Single-beat noninvasive imaging of cardiac electrophysiology of ventricular pre-excitation

Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem

BACKGROUND

The risk stratification and prognosis of cardiac arrhythmia depend on the individual condition of patients, while invasive diagnostic methods may be risky to patient health, and current non-invasive diagnostic methods are applicable to few disease types without sensitivity and specificity. Cardiac electrophysiologic imaging (ECGI) technology reflects cardiac activities accurately and non-invasively, which is of great significance for the diagnosis and treatment of cardiac diseases. This paper aims to provide a new solution for the realization of ECGI by combining simulation model and deep learning methods.

METHODS

A complete three-dimensional bidomain cardiac electrophysiologic activity model was constructed, and simulated electrocardiogram data were obtained as training samples. Particle swarm optimization-back propagation neural network, convolutional neural network, and long short-term memory network were used respectively to reconstruct the cardiac surface potential.

RESULTS

The correlation coefficients between the simulation results and the clinical data range from 75.76 to 84.61%. The P waves, PR intervals, QRS complex, and T waves in the simulated waveforms were within the normal clinical range, and the distribution trend of the simulated body surface potential mapping was consistent with the clinical data. The coefficient of determination R2 between the reconstruction results of all the algorithms and the true value is above 0.80, and the mean absolute error is below 2.1 mV, among which the R2 of long short-term memory network is about 0.99 and the mean absolute error about 0.5 mV.

CONCLUSIONS

The electrophysiologic model constructed in this study can reflect cardiac electrical activity, and contains the mapping relationship between the cardiac potential and the body surface potential. In cardiac potential reconstruction, long short-term memory network has significant advantages over other algorithms.

CLINICAL TRIAL NUMBER

Not applicable.

A computational study on the influence of antegrade accessory pathway location on the 12-lead electrocardiogram in Wolff-Parkinson-White syndrome

AIMS

Wolff-Parkinson-White (WPW) syndrome is a cardiovascular disease characterized by abnormal atrioventricular conduction facilitated by accessory pathways (APs). Invasive catheter ablation of the AP represents the primary treatment modality. Accurate localization of APs is crucial for successful ablation outcomes, but current diagnostic algorithms based on the 12-lead electrocardiogram (ECG) often struggle with precise determination of AP locations. In order to gain insight into the mechanisms underlying localization failures observed in current diagnostic algorithms, we employ a virtual cardiac model to elucidate the relationship between AP location and ECG morphology.

METHODS AND RESULTS

We first introduce a cardiac model of electrophysiology that was specifically tailored to represent antegrade APs in the form of a short atrioventricular bypass tract. Locations of antegrade APs were then automatically swept across both ventricles in the virtual model to generate a synthetic ECG database consisting of 9271 signals. Regional grouping of antegrade APs revealed overarching morphological patterns originating from diverse cardiac regions. We then applied variance-based sensitivity analysis relying on polynomial chaos expansion on the ECG database to mathematically quantify how variation in AP location and timing relates to morphological variation in the 12-lead ECG. We utilized our mechanistic virtual model to showcase the limitations of AP localization using standard ECG-based algorithms and provide mechanistic explanations through exemplary simulations.

CONCLUSION

Our findings highlight the potential of virtual models of cardiac electrophysiology not only to deepen our understanding of the underlying mechanisms of WPW syndrome but also to potentially enhance the diagnostic accuracy of ECG-based algorithms and facilitate personalized treatment planning.

Clinical magnetocardiography: the unshielded bet-past, present, and future

Magnetocardiography (MCG), which is nowadays 60 years old, has not yet been fully accepted as a clinical tool. Nevertheless, a large body of research and several clinical trials have demonstrated its reliability in providing additional diagnostic electrophysiological information if compared with conventional non-invasive electrocardiographic methods. Since the beginning, one major objective difficulty has been the need to clean the weak cardiac magnetic signals from the much higher environmental noise, especially that of urban and hospital environments. The obvious solution to record the magnetocardiogram in highly performant magnetically shielded rooms has provided the ideal setup for decades of research demonstrating the diagnostic potential of this technology. However, only a few clinical institutions have had the resources to install and run routinely such highly expensive and technically demanding systems. Therefore, increasing attempts have been made to develop cheaper alternatives to improve the magnetic signal-to-noise ratio allowing MCG in unshielded hospital environments. In this article, the most relevant milestones in the MCG's journey are reviewed, addressing the possible reasons beyond the currently long-lasting difficulty to reach a clinical breakthrough and leveraging the authors' personal experience since the early 1980s attempting to finally bring MCG to the patient's bedside for many years thus far. Their nearly four decades of foundational experimental and clinical research between shielded and unshielded solutions are summarized and referenced, following the original vision that MCG had to be intended as an unrivaled method for contactless assessment of the cardiac electrophysiology and as an advanced method for non-invasive electroanatomical imaging, through multimodal integration with other non-fluoroscopic imaging techniques. Whereas all the above accounts for the past, with the available innovative sensors and more affordable active shielding technologies, the present demonstrates that several novel systems have been developed and tested in multicenter clinical trials adopting both shielded and unshielded MCG built-in hospital environments. The future of MCG will mostly be dependent on the results from the ongoing progress in novel sensor technology, which is relatively soon foreseen to provide multiple alternatives for the construction of more compact, affordable, portable, and even wearable devices for unshielded MCG inside hospital environments and perhaps also for ambulatory patients.

Visualization of the SyncAV® Algorithm for CRT Optimization by Non-invasive Imaging of Cardiac Electrophysiology: NICE-CRT Trial

(1) Background: Periodic repetitive AV interval optimization using a device-based algorithm in cardiac resynchronization therapy (CRT) devices may improve clinical outcomes. There is an unmet need to successfully transform its application into clinical routine. (2) Methods: Non-invasive imaging of cardiac electrophysiology was performed in different device programming settings of the SyncAV^® algorithm in 14 heart failure patients with left bundle branch block and a PR interval ≤ 250 milliseconds to determine the shortest ventricular activation time. (3) Results: the best offset time (to be manually programmed) permitting automatic dynamic adjustment of the paced atrioventricular interval after every 256 heart beats was found to be 30 and 50 milliseconds, decreasing mean native QRS duration from 181.6 ± 23.9 milliseconds to 130.7 ± 10.0 and 130.1 ± 10.5 milliseconds, respectively (p = 0.01); this was followed by an offset of 40 milliseconds (decreasing QRS duration to 130.1 ± 12.2 milliseconds; p = 0.08). (4) Conclusions: The herein presented NICE-CRT study supports the current recommendation to program an offset of 50 milliseconds as default in patients with left bundle branch block and preserved atrioventricular conduction after implantation of a CRT device capable of SyncAV^® optimization. Alternatively, offset programming of 30 milliseconds may also be applied as default programming. In patients with no or poor CRT response, additional efforts should be spent to individualize best offset programming with electrocardiographic optimization techniques.

