A new method for myocardial activation imaging

Reducing Line-of-block Artifacts in Cardiac Activation Maps Estimated Using ECG Imaging: A Comparison of Source Models and Estimation Methods

OBJECTIVE

To investigate cardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoBs.

METHODS

Body surface potentials were computed for 137 simulated ventricular excitations. Subsequently, the inverse problem was solved to obtain extracellular potentials (EP) and transmembrane voltages (TMV). From these, activation times (AT) were estimated using four methods and compared to the ground truth. This process was evaluated with two cardiac mesh resolutions. Factors contributing to LoB artifacts were identified by analyzing the impact of spatial and temporal smoothing on the morphology of source signals.

RESULTS

AT estimation using a spatiotemporal derivative performed better than using a temporal derivative. Compared to deflection-based AT estimation, correlation-based methods were less prone to LoB artifacts but performed worse in identifying real LoBs. Temporal smoothing could eliminate artifacts for TMVs but not for EPs, which could be linked to their temporal morphology. TMVs led to more accurate ATs on the septum than EPs. Mesh resolution had a negligible effect on inverse reconstructions, but small distances were important for cross-correlation-based estimation of AT delays.

CONCLUSION

LoB artifacts are mainly caused by the inherent spatial smoothing effect of the inverse reconstruction. Among the configurations evaluated, only deflection-based AT estimation in combination with TMVs and strong temporal smoothing can prevent LoB artifacts, while preserving real LoBs.

SIGNIFICANCE

Regions of slow conduction are of considerable clinical interest and LoB artifacts observed in non-invasive ATs can lead to misinterpretations. We addressed this problem by identifying factors causing such artifacts and methods to reduce them.

Comparing Non-invasive Inverse Electrocardiography With Invasive Endocardial and Epicardial Electroanatomical Mapping During Sinus Rhythm

This study presents a novel non-invasive equivalent dipole layer (EDL) based inverse electrocardiography (iECG) technique which estimates both endocardial and epicardial ventricular activation sequences. We aimed to quantitatively compare our iECG approach with invasive electro-anatomical mapping (EAM) during sinus rhythm with the objective of enabling functional substrate imaging and sudden cardiac death risk stratification in patients with cardiomyopathy. Thirteen patients (77% males, 48 ± 20 years old) referred for endocardial and epicardial EAM underwent 67-electrode body surface potential mapping and CT imaging. The EDL-based iECG approach was improved by mimicking the effects of the His-Purkinje system on ventricular activation. EAM local activation timing (LAT) maps were compared with iECG-LAT maps using absolute differences and Pearson’s correlation coefficient, reported as mean ± standard deviation [95% confidence interval]. The correlation coefficient between iECG-LAT maps and EAM was 0.54 ± 0.19 [0.49–0.59] for epicardial activation, 0.50 ± 0.27 [0.41–0.58] for right ventricular endocardial activation and 0.44 ± 0.29 [0.32–0.56] for left ventricular endocardial activation. The absolute difference in timing between iECG maps and EAM was 17.4 ± 7.2 ms for epicardial maps, 19.5 ± 7.7 ms for right ventricular endocardial maps, 27.9 ± 8.7 ms for left ventricular endocardial maps. The absolute distance between right ventricular endocardial breakthrough sites was 30 ± 16 mm and 31 ± 17 mm for the left ventricle. The absolute distance for latest epicardial activation was median 12.8 [IQR: 2.9–29.3] mm. This first in-human quantitative comparison of iECG and invasive LAT-maps on both the endocardial and epicardial surface during sinus rhythm showed improved agreement, although with considerable absolute difference and moderate correlation coefficient. Non-invasive iECG requires further refinements to facilitate clinical implementation and risk stratification.

Non-invasive epicardial and endocardial electrocardiographic imaging for scar-related ventricular tachycardia

Aims

Contact mapping is currently used to guide catheter ablation of scar-related ventricular tachycardia (VT) but usually provides incomplete assessment of 3D re-entry circuits and their arrhythmogenic substrates. This study investigates the feasibility of non-invasive electrocardiographic imaging (ECGi) in mapping scar substrates and re-entry circuits throughout the epicardium and endocardium.

Methods and results

Four patients undergoing endocardial and epicardial mapping and ablation of scar-related VT had computed tomography scans and a 120-lead electrocardiograms, which were used to compute patient-specific ventricular epicardial and endocardial unipolar electrograms (CEGMs). Native-rhythm CEGMs were used to identify sites of myocardial scar and signal fractionation. Computed electrograms of induced VT were used to localize re-entrant circuits and exit sites. Results were compared to in vivo contact mapping data and epicardium-based ECGi solutions. During native rhythm, an average of 493 ± 18 CEGMs were analysed on each patient. Identified regions of scar and fractionation comprised, respectively, 25 ± 4% and 2 ± 1% of the ventricular surface area. Using a linear mixed-effects model grouped at the level of an individual patient, CEGM voltage and duration were significantly associated with contact bipolar voltage. During induced VT, the inclusion of endocardial layer in ECGi made it possible to identify two epicardial vs. three endocardial VT exit sites among five reconstructed re-entry circuits.

Conclusion

Electrocardiographic imaging may be used to reveal sites of signal fractionation and to map short-lived VT circuits. Its capacity to map throughout epicardial and endocardial layers may improve the delineation of 3D re-entry circuits and their arrhythmogenic substrates.

Localization of Activation Origin on Patient-Specific Endocardial Surface by the Equivalent Double Layer (EDL) Source Model With Sparse Bayesian Learning

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 for activation originating on the left-ventricular endocardial surface, by using a sparse Bayesian learning (SBL).

METHODS

The inverse problem of electrocardiography was solved by reconstructing endocardial potentials from time integrals of body-surface electrocardiograms and from patient-specific geometry of the heart and torso for three patients with structurally normal ventricular myocardium, who underwent endocardial catheter mapping that included pace mapping. Complementary simulations using dipole sources in patient-specific geometry were also performed. The proposed method is using sparse property of the equivalent-double-layer (EDL) model of cardiac sources; it employs the SBL and makes use of the spatio-temporal features of the cardiac action potentials.

