Non-invasive localization of the ventricular excitation origin without patient-specific geometries using deep learning.

Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categorized as sudden cardiac death, which can be related to ventricular tachycardia (VT). This type of arrhythmia can be caused by focal activation sources outside the sinus node. Catheter ablation of these foci is a curative treatment in order to inactivate the abnormal triggering activity. However, the localization procedure is usually time-consuming and requires an invasive procedure in the catheter lab. To facilitate and expedite the treatment, we present two novel localization support techniques based on convolutional neural networks (CNNs) that address these clinical needs. In contrast to existing methods, our approaches were designed to be independent of the patient-specific geometry and directly applicable to surface ECG signals, while also delivering a binary transmural position. Moreover, one of the method's outputs can be interpreted as several ranked solutions. The CNNs were trained on a dataset containing only simulated data and evaluated both on simulated test data and clinical data. On a novel large and open simulated dataset, the median test error was below 3 mm. The median localization error on the unseen clinical data ranged from 32 mm to 41 mm without optimizing the pre-processing and CNN to the clinical data. Interpreting the output of one of the approaches as ranked solutions, the best median error of the top-3 solutions decreased to 20 mm on the clinical data. The transmural position was correctly detected in up to 82% of all clinical cases. These results demonstrate a proof of principle to utilize CNNs to localize the activation source without the intrinsic need for patient-specific geometrical information. Furthermore, providing multiple solutions can assist physicians in identifying the true activation source amongst more than one possible location. With further optimization to clinical data, these methods have high potential to accelerate clinical interventions, replace certain steps within these procedures and consequently reduce procedural risk and improve VT patient outcomes.

Cobiveco: Consistent biventricular coordinates for precise and intuitive description of position in the heart - with MATLAB implementation.

Ventricular coordinates are widely used as a versatile tool for various applications that benefit from a description of local position within the heart. However, the practical usefulness of ventricular coordinates is determined by their ability to meet application-specific requirements. For regression-based estimation of biventricular position, for example, a symmetric definition of coordinate directions in both ventricles is important. For the transfer of data between different hearts as another use case, the consistency of coordinate values across different geometries is particularly relevant. To meet these requirements, we compare different approaches to compute coordinates and present Cobiveco, a symmetric, consistent and intuitive biventricular coordinate system that builds upon existing coordinate systems, but overcomes some of their limitations. A novel one-way transfer error is introduced to assess the consistency of the coordinates. Normalized distances along bijective trajectories between two boundaries were found to be superior to solutions of Laplace's equation for defining coordinate values, as they show better linearity in space. Evaluation of transfer and linearity errors on 36 patient geometries revealed a more than 4-fold improvement compared to a state-of-the-art method. Finally, we show two application examples underlining the relevance for cardiac data processing. Cobiveco MATLAB code is available under a permissive open-source license.

His-Optimized Cardiac Resynchronization Therapy With Ventricular Fusion Pacing for Electrical Resynchronization in Heart Failure.

OBJECTIVES: This study sought to evaluate the effectiveness of His-optimized cardiac resynchronization therapy (HOT-CRT) for reducing left ventricular activation time (LVAT) compared to His bundle pacing (HBP) and biventricular (BiV) pacing (including multipoint pacing [MPP]), using electrocardiographic (ECG) imaging. BACKGROUND: HBP may correct bundle branch block (BBB) and has shown encouraging results for providing CRT. However, HBP does not correct BBB in all patients and may be combined with univentricular or BiV fusion pacing to deliver HOT-CRT to maximize resynchronization. METHODS: Nineteen patients with a standard indication for CRT, implanted with HBP without correction of BBB and BiV (n = 14) or right ventricular (n = 5) leads, were prospectively enrolled. Patients underwent ECG imaging while pacing in different configurations using different LV electrodes and at different HBP ventricular pacing (VP) delays. The primary endpoint was reduction in LVAT with HOT-CRT, and the secondary endpoints included various other dys-synchrony measurements including right ventricular activation time (RVAT). RESULTS: Compared to HBP, HOT-CRT reduced LVAT by 21% (-17 ms [95% confidence interval [CI]: -25 to -9 ms]; p < 0.001) and outperformed BiV by 24% (-22 ms [95% CI: -33 to -10 ms]; p = 0.002) and MPP by 13% (-11 ms [95% CI: -21 to -1 ms]; p = 0.035). Relative to HBP, HOT-CRT also reduced RVAT by 7% (-5 ms [95% CI: -9 to -1 ms; p = 0.035) in patients with right BBB, whereas RVAT was increased by BiV. The other electrical dyssynchrony measurements also improved with HOT-CRT. CONCLUSIONS: HOT-CRT acutely improves ventricular electrical synchrony beyond BiV and MPP. The impact of this finding needs to be evaluated further in studies with clinical follow-up. (Electrical Resynchronization and Acute Hemodynamic Effects of Direct His Bundle Pacing Compared to Biventricular Pacing; NCT03452462).