Reconstruction of three-dimensional biventricular activation based on the 12-lead electrocardiogram via patient-specific modelling

Aims

Non-invasive imaging of electrical activation requires high-density body surface potential mapping. The nine electrodes of the 12-lead electrocardiogram (ECG) are insufficient for a reliable reconstruction with standard inverse methods. Patient-specific modelling may offer an alternative route to physiologically constraint the reconstruction. The aim of the study was to assess the feasibility of reconstructing the fully 3D electrical activation map of the ventricles from the 12-lead ECG and cardiovascular magnetic resonance (CMR).

Methods and results

Ventricular activation was estimated by iteratively optimizing the parameters (conduction velocity and sites of earliest activation) of a patient-specific model to fit the simulated to the recorded ECG. Chest and cardiac anatomy of 11 patients (QRS duration 126–180 ms, documented scar in two) were segmented from CMR images. Scar presence was assessed by magnetic resonance (MR) contrast enhancement. Activation sequences were modelled with a physiologically based propagation model and ECGs with lead field theory. Validation was performed by comparing reconstructed activation maps with those acquired by invasive electroanatomical mapping of coronary sinus/veins (CS) and right ventricular (RV) and left ventricular (LV) endocardium. The QRS complex was correctly reproduced by the model (Pearson’s correlation r = 0.923). Reconstructions accurately located the earliest and latest activated LV regions (median barycentre distance 8.2 mm, IQR 8.8 mm). Correlation of simulated with recorded activation time was very good at LV endocardium (r = 0.83) and good at CS (r = 0.68) and RV endocardium (r = 0.58).

Conclusion

Non-invasive assessment of biventricular 3D activation using the 12-lead ECG and MR imaging is feasible. Potential applications include patient-specific modelling and pre-/per-procedural evaluation of ventricular activation.

Use of the inverse solution guidance algorithm method for RF ablation catheter guidance

INTRODUCTION

We previously introduced the inverse solution guidance algorithm (ISGA) methodology using a Single Equivalent Moving Dipole model of cardiac electrical activity to localize both the exit site of a re-entrant circuit and the tip of a radiofrequency (RF) ablation catheter. The purpose of this study was to investigate the use of ISGA for ablation catheter guidance in an animal model.

METHODS

Ventricular tachycardia (VT) was simulated by rapid ventricular pacing at a target site in eleven Yorkshire swine. The ablation target was established using three different techniques: a pacing lead placed into the ventricular wall at the mid-myocardial level (Type-1), an intracardiac mapping catheter (Type-2), and an RF ablation catheter placed at a random position on the endocardial surface (Type-3). In each experiment, one operator placed the catheter/pacing lead at the target location, while another used the ISGA system to manipulate the RF ablation catheter starting from a random ventricular location to locate the target.

RESULTS

The average localization error of the RF ablation catheter tip was 0.31 ± 0.08 cm. After analyzing approximately 35 cardiac cycles of simulated VT, the ISGA system's accuracy in locating the target was 0.4 cm after four catheter movements in the Type-1 experiment, 0.48 cm after six movements in the Type-2 experiment, and 0.67 cm after seven movements in the Type-3 experiment.

CONCLUSION

We demonstrated the feasibility of using the ISGA method to guide an ablation catheter to the origin of a VT focus by analyzing a few beats of body surface potentials without electro-anatomic mapping.

Electrocardiographic imaging for cardiac arrhythmias and resynchronization therapy

Use of the 12-lead electrocardiogram (ECG) is fundamental for the assessment of heart disease, including arrhythmias, but cannot always reveal the underlying mechanism or the location of the arrhythmia origin. Electrocardiographic imaging (ECGi) is a non-invasive multi-lead ECG-type imaging tool that enhances conventional 12-lead ECG. Although it is an established technology, its continuous development has been shown to assist in arrhythmic activation mapping and provide insights into the mechanism of cardiac resynchronization therapy (CRT). This review addresses the validity, reliability, and overall feasibility of ECGi for use in a diverse range of arrhythmias. A systematic search limited to full-text human studies published in peer-reviewed journals was performed through Medline via PubMed, using various combinations of three key concepts: ECGi, arrhythmia, and CRT. A total of 456 studies were screened through titles and abstracts. Ultimately, 42 studies were included for literature review. Evidence to date suggests that ECGi can be used to provide diagnostic insights regarding the mechanistic basis of arrhythmias and the location of arrhythmia origin. Furthermore, ECGi can yield valuable information to guide therapeutic decision-making, including during CRT. Several studies have used ECGi as a diagnostic tool for atrial and ventricular arrhythmias. More recently, studies have tested the value of this technique in predicting outcomes of CRT. As a non-invasive method for assessing cardiovascular disease, particularly arrhythmias, ECGi represents a significant advancement over standard procedures in contemporary cardiology. Its full potential has yet to be fully explored.

Acoustoelectric Signal Decoding Based on Fourier Approximation

The acoustoelectric (AE) effect is that ultrasonic wave causes the conductivity of electrolyte to change in local position. AE imaging is an imaging method that utilizes AE effect. The decoding accuracy of AE signal is of great significance to improve the decoded signal quality and resolution of AE imaging. At present, the envelope function is adopted to decode AE signal, but the timing characteristics of the decoded signal and the source signal are not very consistent. In order to further improve the decoding accuracy, based on envelope decoding, the decoding process of AE signal is investigated. Considering with the periodic property of AE signal in time series, the upper envelope signal is further fitted by Fourier approximation. Phantom experiment validates the feasibility of AE signal decoding by Fourier approximation. And the time sequence diagram decoded with envelope is also compared. The fitted curve can represent the overall trend curve of low-frequency current signal, which has a significant correspondence with the current source signal. The main performance is of the same frequency and phase. Experiment results validate that the proposed decoding algorithm can improve the decoding accuracy of AE signal and be of potential for the clinical application of AE imaging.

Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials

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.

How Accurate Is Inverse Electrocardiographic Mapping? A Systematic In Vivo Evaluation

BACKGROUND

Inverse electrocardiographic mapping reconstructs cardiac electrical activity from recorded body surface potentials. This noninvasive technique has been used to identify potential ablation targets. Despite this, there has been little systematic evaluation of its reliability.