RESULTS

The mean localization error of the proposed method for pooled pacing sites ( n=52) was significantly smaller ( p=0.0039) than that achieved for the same patients in the study of Erem et al. Simulation experiments localized the source dipoles ( n=48) from forward-simulated potentials with the error of 9.4 ± 4.5 mm (mean ± SD).

CONCLUSION

The results of our clinical and simulation experiments demonstrate that localization of left-ventricular endocardial activation by means of the Bayesian approach, based on sparse representation of sources by EDL, is feasible and accurate.

SIGNIFICANCE

The proposed approach to localizing endocardial sources may have important applications in pre-procedure assessment of arrhythmias and in guiding their ablation treatment.

Evaluation of Fifteen Algorithms for the Resolution of the Electrocardiography Imaging Inverse Problem Using ex-vivo and in-silico Data

The electrocardiographic imaging inverse problem is ill-posed. Regularization has to be applied to stabilize the problem and solve for a realistic solution. Here, we assess different regularization methods for solving the inverse problem. In this study, we assess (i) zero order Tikhonov regularization (ZOT) in conjunction with the Method of Fundamental Solutions (MFS), (ii) ZOT regularization using the Finite Element Method (FEM), and (iii) the L1-Norm regularization of the current density on the heart surface combined with FEM. Moreover, we apply different approaches for computing the optimal regularization parameter, all based on the Generalized Singular Value Decomposition (GSVD). These methods include Generalized Cross Validation (GCV), Robust Generalized Cross Validation (RGCV), ADPC, U-Curve and Composite REsidual and Smoothing Operator (CRESO) methods. Both simulated and experimental data are used for this evaluation. Results show that the RGCV approach provides the best results to determine the optimal regularization parameter using both the FEM-ZOT and the FEM-L1-Norm. However for the MFS-ZOT, the GCV outperformed all the other regularization parameter choice methods in terms of relative error and correlation coefficient. Regarding the epicardial potential reconstruction, FEM-L1-Norm clearly outperforms the other methods using the simulated data but, using the experimental data, FEM based methods perform as well as MFS. Finally, the use of FEM-L1-Norm combined with RGCV provides robust results in the pacing site localization.

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.

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.

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.

A Potential-Based Inverse Spectral Method to Noninvasively Localize Discordant Distributions of Alternans on the Heart From the ECG

T-wave alternans (TWA), defined as the beat-to-beat alternation in amplitude of the T-waves, has been shown to be linked to ventricular fibrillation (VF). However, current TWA tests have high sensitivity but low specificity in determining who is at risk. To overcome this limitation, it might be helpful to determine the spatial distribution of any regions on the heart that alternate in opposite phase. Understanding these spatial distributions in relation to the regular activation of the heart could help explain the mechanism for the genesis of VF and thus disambiguate the low specificity of TWA.

GOAL

Image the spatial distribution of TWA on the heart surface from ECG measurements.

METHODS

We introduced the inverse spectral method (ISM), a tailored inverse (or ElectroCardioGraphic Imaging) solution designed specifically to noninvasively image cases of TWA on the heart.

RESULTS

We evaluate the ISM on its capacity to reliably detect the spatial distributions of TWA compared against a standard TWA detection method applied directly to the electrograms on the heart surface. We report on results from both a series of synthetic simulations of TWA generated using the ECGSIM software and a set of continuous epicardial surface voltage recordings from a canine experiment. ISM detected TWA distributions that matched the phase of the true underlying out-of-phase regions over and of the heart surface, respectively.

CONCLUSION

Our results suggest that ISM is capable of reliably detecting the different regions present in a TWA distribution across a wide variety of TWA locations on the heart in simulation and in the face of transients and nonidealities in the canine recordings.

Noninvasive Imaging of Human Atrial Activation during Atrial Flutter and Normal Rhythm from Body Surface Potential Maps

Background

Knowledge of atrial electrophysiological properties is crucial for clinical intervention of atrial arrhythmias and the investigation of the underlying mechanism. This study aims to evaluate the feasibility of a novel noninvasive cardiac electrical imaging technique in imaging bi-atrial activation sequences from body surface potential maps (BSPMs).

Methods

The study includes 7 subjects, with 3 atrial flutter patients, and 4 healthy subjects with normal atrial activations. The subject-specific heart-torso geometries were obtained from MRI/CT images. The equivalent current densities were reconstructed from 208-channel BSPMs by solving the inverse problem using individual heart-torso geometry models. The activation times were estimated from the time instant corresponding to the highest peak in the time course of the equivalent current densities. To evaluate the performance, a total of 32 cycles of atrial flutter were analyzed. The imaged activation maps obtained from single beats were compared with the average maps and the activation maps measured from CARTO, by using correlation coefficient (CC) and relative error (RE).

Results

The cardiac electrical imaging technique is capable of imaging both focal and reentrant activations. The imaged activation maps for normal atrial activations are consistent with findings from isolated human hearts. Activation maps for isthmus-dependent counterclockwise reentry were reconstructed on three patients with typical atrial flutter. The method was capable of imaging macro counterclockwise reentrant loop in the right atrium and showed inter-atria electrical conduction through coronary sinus. The imaged activation sequences obtained from single beats showed good correlation with both the average activation maps (CC = 0.91±0.03, RE = 0.29±0.05) and the clinical endocardial findings using CARTO (CC = 0.70±0.04, RE = 0.42±0.05).

Conclusions

The noninvasive cardiac electrical imaging technique is able to reconstruct complex atrial reentrant activations and focal activation patterns in good consistency with clinical electrophysiological mapping. It offers the potential to assist in radio-frequency ablation of atrial arrhythmia and help defining the underlying arrhythmic mechanism.

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.