Combination of lead-field theory with cardiac vector direction: ECG imaging of septal ventricular activation.

BACKGROUND: Despite the tremendous progress recently reported in ECG imaging (ECGI), some fundamental challenges are still hindering this non-invasive technology from meeting rising clinical expectations. In the present work, we address one of the major ECGI shortcomings in reconstruction of ventricular activation - the limited accuracy of endocardial and particularly septal mapping. METHODS: Ten CRT patients (five female, median (min-max) age - 61 (27-78) years) with previously implanted CRT devices underwent ECGI with isolated right ventricular (RV) pacing. In eight patients, the RV pacemaker lead was placed in the middle septal area of the posterior RV wall. Two subjects had a pacing lead in the anteroseptal apical segment, two at septal RVOT, two at septal junction with posterior wall and six in anterolateral segments. Lead positions were exactly known from CT scans, making the respective paced ECG sequences ideal for validation of ECGI endocardial accuracy. Non-invasive mapping was performed for single RV paced beats using original parameters of the CRT device. For non-invasive estimation of the focal origins, we considered the lead-field based fastest route algorithm (FRA) and its combination with the cardiac vector fit (FRA-V). Furthermore, we extended the resulting combined map by incorporating cardiac activation direction (FRA-V-D) provided by the cardiac dipole. RESULTS: The median (min-max) localization errors were 14 mm (7-27), 9 mm (7-28) and 11 mm (8-24) for FRA, FRA-V and FRA-V-D, respectively. Notably, in all cases at least one of the considered ECGI methods was able to correctly localize the found excitation origin on the endocardium. CONCLUSIONS: This preliminary study investigates combination of the rule-based fastest route algorithm with cardiac vector fit and direction for non-invasive imaging of septal ventricular sources. The developed ECGI methodology delivers reasonable reconstruction accuracy with the 10 mm median localization error. These findings suggest potential use of ECGI for challenging clinical cases, where catheter access to the correct cardiac anatomical region plays a crucial role in the execution of the electrophysiological procedure.

ECG Adapted Fastest Route Algorithm to Localize the Ectopic Excitation Origin in CRT Patients.

Although model-based solution strategies for the ECGI were reported to deliver promising clinical results, they strongly rely on some a priori assumptions, which do not hold true for many pathological cases. The fastest route algorithm (FRA) is a well-established method for noninvasive imaging of ectopic activities. It generates test activation sequences on the heart and compares the corresponding test body surface potential maps (BSPMs) to the measured ones. The test excitation propagation patterns are constructed under the assumption of a global conduction velocity in the heart, which is violated in the cardiac resynchronization (CRT) patients suffering from conduction disturbances. In the present work, we propose to apply dynamic time warping (DTW) to the test and measured ECGs before measuring their similarity. The warping step is a non-linear pattern matching that compensates for local delays in the temporal sequences, thus accounting for the inhomogeneous excitation propagation, while aligning them in an optimal way with respect to a distance function. To evaluate benefits of the temporal warping for FRA-based BSPMs, we considered three scenarios. In the first setting, a simplified simulation example was constructed to illustrate the temporal warping and display the resulting distance map. Then, we applied the proposed method to eight BSPMs produced by realistic ectopic activation sequences and compared its performance to FRA. Finally, we assessed localization accuracy of both techniques in ten CRT patients. For each patient, we noninvasively imaged two paced ECGs: from left and right ventricular implanted leads. In all scenarios, FRA-DTW outperformed FRA in terms of LEs. For the clinical cases, the median (25-75% range) distance errors were reduced from 16 (8-23)mm to 5 (2-10)mm for all pacings, from 15 (11-25)mm to 8 (3-13)mm in the left, and from 19 (6-23)mm to 4 (2-8)mm in the right ventricle, respectively. The obtained results suggest the ability of temporal ECG warping to compensate for an inhomogeneous conduction profile, while retaining computational efficiency intrinsic to FRA.