METHODS

Torso and ventricular epicardial potentials were recorded simultaneously in anesthetized, closed-chest pigs (n=5), during sinus rhythm, epicardial, and endocardial ventricular pacing (70 records in total). Body surface and cardiac electrode positions were determined and registered using magnetic resonance imaging. Epicardial potentials were reconstructed during ventricular activation using experiment-specific magnetic resonance imaging-based thorax models, with homogeneous or inhomogeneous (lungs, skeletal muscle, fat) electrical properties. Coupled finite/boundary element methods and a meshless approach based on the method of fundamental solutions were compared. Inverse mapping underestimated epicardial potentials >2-fold (P<0.0001).

RESULTS

Mean correlation coefficients for reconstructed epicardial potential distributions ranged from 0.60±0.08 to 0.64±0.07 across all methods. Epicardial electrograms were recovered with reasonable fidelity at ≈50% of sites (median correlation coefficient, 0.69-0.72), but variation was substantial. General activation spread was reproduced (median correlation coefficient, 0.72-0.78 for activation time maps after spatio-temporal smoothing). Epicardial foci were identified with a median location error ≈16 mm (interquartile range, 9-29 mm). Inverse mapping with meshless method of fundamental solutions was better than with finite/boundary element methods, and the latter were not improved by inclusion of inhomogeneous torso electrical properties.

CONCLUSIONS

Inverse potential mapping provides useful information on the origin and spread of epicardial activation. However the spatio-temporal variability of recovered electrograms limit resolution and must constrain the accuracy with which arrhythmia circuits can be identified independently using this approach.

Machine-readable Yin-Yang imbalance: traditional Chinese medicine syndrome computer modeling based on three-dimensional noninvasive cardiac electrophysiology imaging

OBJECTIVES

The principal diagnostic methods of traditional Chinese medicine (TCM) are inspection, auscultation and olfaction, inquiry, and pulse-taking. Treatment by syndrome differentiation is likely to be subjective. This study was designed to provide a basic theory for TCM diagnosis and establish an objective means of evaluating the correctness of syndrome differentiation.

METHODS

We herein provide the basic theory of TCM syndrome computer modeling based on a noninvasive cardiac electrophysiology imaging technique. Noninvasive cardiac electrophysiology imaging records the heart's electrical activity from hundreds of electrodes on the patient's torso surface and therefore provides much more information than 12-lead electrocardiography. Through mathematical reconstruction algorithm calculations, the reconstructed heart model is a machine-readable description of the underlying mathematical physics model that reveals the detailed three-dimensional (3D) electrophysiological activity of the heart.

RESULTS

From part of the simulation results, the imaged 3D cardiac electrical source provides dynamic information regarding the heart's electrical activity at any given location within the 3D myocardium.

CONCLUSIONS

This noninvasive cardiac electrophysiology imaging method is suitable for translating TCM syndromes into a computable format of the underlying mathematical physics model to offer TCM diagnosis evidence-based standards for ensuring correct evaluation and rigorous, scientific data for demonstrating its efficacy.

Solving the Inverse Problem of Electrocardiography on the Endocardium Using a Single Layer Source

The inverse problem of electrocardiography consists in reconstructing cardiac electrical activity from given body surface electrocardiographic measurements. Despite tremendous progress in the field over the last decades, the solution of this problem in terms of electrical potentials on both epi- and the endocardial heart surfaces with acceptable accuracy remains challenging. This paper presents a novel numerical approach aimed at improving the solution quality on the endocardium. Our method exploits the solution representation in the form of electrical single layer densities on the myocardial surface. We demonstrate that this representation brings twofold benefits: first, the inverse problem can be solved for the physiologically meaningful single layer densities. Secondly, a conventional transfer matrix for electrical potentials can be split into two parts, one of which turned out to posess regularizing properties leading to improved endocardial reconstructions. The method was tested in-silico for ventricular pacings utilizing realistic CT-based heart and torso geometries. The proposed approach provided more accurate solution on the ventricular endocardium compared to the conventional potential-based solutions with Tikhonov regularization of the 0th, 1st, and 2nd orders. Furthermore, we show a uniform spatio-temporal behavior of the single layer densities over the heart surface, which could be conveniently employed in the regularization procedure.

Localization of Activation Origin on Patient-Specific Epicardial Surface by Empirical Bayesian Method

OBJECTIVE

Ablation treatment of ventricular arrhythmias can be facilitated by pre-procedure planning aided by electrocardiographic inverse solution, which can help to localize the origin of arrhythmia. Our aim was to improve localization accuracy of the inverse solution by using a novel Bayesian approach.

METHODS

The inverse problem of electrocardiography was solved by reconstructing epicardial potentials from 120 body-surface electrocardiograms and from patient-specific geometry of the heart and torso for four patients suffering from scar-related ventricular tachycardia who underwent epicardial catheter mapping, which included pace-mapping. Simulations using dipole sources in patient-specific geometry were also performed. The proposed method, using dynamic spatio-temporal a priori constraints of the solution, was compared with classical Tikhonov methods based on fixed constraints.

RESULTS

The mean localization error of the proposed method for all available pacing sites (n=78) was significantly smaller than that achieved by Tikhonov methods; specifically, the localization accuracy for pacing in the normal tissue (n=17) was [Formula: see text] mm (mean ± SD) versus [Formula: see text] mm reported in the previous study using the same clinical data and Tikhonov regularization. Simulation experiments further supported these clinical findings.

CONCLUSION

The promising results of in vivo and in silico experiments presented in this study provide a strong incentive to pursuing further investigation of data-driven Bayesian methods in solving the electrocardiographic inverse problem.

SIGNIFICANCE

The proposed approach to localizing origin of ventricular activation sequence may have important applications in pre-procedure assessment of arrhythmias and in guiding their ablation treatment.

Validation and Opportunities of Electrocardiographic Imaging: From Technical Achievements to Clinical Applications

Electrocardiographic imaging (ECGI) reconstructs the electrical activity of the heart from a dense array of body-surface electrocardiograms and a patient-specific heart-torso geometry. Depending on how it is formulated, ECGI allows the reconstruction of the activation and recovery sequence of the heart, the origin of premature beats or tachycardia, the anchors/hotspots of re-entrant arrhythmias and other electrophysiological quantities of interest. Importantly, these quantities are directly and non-invasively reconstructed in a digitized model of the patient's three-dimensional heart, which has led to clinical interest in ECGI's ability to personalize diagnosis and guide therapy. Despite considerable development over the last decades, validation of ECGI is challenging. Firstly, results depend considerably on implementation choices, which are necessary to deal with ECGI's ill-posed character. Secondly, it is challenging to obtain (invasive) ground truth data of high quality. In this review, we discuss the current status of ECGI validation as well as the major challenges remaining for complete adoption of ECGI in clinical practice. Specifically, showing clinical benefit is essential for the adoption of ECGI. Such benefit may lie in patient outcome improvement, workflow improvement, or cost reduction. Future studies should focus on these aspects to achieve broad adoption of ECGI, but only after the technical challenges have been solved for that specific application/pathology. We propose 'best' practices for technical validation and highlight collaborative efforts recently organized in this field. Continued interaction between engineers, basic scientists, and physicians remains essential to find a hybrid between technical achievements, pathological mechanisms insights, and clinical benefit, to evolve this powerful technique toward a useful role in clinical practice.