Noninvasive epicardial and endocardial electrocardiographic imaging of scar-related ventricular tachycardia

BACKGROUND

The majority of life-threatening ventricular tachycardias (VTs) are sustained by heterogeneous scar substrates with narrow strands of surviving tissue. An effective treatment for scar-related VT is to modify the underlying scar substrate by catheter ablation. If activation sequence and entrainment mapping can be performed during sustained VT, the exit and isthmus of the circuit can often be identified. However, with invasive catheter mapping, only monomorphic VT that is hemodynamically stable can be mapped in this manner. For the majority of patients with poorly tolerated VTs or multiple VTs, a close inspection of the re-entry circuit is not possible. A noninvasive approach to fast mapping of unstable VTs can potentially allow an improved identification of critical ablation sites.

METHODS

For patients who underwent catheter ablation of scar-related VT, CT scan was obtained prior to the ablation procedure and 120-lead body-surface electrocardiograms (ECGs) were acquired during induced VTs. These data were used for noninvasive ECG imaging to computationally reconstruct electrical potentials on the epicardium and on the endocardium of both ventricles. Activation time and phase maps of the VT circuit were extracted from the reconstructed electrograms. They were analyzed with respect to scar substrate obtained from catheter mapping, as well as VT exits confirmed through ablation sites that successfully terminated the VT.

RESULTS

The reconstructed re-entry circuits correctly revealed both epicardial and endocardial origins of activation, consistent with locations of exit sites confirmed from the ablation procedure. The temporal dynamics of the re-entry circuits, particularly the slowing of conduction as indicated by the crowding and zig-zag conducting of the activation isochrones, collocated well with scar substrate obtained by catheter voltage maps. Furthermore, the results indicated that some re-entry circuits involve both the epicardial and endocardial layers, and can only be properly interpreted by mapping both layers simultaneously.

CONCLUSIONS

This study investigated the potential of ECG-imaging for beat-to-beat mapping of unstable reentrant circuits. It shows that simultaneous epicardial and endocardial mapping may improve the delineation of the 3D spatial construct of a re-entry circuit and its exit. It also shows that the use of phase mapping can reveal regions of slow conduction that collocate well with suspected heterogeneous regions within and around the scar.

Numerical simulation of electrocardiograms for full cardiac cycles in healthy and pathological conditions

This work is dedicated to the simulation of full cycles of the electrical activity of the heart and the corresponding body surface potential. The model is based on a realistic torso and heart anatomy, including ventricles and atria. One of the specificities of our approach is to model the atria as a surface, which is the kind of data typically provided by medical imaging for thin volumes. The bidomain equations are considered in their usual formulation in the ventricles, and in a surface formulation on the atria. Two ionic models are used: the Courtemanche-Ramirez-Nattel model on the atria and the 'minimal model for human ventricular action potentials' by Bueno-Orovio, Cherry, and Fenton in the ventricles. The heart is weakly coupled to the torso by a Robin boundary condition based on a resistor-capacitor transmission condition. Various electrocardiograms (ECGs) are simulated in healthy and pathological conditions (left and right bundle branch blocks, Bachmann's bundle block, and Wolff-Parkinson-White syndrome). To assess the numerical ECGs, we use several qualitative and quantitative criteria found in the medical literature. Our simulator can also be used to generate the signals measured by a vest of electrodes. This capability is illustrated at the end of the article. Copyright © 2015 John Wiley & Sons, Ltd.

Examining the Impact of Prior Models in Transmural Electrophysiological Imaging: A Hierarchical Multiple-Model Bayesian Approach

Noninvasive cardiac electrophysiological (EP) imaging aims to mathematically reconstruct the spatiotemporal dynamics of cardiac sources from body-surface electrocardiographic (ECG) data. This ill-posed problem is often regularized by a fixed constraining model. However, a fixed-model approach enforces the source distribution to follow a pre-assumed structure that does not always match the varying spatiotemporal distribution of actual sources. To understand the model-data relation and examine the impact of prior models, we present a multiple-model approach for volumetric cardiac EP imaging where multiple prior models are included and automatically picked by the available ECG data. Multiple models are incorporated as an Lp-norm prior for sources, where p is an unknown hyperparameter with a prior uniform distribution. To examine how different combinations of models may be favored by different measurement data, the posterior distribution of cardiac sources and hyperparameter p is calculated using a Markov Chain Monte Carlo (MCMC) technique. The importance of multiple-model prior was assessed in two sets of synthetic and real-data experiments, compared to fixed-model priors (using Laplace and Gaussian priors). The results showed that the posterior combination of models (the posterior distribution of p) as determined by the ECG data differed substantially when reconstructing sources with different sizes and structures. While the use of fixed models is best suited in situations where the prior assumption fits the actual source structures, the use of an automatically adaptive set of models may have the ability to better address model-data mismatch and to provide consistent performance in reconstructing sources with different properties.

Application of robust Generalised Cross-Validation to the inverse problem of electrocardiology

Robust Generalised Cross-Validation was proposed recently as a method for determining near optimal regularisation parameters in inverse problems. It was introduced to overcome a problem with the regular Generalised Cross-Validation method in which the function that is minimised to obtain the regularisation parameter often has a broad, flat minimum, resulting in a poor estimate for the parameter. The robust method defines a new function to be minimised which has a narrower minimum, but at the expense of introducing a new parameter called the robustness parameter. In this study, the Robust Generalised Cross-Validation method is applied to the inverse problem of electrocardiology. It is demonstrated that, for realistic situations, the robustness parameter can be set to zero. With this choice of robustness parameter, it is shown that the robust method is able to obtain estimates of the regularisation parameter in the inverse problem of electrocardiology that are comparable to, or better than, many of the standard methods that are applied to this inverse problem.

Sensitivity of Noninvasive Cardiac Electrophysiological Imaging to Variations in Personalized Anatomical Modeling

OBJECTIVE

Noninvasive cardiac electrophysiological (EP) imaging techniques rely on anatomically-detailed heart-torso models derived from high-quality tomographic images of individual subjects. However, anatomical modeling involves variations that lead to unresolved uncertainties in the outcome of EP imaging, bringing questions to the robustness of these methods in clinical practice. In this study, we design a systematic statistical approach to assess the sensitivity of EP imaging methods to the variations in personalized anatomical modeling.

