An improved method for estimating epicardial potentials from the body surface

Neural network aided extended Kalman filtering for inverse imaging of cardiac transmembrane potential

Objective.The aim of this study is to address the limitations in reconstructing the electrical activity of the heart from the body surface electrocardiogram, which is an ill-posed inverse problem. Current methods often assume values commonly used in the literature in the absence ofa prioriknowledge, leading to errors in the model. Furthermore, most methods ignore the dynamic activation process inherent in cardiomyocytes during the cardiac cycle.Approach.To overcome these limitations, we propose an extended Kalman filter (EKF)-based neural network approach to dynamically reconstruct cardiac transmembrane potential (TMP). Specifically, a recurrent neural network is used to establish the state estimation equation of the EKF, while a convolutional neural network is used as the measurement equation. The Jacobi matrix of the network undergoes a correction feedback process to obtain the Kalman gain.Main results.After repeated iterations, the final estimated state vector, i.e. the reconstructed image of the TMP, is obtained. The results from both the final simulation and real experiments demonstrate the robustness and accurate quantification of the model.Significance.This study presents a new approach to cardiac TMP reconstruction that offers higher accuracy and robustness compared to traditional methods. The use of neural networks and EKFs allows dynamic modelling that takes into account the activation processes inherent in cardiomyocytes and does not requirea prioriknowledge of inputs such as forward transition matrices.

Nonlocal based FISTA network for noninvasive cardiac transmembrane potential imaging

Objective. The primary aim of our study is to advance our understanding and diagnosis of cardiac diseases. We focus on the reconstruction of myocardial transmembrane potential (TMP) from body surface potential mapping.Approach. We introduce a novel methodology for the reconstruction of the dynamic distribution of TMP. This is achieved through the integration of convolutional neural networks with conventional optimization algorithms. Specifically, we utilize the subject-specific transfer matrix to describe the dynamic changes in TMP distribution and ECG observations at the body surface. To estimate the TMP distribution, we employ LNFISTA-Net, a learnable non-local regularized iterative shrinkage-thresholding network. The coupled estimation processes are iteratively repeated until convergence.Main results. Our experiments demonstrate the capabilities and benefits of this strategy. The results highlight the effectiveness of our approach in accurately estimating the TMP distribution, thereby providing a reliable method for the diagnosis of cardiac diseases.Significance. Our approach demonstrates promising results, highlighting its potential utility for a range of applications in the medical field. By providing a more accurate and dynamic reconstruction of TMP, our methodology could significantly improve the diagnosis and treatment of cardiac diseases, thereby contributing to advancements in healthcare.

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.

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

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

Electrocardiographic Imaging Using a Spatio-Temporal Basis of Body Surface Potentials-Application to Atrial Ectopic Activity

Electrocardiographic imaging (ECGI) strongly relies on a priori assumptions and additional information to overcome ill-posedness. The major challenge of obtaining good reconstructions consists in finding ways to add information that effectively restricts the solution space without violating properties of the sought solution. In this work, we attempt to address this problem by constructing a spatio-temporal basis of body surface potentials (BSP) from simulations of many focal excitations. Measured BSPs are projected onto this basis and reconstructions are expressed as linear combinations of corresponding transmembrane voltage (TMV) basis vectors. The novel method was applied to simulations of 100 atrial ectopic foci with three different conduction velocities. Three signal-to-noise ratios (SNR) and bases of six different temporal lengths were considered. Reconstruction quality was evaluated using the spatial correlation coefficient of TMVs as well as estimated local activation times (LAT). The focus localization error was assessed by computing the geodesic distance between true and reconstructed foci. Compared with an optimally parameterized Tikhonov-Greensite method, the BSP basis reconstruction increased the mean TMV correlation by up to 22, 24, and 32% for an SNR of 40, 20, and 0 dB, respectively. Mean LAT correlation could be improved by up to 5, 7, and 19% for the three SNRs. For 0 dB, the average localization error could be halved from 15.8 to 7.9 mm. For the largest basis length, the localization error was always below 34 mm. In conclusion, the new method improved reconstructions of atrial ectopic activity especially for low SNRs. Localization of ectopic foci turned out to be more robust and more accurate. Preliminary experiments indicate that the basis generalizes to some extent from the training data and may even be applied for reconstruction of non-ectopic activity.