Three-Dimensional Noninvasive Imaging of Ventricular Arrhythmias in Patients With Premature Ventricular Contractions

OBJECTIVE

Noninvasive imaging of cardiac electrical activity promises to provide important information regarding the underlying arrhythmic substrates for successful ablation intervention and further understanding of the mechanism of such lethal disease. The aim of this study is to evaluate the performance of a novel 3-D cardiac activation imaging technique to noninvasively localize and image origins of focal ventricular arrhythmias in patients undergoing radio frequency ablation.

METHODS

Preprocedural ECG gated contrast enhanced cardiac CT images and body surface potential maps were collected from 13 patients within a week prior to the ablation. The electrical activation images were estimated over the 3-D myocardium using a cardiac electric sparse imaging technique, and compared with CARTO activation maps and the ablation sites in the same patients.

RESULTS

Noninvasively-imaged activation sequences were consistent with the CARTO mapping results with an average correlation coefficient of 0.79, average relative error of 0.19, and average relative resolution error of 0.017. The imaged initiation sites of premature ventricular contractions (PVCs) were, on average, within 8 mm of the last successful ablation site and within 3 mm of the nearest ablation site.

CONCLUSION

The present results demonstrate the excellent performance of the 3-D cardiac activation imaging technique in imaging the activation sequence associated with PVC, and localizing the initial sites of focal ventricular arrhythmias in patients. These promising results suggest that the 3-D cardiac activation imaging technique may become a useful tool for aiding clinical diagnosis and management of ventricular arrhythmias.

Activation recovery interval imaging of premature ventricular contraction

Dispersion of ventricular repolarization due to abnormal activation contributes to the susceptibility to cardiac arrhythmias. However, the global pattern of repolarization is difficult to assess clinically. Activation recovery interval (ARI) has been used to understand the properties of ventricular repolarization. In this study, we developed an ARI imaging technique to noninvasively reconstruct three-dimensional (3D) ARI maps in 10 premature ventricular contraction (PVC) patients and evaluated the results with the endocardial ARI maps recorded by a clinical navigation system (CARTO). From the analysis results of a total of 100 PVC beats in 10 patients, the average correlation coefficient is 0.86±0.05 and the average relative error is 0.06±0.03. The average localization error is 4.5±2.3 mm between the longest ARI sites in 3D ARI maps and those in CARTO endocardial ARI maps. The present results suggest that ARI imaging could serve as an alternative of evaluating global pattern of ventricular repolarization noninvasively and could assist in the future investigation of the relationship between global repolarization dispersion and the susceptibility to cardiac arrhythmias.

Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs produced by an anisotropic model of the heart

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.

Noninvasive epicardial and endocardial mapping of premature ventricular contractions

Aims

The aim of the present study was to estimate the accuracy of a novel non-invasive epicardial and endocardial electrophysiology system (NEEES) for mapping ectopic ventricular depolarizations.

Methods and results

The study enrolled 20 patients with monomorphic premature ventricular contractions (PVCs) or ventricular tachycardia (VT). All patients underwent pre-procedural computed tomography or magnetic resonance imaging of the heart and torso. Radiographic data were semi-automatically processed by the NEEES to reconstruct a realistic 3D model of the heart and torso. In the electrophysiology laboratory, body-surface electrodes were connected to the NEEES followed by unipolar EKG recordings during episodes of PVC/VT. The body-surface EKG data were processed by the NEEES using its inverse-problem solution software in combination with anatomical data from the heart and torso. The earliest site of activation as denoted on the NEEES 3D heart model was compared with the PVC/VT origin using a 3D electroanatomical mapping system. The site of successful catheter ablation served as final confirmation. A total of 21 PVC/VT morphologies were analysed and ablated. The chamber of interest was correctly diagnosed non-invasively in 20 of 21 (95%) PVC/VT cases. In 18 of the 21 (86%) cases, the correct ventricular segment was diagnosed. Catheter ablation resulted in acute success in 19 of the 20 (95%) patients, whereas 1 patient underwent successful surgical ablation. During 6 months of follow-up, 19 of the 20 (95%) patients were free from recurrence off antiarrhythmic drugs.

Conclusion

The NEEES accurately identified the site of PVC/VT origin. Knowledge of the potential site of the PVC/VT origin may aid the physician in planning a successful ablation strategy.

Localizing the Accessory Pathway in Ventricular Preexcitation Patients Using a Score Based Algorithm

Objectives: Clinical data was analyzed to find an efficient way to localize the accessory pathway in patients with ventricular preexcitation.

Methods: The delta wave morphologies and ablation sites of 186 patients who underwent catheter ablation were analyzed and an algorithm (“locAP”) to localize the accessory pathway was developed from the 84 data sets with a PQ interval ≤ 0.12 s and a QRS width ≥ 0.12 s. Fifty additional patients were included for a prospective validation. The locAP algorithm ranks 13 locations according to the likelihood that the accessory pathway is localized there. The algorithm is based on the locAP score which uses the standardized residuals of the available data sets.

Results: The locAP algorithm’s accuracy is 0.54 for 13 locations, with a sensitivity of 0.84, a specificity of 0.97, and a positive likelihood ratio of 24.94. If the two most likely locations are regarded, the accuracy rises to 0.79, for the three most likely locations combined the accuracy is 0.82. This new algorithm performs better than Milstein’s, Fitzpatrick’s, and Arruda’s algorithm both in the original study population as well as in a prospective study.

Conclusions: The locAP algorithm is a valid and valuable tool for clinical practice in a cardiac electrophysiology laboratory. It could be shown that use of the locAP algorithm is favorable over the localizing algorithms that are in clinical use today.

Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs produced by an anisotropic model of the heart

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.