METHODS

We first quantify the variations in personalized anatomical models by a novel application of statistical shape modeling. Given the statistical distribution of the variation in personalized anatomical models, we then employ unscented transform to determine the sensitivity of EP imaging outputs to the variation in input personalized anatomical modeling.

RESULTS

We test the feasibility of our proposed approach using two of the existing EP imaging methods: epicardial-based electrocardiographic imaging and transmural electrophysiological imaging. Both phantom and real-data experiments show that variations in personalized anatomical models have negligible impact on the outcome of EP imaging.

CONCLUSION

This study verifies the robustness of EP imaging methods to the errors in personalized anatomical modeling and suggests the possibility to simplify the process of anatomical modeling in future clinical practice.

SIGNIFICANCE

This study proposes a systematic statistical approach to quantify anatomical modeling variations and assess their impact on EP imaging, which can be extended to find a balance between the quality of personalized anatomical models and the accuracy of EP imaging that may improve the clinical feasibility of EP imaging.

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.

Imaging cardiac activation sequence during ventricular tachycardia in a canine model of nonischemic heart failure

Noninvasive cardiac activation imaging of ventricular tachycardia (VT) is important in the clinical diagnosis and treatment of arrhythmias in heart failure (HF) patients. This study investigated the ability of the three-dimensional cardiac electrical imaging (3DCEI) technique for characterizing the activation patterns of spontaneously occurring and norepinephrine (NE)-induced VTs in a newly developed arrhythmogenic canine model of nonischemic HF. HF was induced by aortic insufficiency followed by aortic constriction in three canines. Up to 128 body-surface ECGs were measured simultaneously with bipolar recordings from up to 232 intramural sites in a closed-chest condition. Data analysis was performed on the spontaneously occurring VTs (n=4) and the NE-induced nonsustained VTs (n=8) in HF canines. Both spontaneously occurring and NE-induced nonsustained VTs initiated by a focal mechanism primarily from the subendocardium, but occasionally from the subepicardium of left ventricle. Most focal initiation sites were located at apex, right ventricular outflow tract, and left lateral wall. The NE-induced VTs were longer, more rapid, and had more focal sites than the spontaneously occurring VTs. Good correlation was obtained between imaged activation sequence and direct measurements (averaged correlation coefficient of ∼0.70 over 135 VT beats). The reconstructed initiation sites were ∼10 mm from measured initiation sites, suggesting good localization in such a large animal model with cardiac size similar to a human. Both spontaneously occurring and NE-induced nonsustained VTs had focal initiation in this canine model of nonischemic HF. 3DCEI is feasible to image the activation sequence and help define arrhythmia mechanism of nonischemic HF-associated VTs.

Noninvasive imaging of 3-dimensional myocardial infarction from the inverse solution of equivalent current density in pathological hearts

We propose a new approach to noninvasively image the 3-D myocardial infarction (MI) substrates based on equivalent current density (ECD) distribution that is estimated from the body surface potential maps (BSPMs) during S-T segment. The MI substrates were identified using a predefined threshold of ECD. Computer simulations were performed to assess the performance with respect to: 1) MI locations; 2) MI sizes; 3) measurement noise; 4) numbers of BSPM electrodes; and 5) volume conductor modeling errors. A total of 114 sites of transmural infarctions, 91 sites of epicardial infarctions, and 36 sites of endocardial infarctions were simulated. The simulation results show that: 1) Under 205 electrodes and 10-μV noise, the averaged accuracies of imaging transmural MI are 83.4% for sensitivity, 82.2% for specificity, 65.0% for Dice's coefficient, and 6.5 mm for distances between the centers of gravity (DCG). 2) For epicardial infarction, the averaged imaging accuracies are 81.6% for sensitivity, 75.8% for specificity, 45.3% for Dice's coefficient, and 7.5 mm for DCG; while for endocardial infarction, the imaging accuracies are 80.0% for sensitivity, 77.0% for specificity, 39.2% for Dice's coefficient, and 10.4 mm for DCG. 3) A reasonably good imaging performance was obtained under higher noise levels, fewer BSPM electrodes, and mild volume conductor modeling errors. The present results suggest that this method has the potential to aid in the clinical identification of the MI substrates.

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.

Hierarchical multiple-model Bayesian approach to transmural electrophysiological imaging

Noninvasive electrophysiological (EP) imaging of the heart aims to mathematically reconstruct the spatiotemporal dynamics of cardiac current sources from body-surface electrocardiographic (ECG) data. This ill-posed problem is often regularized by a fixed constraining model. However, this approach enforces the source distribution to follow a preassumed spatial structure that does not always match the varying spatiotemporal distribution of current sources. We propose a hierarchical Bayesian approach to transmural EP imaging that employs a continuous combination of multiple models, each reflecting a specific spatial property for current sources. Multiple models are incorporated as an Lp-norm prior for current sources, where p is an unknown hyperparameter with a prior probabilistic distribution. The current source estimation is obtained as an optimally weighted combination of solutions across all models, the weight being determined from the posterior distribution of p inferred from ECG data. The accuracy of our approach is assessed in a set of synthetic and real-data experiments on human heart-torso models. While the use of fixed models (L1- and L2-norm) only properly recovers sources with specific structures, our method delivers consistent performance in reconstructing sources with various extents and structures.