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.

Using a Spatio-Temporal Basis for ECG Imaging of Ventricular Pacings: Insights From Simulations and First Application to Clinical Data.

ECG imaging estimates the cardiac electrical activity from body surface potentials. As this involves solving a severly ill-posed problem, additional information is required to get a unique and stable solution. Recent progress is based on introducing more problem-specific information by exploiting the structure of cardiac excitation. However, added information must be either certain or general enough to not impair the solution. We have recently developed a method that uses a spatio-temporal basis to restrict the solution space. In the present work, we analyzed this method with respect to one of the most fundamental assumptions made during basis creation: cardiac (an)isotropy. We tested the reconstruction using simulations of ventricular pacings and then applied it to clinical data. In simulations, the overall median localization error was smallest with a basis including fiber orientation. For the clinical data, however, the overall error was smallest with an isotropic basis. This observation suggests that modeling priors should be introduced with care, whereby further work is needed.

ECGI in atrial fibrillation: A clinician's wish list.

Have we a challenge of credibility in the invasive treatment of atrial fibrillation (AFIB)? The incidence of AFIB in the European Union (EU) is about 600,000 cases per year, while only 100,000 get an invasive treatment with a failure rate of close to 40%. Those that remain in AFIB need two times more hospitalizations and three times more re-hospitalizations. AFIB accounts for over 1% of the EU health care costs. Too many patients are not referred and the indication rates of cardiac ablation are inexplicably variable throughout the EU. A reflection is made on how electrocardiographic imaging (ECGI) can contribute to bringing the therapy to an advanced level by achieving a higher success rate, efficiently increasing access to ablation therapies, a better patient selection and therapy planning, personalization and follow up.

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.

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.

Influence of Modeling Errors on the Initial Estimate for Nonlinear Myocardial Activation Times Imaging Calculated With Fastest Route Algorithm.

Noninvasive reconstruction of cardiac electrical activity has a great potential to support clinical decision making, planning, and treatment. Recently, significant progress has been made in the estimation of the cardiac activation from body surface potential maps (BSPMs) using boundary element method (BEM) with the equivalent double layer (EDL) as a source model. In this formulation, noninvasive assessment of activation times results in a nonlinear optimization problem with an initial estimate calculated with the fastest route algorithm (FRA). Each FRA-simulated activation sequence is converted into the ECG. The best initialization is determined by the sequence providing the highest correlation between predicted and measured potentials. We quantitatively assess the effects of the forward modeling errors on the FRA-based initialization. We present three simulation setups to investigate the effects of volume conductor model simplifications, neglecting the cardiac anisotropy and geometrical errors on the localization of ectopic beats starting on the ventricular surface. For the analysis, 12-lead ECG and 99 electrodes BSPM system were used. The areas in the heart exposing the largest localization errors were volume conductor model and electrode configuration specific with an average error <10 mm. The results show the robustness of the FRA-based initialization with respect to the considered modeling errors.

The Consortium for Electrocardiographic Imaging.

Electrocardiographic imaging (ECGI) has recently gained attention as a viable diagnostic tool for reconstructing cardiac electrical activity in normal hearts as well as in cardiac arrhythmias. However, progress has been limited by the lack of both standards and unbiased comparisons of approaches and techniques across the community, as well as the consequent difficulty of effective collaboration across research groups.. To address these limitations, we created the Consortium for Electrocardiographic Imaging (CEI), with the objective of facilitating collaboration across the research community in ECGI and creating standards for comparisons and reproducibility. Here we introduce CEI and describe its two main efforts, the creation of EDGAR, a public data repository, and the organization of three collaborative workgroups that address key components and applications in ECGI. Both EDGAR and the workgroups will facilitate the sharing of ideas, data and methods across the ECGI community and thus address the current lack of reproducibility, broad collaboration, and unbiased comparisons.