Wavelet-promoted sparsity for non-invasive reconstruction of electrical activity of the heart

We investigated a novel sparsity-based regularization method in the wavelet domain of the inverse problem of electrocardiography that aims at preserving the spatiotemporal characteristics of heart-surface potentials. In three normal, anesthetized dogs, electrodes were implanted around the epicardium and body-surface electrodes were attached to the torso. Potential recordings were obtained simultaneously on the body surface and on the epicardium. A CT scan was used to digitize a homogeneous geometry which consisted of the body-surface electrodes and the epicardial surface. A novel multitask elastic-net-based method was introduced to regularize the ill-posed inverse problem. The method simultaneously pursues a sparse wavelet representation in time-frequency and exploits correlations in space. Performance was assessed in terms of quality of reconstructed epicardial potentials, estimated activation and recovery time, and estimated locations of pacing, and compared with performance of Tikhonov zeroth-order regularization. Results in the wavelet domain obtained higher sparsity than those in the time domain. Epicardial potentials were non-invasively reconstructed with higher accuracy than with Tikhonov zeroth-order regularization (p < 0.05), and recovery times were improved (p < 0.05). No significant improvement was found in terms of activation times and localization of origin of pacing. Next to improved estimation of recovery isochrones, which is important when assessing substrate for cardiac arrhythmias, this novel technique opens potentially powerful opportunities for clinical application, by allowing to choose wavelet bases that are optimized for specific clinical questions. Graphical Abstract The inverse problem of electrocardiography is to reconstruct heart-surface potentials from recorded bodysurface electrocardiograms (ECGs) and a torso-heart geometry. However, it is ill-posed and solving it requires additional constraints for regularization. We introduce a regularization method that simultaneously pursues a sparse wavelet representation in time-frequency and exploits correlations in space. Our approach reconstructs epicardial (heart-surface) potentials with higher accuracy than common methods. It also improves the reconstruction of recovery isochrones, which is important when assessing substrate for cardiac arrhythmias. This novel technique opens potentially powerful opportunities for clinical application, by allowing to choose wavelet bases that are optimized for specific clinical questions.

Scalable and Accurate ECG Simulation for Reaction-Diffusion Models of the Human Heart

Realistic electrocardiogram (ECG) simulation with numerical models is important for research linking cellular and molecular physiology to clinically observable signals, and crucial for patient tailoring of numerical heart models. However, ECG simulation with a realistic torso model is computationally much harder than simulation of cardiac activity itself, so that many studies with sophisticated heart models have resorted to crude approximations of the ECG. This paper shows how the classical concept of electrocardiographic lead fields can be used for an ECG simulation method that matches the realism of modern heart models. The accuracy and resource requirements were compared to those of a full-torso solution for the potential and scaling was tested up to 14,336 cores with a heart model consisting of 11 million nodes. Reference ECGs were computed on a 3.3 billion-node heart-torso mesh at 0.2 mm resolution. The results show that the lead-field method is more efficient than a full-torso solution when the number of simulated samples is larger than the number of computed ECG leads. While the initial computation of the lead fields remains a hard and poorly scalable problem, the ECG computation itself scales almost perfectly and, even for several hundreds of ECG leads, takes much less time than the underlying simulation of cardiac activity.

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.

Three-Dimensional Visualization of Myocardial Ischemia Based on the Standard Twelve-Lead Electrocardiogram

A novel method was proposed for transforming the ischemic information in the 12-lead electrocardiogram (ECG) into the pseudo-color pattern displayed on a 3D heart model based on the projection of a ST injury vector in this study. The projection of the ST injury vector at a point on the heart surface was used for identifying the presence of myocardial ischemia by the difference between the projection value and the detection threshold. Supposing that myocardial ischemia was uniform and continuous, the location and range of myocardial ischemia could be accurately calculated and visually displayed in a color-encoding way. The diagnoses of the same patient were highly consistent (kappa coefficient k = 0.9030) between the proposed method used by ordinary people lacking medical knowledge and the standard 12-lead ECG used by experienced cardiologists. In addition, the diagnostic accuracy of the proposed method was further confirmed by the coronary angiography. The results of this study provide a new way to promote the development of the 3D visualization of the standard 12-lead ECG, which has a great help for inexperienced doctors or ordinary family members in their diagnosis of patients with myocardial ischemia.