Lp-norm regularization in volumetric imaging of cardiac current sources

Advances in computer vision have substantially improved our ability to analyze the structure and mechanics of the heart. In comparison, our ability to observe and analyze cardiac electrical activities is much limited. The progress to computationally reconstruct cardiac current sources from noninvasive voltage data sensed on the body surface has been hindered by the ill-posedness and the lack of a unique solution of the reconstruction problem. Common L2- and L1-norm regularizations tend to produce a solution that is either too diffused or too scattered to reflect the complex spatial structure of current source distribution in the heart. In this work, we propose a general regularization with Lp-norm (1 < p < 2) constraint to bridge the gap and balance between an overly smeared and overly focal solution in cardiac source reconstruction. In a set of phantom experiments, we demonstrate the superiority of the proposed Lp-norm method over its L1 and L2 counterparts in imaging cardiac current sources with increasing extents. Through computer-simulated and real-data experiments, we further demonstrate the feasibility of the proposed method in imaging the complex structure of excitation wavefront, as well as current sources distributed along the postinfarction scar border. This ability to preserve the spatial structure of source distribution is important for revealing the potential disruption to the normal heart excitation.

Computing ischemic regions in the heart with the bidomain model--first steps towards validation

We investigate whether it is possible to use the bidomain model and body surface potential maps (BSPMs) to compute the size and position of ischemic regions in the human heart. This leads to a severely ill posed inverse problem for a potential equation. We do not use the classical inverse problems of electrocardiography, in which the unknown sources are the epicardial potential distribution or the activation sequence. Instead we employ the bidomain theory to obtain a model that also enables identification of ischemic regions transmurally. This approach makes it possible to distinguish between subendocardial and transmural cases, only using the BSPM data. The main focus is on testing a previously published algorithm on clinical data, and the results are compared with images taken with perfusion scintigraphy. For the four patients involved in this study, the two modalities produce results that are rather similar: The relative differences between the center of mass and the size of the ischemic regions, suggested by the two modalities, are 10.8% ± 4.4% and 7.1% ± 4.6%, respectively. We also present some simulations which indicate that the methodology is robust with respect to uncertainties in important model parameters. However, in contrast to what has been observed in investigations only involving synthetic data, inequality constraints are needed to obtain sound results.

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.

Transmural imaging of ventricular action potentials and post-infarction scars in swine hearts

The problem of using surface data to reconstruct transmural electrophysiological (EP) signals is intrinsically ill-posed without a unique solution in its unconstrained form. Incorporating physiological spatiotemporal priors through probabilistic integration of dynamic EP models, we have previously developed a Bayesian approach to transmural electrophysiological imaging (TEPI) using body-surface electrocardiograms. In this study, we generalize TEPI to using electrical signals collected from heart surfaces, and we test its feasibility on two pre-clinical swine models provided through the STACOM 2011 EP simulation Challenge. Since this new application of TEPI does not require whole-body imaging, there may be more immediate potential in EP laboratories where it could utilize catheter mapping data and produce transmural information for therapy guidance. Another focus of this study is to investigate the consistency among three modalities in delineating scar after myocardial infarction: TEPI, electroanatomical voltage mapping (EAVM), and magnetic resonance imaging (MRI). Our preliminary data demonstrate that, compared to the low-voltage scar area in EAVM, the 3-D electrical scar volume detected by TEPI is more consistent with anatomical scar volume delineated in MRI. Furthermore, TEPI could complement anatomical imaging by providing EP functional features related to both scar and healthy tissue.

Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology

Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the current efforts of clinical atrial modeling in the euHeart project are summarized within the context of recent publications in this field. Model-based segmentation methods allow for the automatic generation of ready-to-simulate patient-specific anatomical models. EP models can be adapted to patient groups based on a-priori knowledge and to the individual without significant further data acquisition. ECG and intracardiac data build the basis for excitation personalization. Information from late enhancement (LE) MRI can be used to evaluate the success of radio-frequency ablation (RFA) procedures and interactive virtual atria pave the way for RFA planning. Atrial modeling is currently in a transition from the sole use in basic research to future clinical applications. The proposed methods build the framework for model-based diagnosis and therapy evaluation and planning. Complex models allow to understand biophysical mechanisms and enable the development of simplified models for clinical applications.

Noninvasive mapping of transmural potentials during activation in swine hearts from body surface electrocardiograms

The three-dimensional cardiac electrical imaging (3DCEI) technique was previously developed to estimate the initiation site(s) of cardiac activation and activation sequence from the noninvasively measured body surface potential maps (BSPMs). The aim of this study was to develop and evaluate the capability of 3DCEI in mapping the transmural distribution of extracellular potentials and localizing initiation sites of ventricular activation in an in vivo animal model. A control swine model (n = 10) was employed in this study. The heart-torso volume conductor model and the excitable heart model were constructed based on each animal's preoperative MR images and a priori known physiological knowledge. Body surface potential mapping and intracavitary noncontact mapping (NCM) were simultaneously conducted during acute ventricular pacing. The 3DCEI analysis was then applied on the recorded BSPMs. The estimated initiation sites were compared to the precise pacing sites; as a subset of the mapped transmural potentials by 3DCEI, the electrograms on the left ventricular endocardium were compared to the corresponding output of the NCM system. Over the 16 LV and 48 RV pacing studies, the averaged localization error was 6.1±2.3 mm, and the averaged correlation coefficient between the estimated endocardial electrograms by 3DCEI and from the NCM system was 0.62±0.09. The results demonstrate that the 3DCEI approach can well localize the sites of initiation of ectopic beats and can obtain physiologically reasonable transmural potentials in an in vivo setting during focal ectopic beats. This study suggests the feasibility of tomographic mapping of 3D ventricular electrograms from the body surface recordings.

Noninvasive reconstruction of the three-dimensional ventricular activation sequence during pacing and ventricular tachycardia in the rabbit heart

Ventricular arrhythmias represent one of leading causes for sudden cardiac death, a significant problem in public health. Noninvasive imaging of cardiac electric activities associated with ventricular arrhythmias plays an important role in better our understanding of the mechanisms and optimizing the treatment options. The present study aims to rigorously validate a novel three-dimensional (3-D) cardiac electrical imaging (3-DCEI) technique with the aid of 3-D intra-cardiac mapping during paced rhythm and ventricular tachycardia (VT) in the rabbit heart. Body surface potentials and intramural bipolar electrical recordings were simultaneously measured in a closed-chest condition in thirteen healthy rabbits. Single-site pacing and dual-site pacing were performed from ventricular walls and septum. VTs and premature ventricular complexes (PVCs) were induced by intravenous norepinephrine (NE). The non-invasively imaged activation sequence correlated well with invasively measured counterparts, with a correlation coefficient of 0.72 and a relative error of 0.30 averaged over all paced beats and NE-induced PVCs and VT beats. The averaged distance from imaged site of initial activation to measured site determined from intra-cardiac mapping was ∼5mm. These promising results suggest that 3-DCEI is feasible to non-invasively localize the origins and image activation sequence of focal ventricular arrhythmias.

