can be formulated as a special and simplified version of Bayesian MAP estimation, have been included here for comparison with the Kalman filtering method. Our results show that the state-space approach outperforms Bayesian MAP estimation in all cases; ML yields accurate results when the test and training beats come from the same physiological model, but MAP is superior to ML, especially if the test and training beats are from different physiological models. Graphical Abstract ML and MAP estimation of parameters for the Kalman filter and smoother applied to electrocardiographic imaging.

Characteristics of Marshall bundle-related atrial tachycardias using an ultrahigh-resolution mapping system.

Marshall bundle (MB)-related atrial tachycardias (ATs) have already been described; however, their characteristics using an ultrahigh-resolution mapping system are not yet well known. The purpose of this study was to clarify the characteristics of MB-related ATs with ultrahigh-resolution mapping. In 28 patients who underwent an electrophysiological study for ATs using an ultrahigh-resolution mapping system, precise circuits of 37 ATs were detected. Among those ATs, five were diagnosed as MB-related ATs that had epicardial connections among the reentrant circuits (mean age 76.6 ± 3.7years, one male patient). We analyzed the characteristics of those MB-related ATs with ultrahigh-resolution mapping. The mean cycle length was 260 ± 60ms, and the total acquired electrograms were 12,962 ± 2616 points. Two ATs were perimitral ATs, two rotated around the left pulmonary vein (PV), and one rotated around the left inferior PV. All ATs had a centrifugal activation pattern: 5 o'clock on the mitral annulus in four ATs and the upper ridge in one. Tiny potentials, which indicated epicardial potentials covering the cycle length, were detected in four of five ATs. The local activation times covered over 95% of the tachycardia cycle length on the endocardial side only in all ATs. All ATs were terminated during a radiofrequency ablation from the endocardial side of the Marshall bundle. The ultrahigh-resolution mapping system demonstrated an activation map of MB-related ATs with a centrifugal pattern. Macroreentrant tachycardias with a centrifugal activation pattern should be considered as possible MB-related ATs.

Considering New Regularization Parameter-Choice Techniques for the Tikhonov Method to Improve the Accuracy of Electrocardiographic Imaging.

The electrocardiographic imaging (ECGI) inverse problem highly relies on adding constraints, a process called regularization, as the problem is ill-posed. When there are no prior information provided about the unknown epicardial potentials, the Tikhonov regularization method seems to be the most commonly used technique. In the Tikhonov approach the weight of the constraints is determined by the regularization parameter. However, the regularization parameter is problem and data dependent, meaning that different numerical models or different clinical data may require different regularization parameters. Then, we need to have as many regularization parameter-choice methods as techniques to validate them. In this work, we addressed this issue by showing that the Discrete Picard Condition (DPC) can guide a good regularization parameter choice for the two-norm Tikhonov method. We also studied the feasibility of two techniques: The U-curve method (not yet used in the cardiac field) and a novel automatic method, called ADPC due its basis on the DPC. Both techniques were tested with simulated and experimental data when using the method of fundamental solutions as a numerical model. Their efficacy was compared with the efficacy of two widely used techniques in the literature, the L-curve and the CRESO methods. These solutions showed the feasibility of the new techniques in the cardiac setting, an improvement of the morphology of the reconstructed epicardial potentials, and in most of the cases of their amplitude.

ECG Imaging to Detect the Site of Ventricular Ischemia Using Torso Electrodes: A Computational Study.

Electrocardiography provides some information useful for ischemic diagnosis. However, more recently there has been substantial growth in the area of ECG imaging, which by solving the inverse problem of electrocardiography aims to produce high-resolution mapping of the electrical and magnetic dynamics of the heart. Most inverse studies use the full resolution of the body surface potential (BSP) to reconstruct the epicardial potentials, however using a limited number of torso electrodes to interpolate the BSP is more clinically relevant and has an important effect on the reconstruction which must be quantified. A circular ischemic lesion on the right ventricle lateral wall 27 mm in radius is reconstructed using three Tikhonov methods along with 6 different electrode configurations ranging from 32 leads to 1,024 leads. The 2nd order Tikhonov solution performed the most accurately (~80% lesion identified) followed by the 1st (~50% lesion identified) and then the 0 order Tikhonov solution performed the worst with a maximum of ~30% lesion identified regardless of how many leads were used. With an increasing number of leads the solution produces less error, and the error becomes more localised around the lesion for all three regularisation methods. In noisy conditions, the relative performance gap of the 1st and 2nd order Tikhonov solutions was reduced, and determining an accurate regularisation parameter became relatively more difficult. Lesions located on the left ventricle walls were also able to be identified but comparatively to the right ventricle lateral wall performed marginally worse with lesions located on the interventricular septum being able to be indicated by the reconstructions but not successfully identified against the error. The quality of reconstruction was found to decrease as the lesion radius decreased, with a lesion radius of <20 mm becoming difficult to correctly identify against the error even when using >512 torso electrodes.