Limitations and Challenges in Mapping Ventricular Tachycardia: New Technologies and Future Directions

Recurrent episodes of ventricular tachycardia in patients with structural heart disease are associated with increased mortality and morbidity, despite the life-saving benefits of implantable cardiac defibrillators. Reducing implantable cardiac defibrillator therapies is important, as recurrent shocks can cause increased myocardial damage and stunning, despite the conversion of ventricular tachycardia/ventricular fibrillation. Catheter ablation has emerged as a potential therapeutic option either for primary or secondary prevention of these arrhythmias, particularly in post-myocardial infarction cases where the substrate is well defined. However, the outcomes of catheter ablation of ventricular tachycardia in structural heart disease remain unsatisfactory in comparison with other electrophysiological procedures. The disappointing efficacy of ventricular tachycardia ablation in structural heart disease is multifactorial. In this review, we discuss the issues surrounding this and examine the limitations of current mapping approaches, as well as newer technologies that might help address them.

Simultaneous Non-Invasive Epicardial and Endocardial Mapping in Patients With Brugada Syndrome: New Insights Into Arrhythmia Mechanisms

Background

The underlying mechanisms of Brugada syndrome (BrS) are not completely understood. Recent studies provided evidence that the electrophysiological substrate, leading to electrocardiogram abnormalities and/or ventricular arrhythmias, is located in the right ventricular outflow tract (RVOT). The purpose of this study was to examine abnormalities of epicardial and endocardial local unipolar electrograms by simultaneous noninvasive mapping in patients with BrS.

Methods and Results

Local epicardial and endocardial unipolar electrograms were analyzed using a novel noninvasive epi‐ and endocardial electrophysiology system (NEEES) in 12 patients with BrS and 6 with right bundle branch block for comparison. Fifteen normal subjects composed the control group. Observed depolarization abnormalities included fragmented electrograms in the anatomical area of RVOT endocardially and epicardially, significantly prolonged activation time in the RVOT endocardium (65±20 vs 38±13 ms in controls; P=0.008), prolongation of the activation‐recovery interval in the RVOT epicardium (281±34 vs 247±26 ms in controls; P=0.002). Repolarization abnormalities included a larger area of ST‐segment elevation >2 mV and T‐wave inversions. Negative voltage gradient (−2.5 to −6.0 mV) between epicardium and endocardium of the RVOT was observed in 8 of 12 BrS patients, not present in patients with right bundle branch block or in controls.

Conclusions

Abnormalities of epicardial and endocardial electrograms associated with depolarization and repolarization properties were found using NEEES exclusively in the RVOT of BrS patients. These findings support both, depolarization and repolarization abnormalities, being operative at the same time in patients with BrS.

ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone

ECG imaging is an emerging technology for the reconstruction of cardiac electric activity from non-invasively measured body surface potential maps. In this case report, we present the first evaluation of transmurally imaged activation times against endocardially reconstructed isochrones for a case of sustained monomorphic ventricular tachycardia (VT). Computer models of the thorax and whole heart were produced from MR images. A recently published approach was applied to facilitate electrode localization in the catheter laboratory, which allows for the acquisition of body surface potential maps while performing non-contact mapping for the reconstruction of local activation times. ECG imaging was then realized using Tikhonov regularization with spatio-temporal smoothing as proposed by Huiskamp and Greensite and further with the spline-based approach by Erem et al. Activation times were computed from transmurally reconstructed transmembrane voltages. The results showed good qualitative agreement between the non-invasively and invasively reconstructed activation times. Also, low amplitudes in the imaged transmembrane voltages were found to correlate with volumes of scar and grey zone in delayed gadolinium enhancement cardiac MR. The study underlines the ability of ECG imaging to produce activation times of ventricular electric activity-and to represent effects of scar tissue in the imaged transmembrane voltages.

Non-invasive imaging of ventricular activation during pacing and arrhythmia: Methods and validation

Cardiovascular disease continued to be a leading killer world widely. Each year, about 400,000 cases of sudden cardiac arrest are reported in the U.S. alone. Clinically, radio-frequency ablative procedure has become widely applied in the treatment of ventricular arrhythmia. Non-invasive approaches have been demonstrated to be able to provide important information on the arrhythmogenesis and potentially assist in the clinical practice. In this work, we develop and validate a novel temporal sparse based imaging method, Cardiac Electrical Sparse Imaging (CESI). Computer simulation and animal validation results demonstrate that the CESI approach is capable of imaging with improved accuracy and robustness by exploiting the temporal sparse property underlying cellular electrophysiology. Overall, a CC of 0.8, RE of 0.2 and LE (localization error) of 7 mm has been achieved on human realistic simulation and good accuracy has been observed in canine simultaneous mapping studies. Also, the technique maintains full temporal resolution (RRE <; 0.04) in terms of the activation sequence under various disturbances and in various pathologies such as premature ventricular complex and ventricular tachycardia. Our promising results indicate the excellent performance of noninvasive imaging of cardiac activation under various arrhythmias, and its potential for aiding clinical management of lethal ventricular arrhythmia.

On the efficiency and accuracy of the single equivalent moving dipole method to identify sites of cardiac electrical activation

We have proposed an algorithm to guide radiofrequency catheter ablation procedures. This algorithm employs the single equivalent moving dipole (SEMD) to model cardiac electrical activity. The aim of this study is to investigate the optimal time instant during the cardiac cycle as well as the number of beats needed to accurately estimate the location of a pacing site. We have evaluated this algorithm by pacing the ventricular epicardial surface and inversely estimating the locations of pacing electrodes from the recorded body surface potentials. Two pacing electrode arrays were sutured on the right and left ventricular epicardial surfaces in swine. The hearts were paced by the electrodes sequentially at multiple rates (120-220 bpm), and body surface ECG signals from 64 leads were recorded for the SEMD estimation. We evaluated the combined error of the estimated interelectrode distance and SEMD direction at each time instant during the cardiac cycle, and found the error was minimum when the normalized root mean square (RMS n ) value of body surface ECG signals reached 15 % of its maximum value. The beat-to-beat variation of the SEMD locations was significantly reduced (p < 0.001) when estimated at 15 % RMS n compared to the earliest activation time (EAT). In addition, the 5-95 % interval of the estimated interelectrode distance error decreased exponentially as the number of beats used to estimate a median beat increased. When the number of beats was 4 or larger, the 5-95 % interval was smaller than 3.5 mm (the diameter of a commonly used catheter). In conclusion, the optimal time for the SEMD estimation is at 15 % of RMS n , and at that time instant a median beat estimated from 4 beats is associated with a beat-to-beat variability of the SEMD location that is appropriate for catheter ablation procedures.