Noninvasive detection of epicardial and endocardial activity of the heart

Determining electrical activation of the heart in a noninvasive way is one of the challenges in cardiac electrophysiology. The ECG provides some, but limited information about the electrical status of the heart. This article describes a method to determine both endocardial and epicardial activation of the heart of an individual patient from 64 electrograms recorded from the body surface. Information obtained in this way might be helpful for the treatment of arrhythmias, to assess the effect of drugs on conduction in the heart and to assess electrical stability of the heart.

Noninvasive reconstruction of the three-dimensional ventricular activation sequence during pacing and ventricular tachycardia in the canine heart

Single-beat imaging of myocardial activation promises to aid in both cardiovascular research and clinical medicine. In the present study we validate a three-dimensional (3D) cardiac electrical imaging (3DCEI) technique with the aid of simultaneous 3D intracardiac mapping to assess its capability to localize endocardial and epicardial initiation sites and image global activation sequences during pacing and ventricular tachycardia (VT) in the canine heart. Body surface potentials were measured simultaneously with bipolar electrical recordings in a closed-chest condition in healthy canines. Computed tomography images were obtained after the mapping study to construct realistic geometry models. Data analysis was performed on paced rhythms and VTs induced by norepinephrine (NE). The noninvasively reconstructed activation sequence was in good agreement with the simultaneous measurements from 3D cardiac mapping with a correlation coefficient of 0.74 ± 0.06, a relative error of 0.29 ± 0.05, and a root mean square error of 9 ± 3 ms averaged over 460 paced beats and 96 ectopic beats including premature ventricular complexes, couplets, and nonsustained monomorphic VTs and polymorphic VTs. Endocardial and epicardial origins of paced beats were successfully predicted in 72% and 86% of cases, respectively, during left ventricular pacing. The NE-induced ectopic beats initiated in the subendocardium by a focal mechanism. Sites of initial activation were estimated to be ∼7 mm from the measured initiation sites for both the paced beats and ectopic beats. For the polymorphic VTs, beat-to-beat dynamic shifts of initiation site and activation pattern were characterized by the reconstruction. The present results suggest that 3DCEI can noninvasively image the 3D activation sequence and localize the origin of activation of paced beats and NE-induced VTs in the canine heart with good accuracy. This 3DCEI technique offers the potential to aid interventional therapeutic procedures for treating ventricular arrhythmias arising from epicardial or endocardial sites and to noninvasively assess the mechanisms of these arrhythmias.

An enhanced method for accessory pathway localization in case of Wolff-Parkinson-White syndrome

This paper presents an analysis of the Arruda accessory pathway localization method for patients suffering from Wolff-Parkinson-White syndrome, with modifications to increase the overall accuracy. The Arruda method was tested on a total of 79 cases, and 91.1% localization performance was reached. After a deeper analysis of each decision point of the Arruda localization method, we considered that the lead aVF was not as relevant as other leads (I, II, III, V1) used. The branch of the decision tree, which evaluates the left ventricle positions, was entirely replaced using different decision criteria based on the same biological parameters. The modified algorithm significantly improves the localization accuracy in the left ventricle, reaching 94.9%. An accurate localization performance of non-invasive methods is relevant because it can enlighten the necessary invasive interventions, and it also reduces the discomfort caused to the patient.

Localization of endocardial ectopic activity by means of noninvasive endocardial surface current density reconstruction

Localization of the source of cardiac ectopic activity has direct clinical benefits for determining the location of the corresponding ectopic focus. In this study, a recently developed current-density (CD)-based localization approach was experimentally evaluated in noninvasively localizing the origin of the cardiac ectopic activity from body-surface potential maps (BSPMs) in a well-controlled experimental setting. The cardiac ectopic activities were induced in four well-controlled intact pigs by single-site pacing at various sites within the left ventricle (LV). In each pacing study, the origin of the induced ectopic activity was localized by reconstructing the CD distribution on the endocardial surface of the LV from the measured BSPMs and compared with the estimated single moving dipole (SMD) solution and precise pacing site (PS). Over the 60 analyzed beats corresponding to ten pacing sites (six for each), the mean and standard deviation of the distance between the locations of maximum CD value and the corresponding PSs were 16.9 mm and 4.6 mm, respectively. In comparison, the averaged distance between the SMD locations and the corresponding PSs was slightly larger (18.4 ± 3.4 mm). The obtained CD distribution of activated sources extending from the stimulus site also showed high consistency with the endocardial potential maps estimated by a minimally invasive endocardial mapping system. The present experimental results suggest that the CD method is able to locate the approximate site of the origin of a cardiac ectopic activity, and that the distribution of the CD can portray the propagation of early activation of an ectopic beat.

Noninvasive imaging of three-dimensional cardiac activation sequence during pacing and ventricular tachycardia

BACKGROUND

Imaging cardiac excitation within ventricular myocardium is important in the treatment of cardiac arrhythmias and might help improve our understanding of arrhythmia mechanisms.

OBJECTIVE

This study sought to rigorously assess the imaging performance of a 3-dimensional (3D) cardiac electrical imaging (3DCEI) technique with the aid of 3D intracardiac mapping from up to 216 intramural sites during paced rhythm and norepinephrine (NE)-induced ventricular tachycardia (VT) in the rabbit heart.