Experimental Data and Geometric Analysis Repository-EDGAR.

INTRODUCTION: The "Experimental Data and Geometric Analysis Repository", or EDGAR is an Internet-based archive of curated data that are freely distributed to the international research community for the application and validation of electrocardiographic imaging (ECGI) techniques. The EDGAR project is a collaborative effort by the Consortium for ECG Imaging (CEI, ecg-imaging.org), and focused on two specific aims. One aim is to host an online repository that provides access to a wide spectrum of data, and the second aim is to provide a standard information format for the exchange of these diverse datasets. METHODS: The EDGAR system is composed of two interrelated components: 1) a metadata model, which includes a set of descriptive parameters and information, time signals from both the cardiac source and body-surface, and extensive geometric information, including images, geometric models, and measure locations used during the data acquisition/generation; and 2) a web interface. This web interface provides efficient, search, browsing, and retrieval of data from the repository. RESULTS: An aggregation of experimental, clinical and simulation data from various centers is being made available through the EDGAR project including experimental data from animal studies provided by the University of Utah (USA), clinical data from multiple human subjects provided by the Charles University Hospital (Czech Republic), and computer simulation data provided by the Karlsruhe Institute of Technology (Germany). CONCLUSIONS: It is our hope that EDGAR will serve as a communal forum for sharing and distribution of cardiac electrophysiology data and geometric models for use in ECGI research.

Automatic camera-based identification and 3-D reconstruction of electrode positions in electrocardiographic imaging.

Electrocardiographic imaging (ECG imaging) is a method to depict electrophysiological processes in the heart. It is an emerging technology with the potential of making the therapy of cardiac arrhythmia less invasive, less expensive, and more precise. A major challenge for integrating the method into clinical workflow is the seamless and correct identification and localization of electrodes on the thorax and their assignment to recorded channels. This work proposes a camera-based system, which can localize all electrode positions at once and to an accuracy of approximately 1 ± 1 mm. A system for automatic identification of individual electrodes is implemented that overcomes the need of manual annotation. For this purpose, a system of markers is suggested, which facilitates a precise localization to subpixel accuracy and robust identification using an error-correcting code. The accuracy of the presented system in identifying and localizing electrodes is validated in a phantom study. Its overall capability is demonstrated in a clinical scenario.

Binary optimization for source localization in the inverse problem of ECG.

The goal of ECG-imaging (ECGI) is to reconstruct heart electrical activity from body surface potential maps. The problem is ill-posed, which means that it is extremely sensitive to measurement and modeling errors. The most commonly used method to tackle this obstacle is Tikhonov regularization, which consists in converting the original problem into a well-posed one by adding a penalty term. The method, despite all its practical advantages, has however a serious drawback: The obtained solution is often over-smoothed, which can hinder precise clinical diagnosis and treatment planning. In this paper, we apply a binary optimization approach to the transmembrane voltage (TMV)-based problem. For this, we assume the TMV to take two possible values according to a heart abnormality under consideration. In this work, we investigate the localization of simulated ischemic areas and ectopic foci and one clinical infarction case. This affects only the choice of the binary values, while the core of the algorithms remains the same, making the approximation easily adjustable to the application needs. Two methods, a hybrid metaheuristic approach and the difference of convex functions (DC), algorithm were tested. For this purpose, we performed realistic heart simulations for a complex thorax model and applied the proposed techniques to the obtained ECG signals. Both methods enabled localization of the areas of interest, hence showing their potential for application in ECGI. For the metaheuristic algorithm, it was necessary to subdivide the heart into regions in order to obtain a stable solution unsusceptible to the errors, while the analytical DC scheme can be efficiently applied for higher dimensional problems. With the DC method, we also successfully reconstructed the activation pattern and origin of a simulated extrasystole. In addition, the DC algorithm enables iterative adjustment of binary values ensuring robust performance.