How computer simulations of the human heart can improve anti-arrhythmia therapy

Over the last decade, the state-of-the-art in cardiac computational modelling has progressed rapidly. The electrophysiological function of the heart can now be simulated with a high degree of detail and accuracy, opening the doors for simulation-guided approaches to anti-arrhythmic drug development and patient-specific therapeutic interventions. In this review, we outline the basic methodology for cardiac modelling, which has been developed and validated over decades of research. In addition, we present several recent examples of how computational models of the human heart have been used to address current clinical problems in cardiac electrophysiology. We will explore the use of simulations to improve anti-arrhythmic pacing and defibrillation interventions; to predict optimal sites for clinical ablation procedures; and to aid in the understanding and selection of arrhythmia risk markers. Together, these studies illustrate how the tremendous advances in cardiac modelling are poised to revolutionize medical treatment and prevention of arrhythmia.

Introduction to noninvasive cardiac mapping

From the dawn of the twentieth century, the electrocardiogram (ECG) has revolutionized the way clinical cardiology has been practiced, and it has become the cornerstone of modern medicine today. Driven by clinical and research needs for a more precise understanding of cardiac electrophysiology beyond traditional ECG, inverse solution electrocardiography has been developed, tested, and validated. This article outlines the important progress from ECG development, through more extensive measurement of body surface potentials, and the fundamental leap to solving the inverse problem of electrocardiography, with a focus on mathematical methods and experimental validation.

Temporal Sparse Promoting Three Dimensional Imaging of Cardiac Activation

A new Cardiac Electrical Sparse Imaging (CESI) technique is proposed to image cardiac activation throughout the three-dimensional myocardium from body surface electrocardiogram (ECG) with the aid of individualized heart-torso geometry. The sparse property of cardiac electrical activity in the time domain is utilized in the temporal sparse promoting inverse solution, one formulated to achieve higher spatial-temporal resolution, stronger robustness and thus enhanced capability in imaging cardiac electrical activity. Computer simulations were carried out to evaluate the performance of this imaging method under various circumstances. A total of 12 single site pacing and 7 dual sites pacing simulations with artificial and the hospital recorded sensor noise were used to evaluate the accuracy and stability of the proposed method. Simulations with modeling error on heart-torso geometry and electrode-torso registration were also performed to evaluate the robustness of the technique. In addition to the computer simulations, the CESI algorithm was further evaluated using experimental data in an animal model where the noninvasively imaged activation sequences were compared with those measured with simultaneous intracardiac mapping. All of the CESI results were compared with conventional weighted minimum norm solutions. The present results show that CESI can image with better accuracy, stability and stronger robustness in both simulated and experimental circumstances. In sum, we have proposed a novel method for cardiac activation imaging, and our results suggest that the CESI has enhanced performance, and offers the potential to image the cardiac activation and to assist in the clinical management of ventricular arrhythmias.

Non-invasive focus localization, right ventricular epicardial potential mapping in patients with an MRI-conditional pacemaker system - a pilot study

Background

With the advent of magnetic resonance imaging (MRI) conditional pacemaker systems, the possibility of performing MRI in pacemaker patients has been introduced. Besides for the detailed evaluation of atrial and ventricular volumes and function, MRI can be used in combination with body surface potential mapping (BSPM) in a non-invasive inverse potential mapping (IPM) strategy. In non-invasive IPM, epicardial potentials are reconstructed from recorded body surface potentials (BSP). In order to investigate whether an IPM method with a limited number of electrodes could be used for the purpose of non-invasive focus localization, it was applied in patients with implanted pacing devices. Ventricular paced beats were used to simulate ventricular ectopic foci.

Methods

Ten patients with an MRI-conditional pacemaker system and a structurally normal heart were studied. Patient-specific 3D thorax volume models were reconstructed from the MRI images. BSP were recorded during ventricular pacing. Epicardial potentials were inversely calculated from the BSP. The site of epicardial breakthrough was compared to the position of the ventricular lead tip on MRI and the distance between these points was determined.

Results

For all patients, the site of earliest epicardial depolarization could be identified. When the tip of the pacing lead was implanted in vicinity to the epicardium, i.e. right ventricular (RV) apex or RV outflow tract, the distance between lead tip position and epicardial breakthrough was 6.0 ± 1.9 mm.

Conclusions

In conclusion, the combined MRI and IPM method is clinically applicable and can identify sites of earliest depolarization with a clinically useful accuracy.

Electronic supplementary material

The online version of this article (doi:10.1007/s10840-015-0054-9) contains supplementary material, which is available to authorized users.

Noninvasive reconstruction of cardiac electrical activity: update on current methods, applications and challenges

Electrical activity at the level of the heart muscle can be noninvasively reconstructed from body-surface electrocardiograms (ECGs) and patient-specific torso-heart geometry. This modality, coined electrocardiographic imaging, could fill the gap between the noninvasive (low-resolution) 12-lead ECG and invasive (high-resolution) electrophysiology studies. Much progress has been made to establish electrocardiographic imaging, and clinical studies appear with increasing frequency. However, many assumptions and model choices are involved in its execution, and only limited validation has been performed. In this article, we will discuss the technical details, clinical applications and current limitations of commonly used methods in electrocardiographic imaging. It is important for clinicians to realise the influence of certain assumptions and model choices for correct and careful interpretation of the results. This, in combination with more extensive validation, will allow for exploitation of the full potential of noninvasive electrocardiographic imaging as a powerful clinical tool to expedite diagnosis, guide therapy and improve risk stratification.

Forward problem of electrocardiography: is it solved?

BACKGROUND

The relationship between epicardial and body surface potentials defines the forward problem of electrocardiography. A robust formulation of the forward problem is instrumental to solving the inverse problem, in which epicardial potentials are computed from known body surface potentials. Here, the accuracy of different forward models has been evaluated experimentally.

METHODS AND RESULTS

Body surface and epicardial potentials were recorded simultaneously in anesthetized closed-chest pigs (n=5) during sinus rhythm, and epicardial and endocardial ventricular pacing (65 records in total). Body surface potentials were simulated from epicardial recordings using experiment-specific volume conductor models constructed from magnetic resonance imaging. Results for homogeneous (isotropic electric properties) and inhomogeneous (incorporating lungs, anisotropic skeletal muscle, and subcutaneous fat) forward models were compared with measured body surface potentials. Correlation coefficients were 0.85±0.08 across all animals and activation sequences with no significant difference between homogeneous and inhomogeneous solutions (P=0.85). Despite this, there was considerable variance between simulated and measured body surface potential distributions. Differences between the body surface potential extrema predicted with homogeneous forward models were 55% to 78% greater than observed (P<0.05) and attenuation of potentials adjacent to extrema were 10% to 171% greater (P<0.03). The length and orientation of the vector between potential extrema were also significantly different. Inclusion of inhomogeneous electric properties in the forward model reduced, but did not eliminate these differences.