METHODS

Body surface potentials and intramural bipolar electrical recordings were simultaneously measured in a closed-chest condition in 13 healthy rabbits. Single-site pacing and dual-site pacing were performed from ventricular walls and septum. VTs and premature ventricular complexes (PVCs) were induced by intravenous NE. Computed tomography images were obtained to construct geometry models.

RESULTS

The noninvasively imaged activation sequence correlated well with invasively measured counterpart, with a correlation coefficient of 0.72 ± 0.04, and a relative error of 0.30 ± 0.02 averaged over 520 paced beats as well as 73 NE-induced PVCs and VT beats. All PVCs and VT beats initiated in the subendocardium by a nonreentrant mechanism. The averaged distance from the imaged site of initial activation to the pacing site or site of arrhythmias determined from intracardiac mapping was ∼5 mm. For dual-site pacing, the double origins were identified when they were located at contralateral sides of ventricles or at the lateral wall and the apex.

CONCLUSION

3DCEI can noninvasively delineate important features of focal or multifocal ventricular excitation. It offers the potential to aid in localizing the origins and imaging activation sequences of ventricular arrhythmias, and to provide noninvasive assessment of the underlying arrhythmia mechanisms.

Single-beat noninvasive imaging of ventricular endocardial and epicardial activation in patients undergoing CRT

Background

Little is known about the effect of cardiac resynchronization therapy (CRT) on endo- and epicardial ventricular activation. Noninvasive imaging of cardiac electrophysiology (NICE) is a novel imaging tool for visualization of both epi- and endocardial ventricular electrical activation.

Methodology/Principal Findings

NICE was performed in ten patients with congestive heart failure (CHF) undergoing CRT and in ten patients without structural heart disease (control group). NICE is a fusion of data from high-resolution ECG mapping with a model of the patient's individual cardiothoracic anatomy created from magnetic resonance imaging. Beat-to-beat endocardial and epicardial ventricular activation sequences were computed during native rhythm as well as during ventricular pacing using a bidomain theory-based heart model to solve the related inverse problem. During right ventricular (RV) pacing control patients showed a deterioration of the ventricular activation sequence similar to the intrinsic activation pattern of CHF patients. Left ventricular propagation velocities were significantly decreased in CHF patients as compared to the control group (1.6±0.4 versus 2.1±0.5 m/sec; p<0.05). CHF patients showed right-to-left septal activation with the latest activation epicardially in the lateral wall of the left ventricle. Biventricular pacing resulted in a resynchronization of the ventricular activation sequence and in a marked decrease of total LV activation duration as compared to intrinsic conduction and RV pacing (129±16 versus 157±28 and 173±25 ms; both p<0.05).

Conclusions/Significance

Endocardial and epicardial ventricular activation can be visualized noninvasively by NICE. Identification of individual ventricular activation properties may help identify responders to CRT and to further improve response to CRT by facilitating a patient-specific lead placement and device programming.

Noninvasive estimation of global activation sequence using the extended Kalman filter

A new algorithm for 3-D imaging of the activation sequence from noninvasive body surface potentials is proposed. After formulating the nonlinear relationship between the 3-D activation sequence and the body surface recordings during activation, the extended Kalman filter (EKF) is utilized to estimate the activation sequence in a recursive way. The state vector containing the activation sequence is optimized during iteration by updating the error variance/covariance matrix. A new regularization scheme is incorporated into the "predict" procedure of EKF to tackle the ill-posedness of the inverse problem. The EKF-based algorithm shows good performance in simulation under single-site pacing. Between the estimated activation sequences and true values, the average correlation coefficient (CC) is 0.95, and the relative error (RE) is 0.13. The average localization error (LE) when localizing the pacing site is 3.0 mm. Good results are also obtained under dual-site pacing (CC = 0.93, RE = 0.16, and LE = 4.3 mm). Furthermore, the algorithm shows robustness to noise. The present promising results demonstrate that the proposed EKF-based inverse approach can noninvasively estimate the 3-D activation sequence with good accuracy and the new algorithm shows good features due to the application of EKF.

Non-invasive imaging of cardiac activation and recovery

The sequences of activation and recovery of the heart have physiological and clinical relevance. We report on progress made over the last years in the method that images these timings based on an equivalent double layer on the myocardial surface serving as the equivalent source of cardiac activity, with local transmembrane potentials (TMP) acting as their strength. The TMP wave forms were described analytically by timing parameters, found by minimizing the difference between observed body surface potentials and those based on the source description. The parameter estimation procedure involved is non-linear, and consequently requires the specification of initial estimates of its solution. Those of the timing of depolarization were based on the fastest route algorithm, taking into account properties of anisotropic propagation inside the myocardium. Those of recovery were based on electrotonic effects. Body surface potentials and individual geometry were recorded on: a healthy subject, a WPW patient and a Brugada patient during an Ajmaline provocation test. In all three cases, the inversely estimated timing agreed entirely with available physiological knowledge. The improvements to the inverse procedure made are attributed to our use of initial estimates based on the general electrophysiology of propagation. The quality of the results and the required computation time permit the application of this inverse procedure in a clinical setting.

Non-invasive imaging of cardiac activation and recovery

The sequences of activation and recovery of the heart have physiological and clinical relevance. We report on progress made over the last years in the method that images these timings based on an equivalent double layer on the myocardial surface serving as the equivalent source of cardiac activity, with local transmembrane potentials (TMP) acting as their strength. The TMP wave forms were described analytically by timing parameters, found by minimizing the difference between observed body surface potentials and those based on the source description. The parameter estimation procedure involved is non-linear, and consequently requires the specification of initial estimates of its solution. Those of the timing of depolarization were based on the fastest route algorithm, taking into account properties of anisotropic propagation inside the myocardium. Those of recovery were based on electrotonic effects. Body surface potentials and individual geometry were recorded on: a healthy subject, a WPW patient and a Brugada patient during an Ajmaline provocation test. In all three cases, the inversely estimated timing agreed entirely with available physiological knowledge. The improvements to the inverse procedure made are attributed to our use of initial estimates based on the general electrophysiology of propagation. The quality of the results and the required computation time permit the application of this inverse procedure in a clinical setting.