CONCLUSIONS

These results demonstrate that homogeneous volume conductor models introduce substantial spatial inaccuracies in forward problem solutions. This probably affects the precision of inverse reconstructions of cardiac potentials, in which this assumption is made.

Noninvasive diagnostic mapping of supraventricular arrhythmias (Wolf-Parkinson-White syndrome and atrial arrhythmias)

The 12-lead electrocardiogram has limited value in precisely identifying the origin of focal or critical component of reentrant arrhythmias during supraventricular arrhythmias, as well as precisely locating accessory atrioventricular conduction pathways. Because of these limitations, efforts have been made to reconstruct epicardial activation sequences from body surface measurements obtained noninvasively. The last decade has registered significant progress in obtaining clinically useful data from the attempts to noninvasively map the epicardial electrical activity. This article summarizes the recent advances made in this area, specifically addressing the clinical outcomes of such efforts relating to atrial arrhythmias and Wolf-Parkinson-White syndrome.

Investigations of sensitivity and resolution of ECG and MCG in a realistically shaped thorax model

Solving the inverse problem of electrocardiography (ECG) and magnetocardiography (MCG) is often referred to as cardiac source imaging. Spatial properties of ECG and MCG as imaging systems are, however, not well known. In this modelling study, we investigate the sensitivity and point-spread function (PSF) of ECG, MCG, and combined ECG+MCG as a function of source position and orientation, globally around the ventricles: signal topographies are modelled using a realistically-shaped volume conductor model, and the inverse problem is solved using a distributed source model and linear source estimation with minimal use of prior information. The results show that the sensitivity depends not only on the modality but also on the location and orientation of the source and that the sensitivity distribution is clearly reflected in the PSF. MCG can better characterize tangential anterior sources (with respect to the heart surface), while ECG excels with normally-oriented and posterior sources. Compared to either modality used alone, the sensitivity of combined ECG+MCG is less dependent on source orientation per source location, leading to better source estimates. Thus, for maximal sensitivity and optimal source estimation, the electric and magnetic measurements should be combined.

Cardiac electrophysiological activation pattern estimation from images using a patient-specific database of synthetic image sequences

While abnormal patterns of cardiac electrophysiological activation are at the origin of important cardiovascular diseases (e.g., arrhythmia, asynchrony), the only clinically available method to observe detailed left ventricular endocardial surface activation pattern is through invasive catheter mapping. However, this electrophysiological activation controls the onset of the mechanical contraction; therefore, important information about the electrophysiology could be deduced from the detailed observation of the resulting motion patterns. In this paper, we present the study of this inverse cardiac electrokinematic relationship. The objective is to predict the activation pattern knowing the cardiac motion from the analysis of cardiac image sequences. To achieve this, we propose to create a rich patient-specific database of synthetic time series of the cardiac images using simulations of a personalized cardiac electromechanical model, in order to study this complex relationship between electrical activity and kinematic patterns in the context of this specific patient. We use this database to train a machine-learning algorithm which estimates the depolarization times of each cardiac segment from global and regional kinematic descriptors based on displacements or strains and their derivatives. Finally, we use this learning to estimate the patient’s electrical activation times using the acquired clinical images. Experiments on the inverse electrokinematic learning are demonstrated on synthetic sequences and are evaluated on clinical data with promising results. The error calculated between our prediction and the invasive intracardiac mapping ground truth is relatively small (around 10 ms for ischemic patients and 20 ms for nonischemic patient). This approach suggests the possibility of noninvasive electrophysiological pattern estimation using cardiac motion imaging.

Patient-specific modeling of ventricular activation pattern using surface ECG-derived vectorcardiogram in bundle branch block

Patient-specific computational models have promise to improve cardiac disease diagnosis and therapy planning. Here a new method is described to simulate left-bundle branch block (LBBB) and RV-paced ventricular activation patterns in three dimensions from non-invasive, routine clinical measurements. Activation patterns were estimated in three patients using vectorcardiograms (VCG) derived from standard 12-lead electrocardiograms (ECG). Parameters of a monodomain model of biventricular electrophysiology were optimized to minimize differences between the measured and computed VCG. Electroanatomic maps of local activation times measured on the LV and RV endocardial surfaces of the same patients were used to validate the simulated activation patterns. For all patients, the optimal estimated model parameters predicted a time-averaged mean activation dipole orientation within 6.7 ± 0.6° of the derived VCG. The predicted local activation times agreed within 11.5 ± 0.8 ms of the measured electroanatomic maps, on the order of the measurement accuracy.

A method to noninvasively identify cardiac bioelectrical sources

BACKGROUND

We have introduced a method to guide radiofrequency catheter ablation (RCA) procedures that estimates the location of a catheter tip used to pace the ventricles and the target site for ablation using the single equivalent moving dipole (SEMD).

OBJECTIVE

To investigate the accuracy of this method in resolving epicardial and endocardial electrical sources.

METHODS

Two electrode arrays, each of nine pacing electrodes at known distances from each other, sutured on the left- and right-ventricular (LV and RV) epicardial surfaces of swine, were used to pace the heart at multiple rates, while body surface potentials from 64 sites were recorded and used to estimate the SEMD location. A similar approach was followed for pacing from catheters in the LV and RV.

RESULTS

The overall (RV & LV) error in estimating the interelectrode distance of adjacent epicardial electrodes was 0.38 ± 0.45 cm. The overall endocardial (RV & LV) interelectrode distance error, was 0.44 ± 0.26 cm. Heart rate did not significantly affect the error of the estimated SEMD location (P > 0.05). The guiding process error became progressively smaller as the SEMD approached an epicardial target site and close to the target, the overall absolute error was ∼ 0.28 cm. The estimated epicardial SEMD locations preserved their topology in image space with respect to their corresponding physical location of the epicardial electrodes.

CONCLUSION

The proposed algorithm suggests one can efficiently and accurately resolve epicardial electrical sources without the need of an imaging modality. In addition, the error in resolving these sources is sufficient to guide RCA procedures.

Comparison of minimum-norm estimation and beamforming in electrocardiography with acute ischemia

In the electrocardiographic (ECG) inverse problem, the electrical activity of the heart is estimated from measured electrocardiogram. A model of thorax conductivities and a model of the cardiac generator is required for the ECG inverse problem. Limitations and errors in methods, models, and data will lead to errors in the estimates. However, in experimental applications, the use of limited or erroneous models is often inevitable due to necessary model simplifications and the difficulty of obtaining accurate 3D anatomical imaging data. In this work, we focus on two methods for solving the inverse problem of ECG in the case of acute ischemia: minimum-norm (MN) estimation and linearly constrained minimum-variance beamforming. We study how these methods perform with different sizes of ischemia and with erroneous conductivity models. The results indicate that the beamformer can localize small ischemia given an accurate model, but it cannot be used for estimating the size of ischemia. The MN estimator is tolerant to geometry errors and excels in estimating the size of ischemia, although the beamformer performs better with accurate model and small ischemia.

Noninvasive imaging of cardiac excitation: current status and future perspective

Noninvasive imaging of cardiac excitation using body surface potential mapping (BSPM) data and inverse procedures is an emerging technique that enables estimation of myocardial depolarization and repolarization. Despite numerous reports on the possible advantages of this imaging technique, it has not yet advanced into daily clinical practice. This is mainly due to the time consuming nature of data acquisition and the complexity of the mathematics underlying the used inverse procedures. However, the popularity of this field of research has increased and noninvasive imaging of cardiac electrophysiology is considered a promising tool to complement conventional invasive electrophysiological studies. Furthermore, the use of appropriately designed electrode vests and more advanced computers has greatly reduced the procedural time. This review provides descriptive overview of the research performed thus far and the possible future directions. The general challenges in routine application of BSPM and inverse procedures are discussed. In addition, individual properties of the biophysical models underlying the inverse procedures are illustrated.

Catheter ablation for ventricular tachycardia: indications and techniques

Ventricular tachycardia (VT) may be secondary to many different underlying pathophysiologies. The nature of the underlying disorder determines amenability to catheter ablation, thus, dictating the circumstances under which it should be undertaken. The differing substrates also influence the choice of techniques that are used. The most intensively studied clinical subgroup of VT is re-entrant VT in the setting of ischemic heart disease. The approach to ablation in such patients is discussed in detail. Subsequent discussion focuses on other clinically encountered varieties of VT and the ablation methods used in each individual disease state.

Noninvasive electrocardiographic imaging of arrhythmogenic substrates in humans

Cardiac excitation is determined by interactions between the source of electric activation (membrane depolarization) and the load that cardiac tissue presents. This relationship is altered in pathology by remodeling processes that often create a substrate favoring the development of cardiac arrhythmias. Most studies of arrhythmia mechanisms and arrhythmogenic substrates have been conducted in animal models, which may differ in important ways from the human pathologies they are designed to represent. Electrocardiographic imaging is a noninvasive method for mapping the electric activity of the heart in humans in real-world conditions. This review summarizes results from electrocardiographic imaging studies of arrhythmogenic substrates associated with human clinical arrhythmias. Examples include heart failure, myocardial infarction scar, atrial fibrillation, and abnormal ventricular repolarization.

Placement of implantable cardioverter-defibrillators in paediatric and congenital heart defect patients: a pipeline for model generation and simulation prediction of optimal configurations

There is currently no reliable way of predicting the optimal implantable cardioverter-defibrillator (ICD) placement in paediatric and congenital heart defect (CHD) patients. This study aimed to: (1) develop a new image processing pipeline for constructing patient-specific heart-torso models from clinical magnetic resonance images (MRIs); (2) use the pipeline to determine the optimal ICD configuration in a paediatric tricuspid valve atresia patient; (3) establish whether the widely used criterion of shock-induced extracellular potential (Φe) gradients ≥5 V cm(-1) in ≥95% of ventricular volume predicts defibrillation success. A biophysically detailed heart-torso model was generated from patient MRIs. Because transvenous access was impossible, three subcutaneous and three epicardial lead placement sites were identified along with five ICD scan locations. Ventricular fibrillation was induced, and defibrillation shocks were applied from 11 ICD configurations to determine defibrillation thresholds (DFTs). Two configurations with epicardial leads resulted in the lowest DFTs overall and were thus considered optimal. Three configurations shared the lowest DFT among subcutaneous lead ICDs. The Φe gradient criterion was an inadequate predictor of defibrillation success, as defibrillation failed in numerous instances even when 100% of the myocardium experienced such gradients. In conclusion, we have developed a new image processing pipeline and applied it to a CHD patient to construct the first active heart-torso model from clinical MRIs.

Usefulness of ventricular endocardial electric reconstruction from body surface potential maps to noninvasively localize ventricular ectopic activity in patients

As radio frequency (RF) catheter ablation becomes increasingly prevalent in the management of ventricular arrhythmia in patients, an accurate and rapid determination of the arrhythmogenic site is of important clinical interest. The aim of this study was to test the hypothesis that the inversely reconstructed ventricular endocardial current density distribution from body surface potential maps (BSPMs) can localize the regions critical for maintenance of a ventricular ectopic activity. Patients with isolated and monomorphic premature ventricular contractions (PVCs) were investigated by noninvasive BSPMs and subsequent invasive catheter mapping and ablation. Equivalent current density (CD) reconstruction (CDR) during symptomatic PVCs was obtained on the endocardial ventricular surface in six patients (four men, two women, years 23-77), and the origin of the spontaneous ectopic activity was localized at the location of the maximum CD value. Compared with the last (successful) ablation site (LAS), the mean and standard deviation of localization error of the CDR approach were 13.8 and 1.3 mm, respectively. In comparison, the distance between the LASs and the estimated locations of an equivalent single moving dipole in the heart was 25.5 ± 5.5 mm. The obtained CD distribution of activated sources extending from the catheter ablation site also showed a high consistency with the invasively recorded electroanatomical maps. The noninvasively reconstructed endocardial CD distribution is suitable to predict a region of interest containing or close to arrhythmia source, which may have the potential to guide RF catheter ablation.

Computational cardiology: how computer simulations could be used to develop new therapies and advance existing ones

This article reviews the latest developments in computational cardiology. It focuses on the contribution of cardiac modelling to the development of new therapies as well as the advancement of existing ones for cardiac arrhythmias and pump dysfunction. Reviewed are cardiac modelling efforts aimed at advancing and optimizing existent therapies for cardiac disease (defibrillation, ablation of ventricular tachycardia, and cardiac resynchronization therapy) and at suggesting novel treatments, including novel molecular targets, as well as efforts to use cardiac models in stratification of patients likely to benefit from a given therapy, and the use of models in diagnostic procedures.

Computational cardiology: the heart of the matter

This paper reviews the newest developments in computational cardiology. It focuses on the contribution of cardiac modeling to the development of new therapies as well as the advancement of existing ones for cardiac arrhythmias and pump dysfunction. Reviewed are cardiac modeling efforts aimed at advancing and optimizing existent therapies for cardiac disease (defibrillation, ablation of ventricular tachycardia, and cardiac resynchronization therapy) and at suggesting novel treatments, including novel molecular targets, as well as efforts to use cardiac models in stratification of patients likely to benefit from a given therapy, and the use of models in diagnostic procedures.