Towards a computational method for imaging the extracellular potassium concentration during regional ischemia

We investigate the possibility of using body surface potential maps to image the extracellular potassium concentration during regional ischemia. The problem is formulated as an inverse problem based on a linear approximation of the bidomain model, where we minimize the difference between the results of the model and observations of body surface potentials. The minimization problem is solved by a one-shot technique, where the original PDE system, an adjoint problem, and the relation describing the minimum, are solved simultaneously. This formulation of the problem requires the solution of a 5 x 5 system of linear partial differential equations. The performance of the model is investigated by performing tests based on synthetic data. We find that the model will in many cases detect the correct position and approximate size of the ischemic regions, while some cases are more difficult to locate. It is observed that a simple post-processing of the results produces images that are qualitatively very similar to the true solution.

Noninvasive three-dimensional cardiac activation imaging from body surface potential maps: a computational and experimental study on a rabbit model

Three-dimensional (3-D) cardiac activation imaging (3-DCAI) is a recently developed technique that aims at imaging the activation sequence throughout the the ventricular myocardium. 3-DCAI entails the modeling and estimation of the cardiac equivalent current density (ECD) distribution from which the activation time at any myocardial site is determined as the time point with the peak amplitude of local ECD estimates. In this paper, we report, for the first time, an in vivo validation study assessing the feasibility of 3-DCAI in comparison with the 3-D intracardiac mapping, for a group of four healthy rabbits undergoing the ventricular pacing from various locations. During the experiments, the body surface potentials and the intramural bipolar electrical recordings were simultaneously measured in a closed-chest condition. The ventricular activation sequence noninvasively imaged from the body surface measurements by using 3-DCAI was generally in agreement with that obtained from the invasive intramural recordings. The quantitative comparison between them showed a root mean square (rms) error of 7.42 +/-0.61 ms, a relative error (RE) of 0.24 +/-0.03, and a localization error (LE) of 5.47 +/-1.57 mm. The experimental results were also consistent with our computer simulations conducted in well-controlled and realistic conditions. The present study suggest that 3-DCAI can noninvasively capture some important features of ventricular excitation (e.g., the activation origin and the activation sequence), and has the potential of becoming a useful imaging tool aiding cardiovascular research and clinical diagnosis of cardiac diseases.

Noninvasive estimation of three-dimensional cardiac electrical activities from body surface potential maps

A noninvasive three-dimensional (3D) cardiac electrical imaging (3DCEI) approach, which can estimate the location of the initiation site (IS) of activation and the resultant 3D activation sequence (AS) from body surface potential maps (BSPMs), was validated in an intact large mammalian model (swine) during acute ventricular pacing. Body surface potential mapping and intracavitary noncontact mapping (NCM) were performed simultaneously during pacing from both right ventricular (RV) sites (intramural) and left ventricular (LV) sites (endocardial). Subsequent 3DCEI analyses were performed on the measured BSPMs. In total, 5 RV and 5 LV sites from control and heart failure animals were paced. The averaged localization error of the RV and LV sites were 7.0+/-1.1 mm and 6.6+/-1.9 mm, respectively. The endocardial ASs as a subset of the estimated 3D ASs by 3DCEI were consistent with those reconstructed from the NCM system. The present experimental results demonstrate that the noninvasive 3DCEI approach can localize the initiation site and estimate cardiac activation sequence with good accuracy in an in vivo setting, under control, paced and/or diseased conditions.

Estimation of global ventricular activation sequences by noninvasive three-dimensional electrical imaging: validation studies in a Swine model during pacing

BACKGROUND

A novel noninvasive imaging technique, the heart-model-based three-dimensional cardiac electrical imaging (3DCEI) approach was previously developed and validated to estimate the initiation site (IS) of cardiac activity and the activation sequence (AS) from body surface potential maps (BSPMs) in a rabbit model. The aim of the present study was to validate the 3DCEI in an intact large mammalian model (swine) during acute ventricular pacing.

METHODS AND RESULTS

The heart-torso geometries were constructed from preoperative magnetic resonance (MR) images acquired from each animal. Body surface potential mapping and intracavitary noncontact mapping (NCM) were performed simultaneously during pacing from both right ventricular (RV) (intramural) and left ventricular (LV) sites (endocardial). Subsequent 3DCEI analyses were performed from the measured BSPMs. The estimated ISs were compared with the precise pacing locations and estimated ASs were compared with those recorded by the NCM system. In total, five RV and five LV sites from control and heart failure (HF) animals were paced and sequences of 100 paced beats were analyzed (10 for each site). The averaged localization error (LE) of the RV and LV sites were 7.3 +/- 1.8 mm (n = 50) and 7.0 +/- 2.2 mm (n = 50), respectively. The global 3D ASs throughout the ventricular myocardium were also derived. The endocardial ASs as a subset of the estimated 3D ASs were consistent with those reconstructed from the NCM system.

CONCLUSION

The present experimental results demonstrate that the noninvasive 3DCEI approach can localize the IS and estimate AS with good accuracy in an in vivo setting under control, paced, and/or diseased conditions.

A wavefront-based constraint for potential surface solutions in inverse electrocardiography

Inverse electrocardiography in recent years has generally been approached using one of two quite distinct source models, either a potential-based approach or an activation-based approach. Each approach has advantages and disadvantages relative to the other, which are inherited by all specific methods based on a given approach. Recently our group has been working to develop models which can bridge between these two approaches, hoping to capture some of the most important advantages of both. In this work we present one such effort, which we term wavefront-based potential reconstruction (WBPR). It is a modification of standard regularization methods for potential-based inverse electrocardiography, into which we incorporate a constraint based on a wavefront-like approximation to the potential-based solution. Initial results indicate significant improvement with respect to localization and characterization of the wavefront in simulations using both epicardially and supra-ventricularly paced heartbeats.