Noninvasive Imaging of High-Frequency Drivers and Reconstruction of Global Dominant Frequency Maps in Patients With Paroxysmal and Persistent Atrial Fibrillation

OBJECTIVE

Highest dominant-frequency (DF) drivers maintaining atrial fibrillation (AF) activities are effective ablation targets for restoring sinus rhythms in patients. This study aims to investigate whether AF drivers with highest activation rate can be noninvasively localized by means of a frequency-based cardiac electrical imaging (CEI) technique, which may aid in the planning of ablation strategy and the investigation of the underlying mechanisms of AF.

METHOD

A total of seven out of 13 patients were recorded with spontaneous paroxysmal or persistent AF and analyzed. The biatrial DF maps were reconstructed by coupling 5-s BSPM with CT-determined patient geometry. The CEI results were compared with ablation sites and DFs found from BSPMs.

RESULTS

CEI imaged left-to-right maximal frequency gradient (7.42 ± 0.66 Hz versus 5.85 ± 1.2 Hz, LA versus RA, p < 0.05) in paroxysmal AF patients. Patients with persistent AF were imaged with a loss of the intrachamber frequency gradient and a dispersion of the fast sources in both chambers. CEI was able to capture the AF behaviors, which were characterized by short-term stability, dynamic transition, and spatial repetition of the highest DF sites. The imaged highest DF sites were consistent with ablation sites in patients studied.

CONCLUSIONS

The frequency-based CEI allows localization of AF drivers with highest DF and characterization of the spatiotemporal frequency behaviors, suggesting the possibility for individualizing treatment strategy and advancing understanding of the underlying AF mechanisms.

SIGNIFICANCE

The establishment of noninvasive imaging techniques localizing AF drivers would facilitate management of this significant cardiac arrhythmia.

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.

Temporal Sparse Promoting Three Dimensional Imaging of Cardiac Activation

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

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

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

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.

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

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

Reconstruction of normal and abnormal gastric electrical sources using a potential based inverse method

The use of cutaneous recordings to non-invasively characterize gastric slow waves has had limited clinical acceptance, primarily due to the uncertainty in relating the recorded signal to the underlying gastric slow waves. In this study we aim to distinguish and quantitatively reconstruct different slow wave patterns using an inverse algorithm. Slow wave patterns corresponding to normal, retrograde and uncoupled activity at different frequencies were imposed on a stomach surface model. Gaussian noise (10% peak-to-peak) was added to cutaneous potentials and the Greensite-Tikhonov inverse method was used to reconstruct the potentials on the stomach. The effectiveness of the number or location of electrodes on the accuracy of the inverse solutions was investigated using four different electrode configurations. Results showed the reconstructed solutions were able to reliably distinguish the different slow wave patterns and waves with lower frequency were better correlated to the known solution than those with higher. The use of up to 228 electrodes improved the accuracy of the inverse solutions. However, the use of 120 electrodes concentrated around the stomach was able to achieve similar results. The most efficient electrode configuration for our model involved 120 electrodes with an inter-electrode distance of 32 mm.

Using transmural regularization and dynamic modeling for noninvasive cardiac potential imaging of endocardial pacing with imprecise thoracic geometry

Cardiac electrical imaging from body surface potential measurements is increasingly being seen as a technology with the potential for use in the clinic, for example for pre-procedure planning or during-treatment guidance for ventricular arrhythmia ablation procedures. However several important impediments to widespread adoption of this technology remain to be effectively overcome. Here we address two of these impediments: the difficulty of reconstructing electric potentials on the inner (endocardial) as well as outer (epicardial) surfaces of the ventricles, and the need for full anatomical imaging of the subject's thorax to build an accurate subject-specific geometry. We introduce two new features in our reconstruction algorithm: a nonlinear low-order dynamic parameterization derived from the measured body surface signals, and a technique to jointly regularize both surfaces. With these methodological innovations in combination, it is possible to reconstruct endocardial activation from clinically acquired measurements with an imprecise thorax geometry. In particular we test the method using body surface potentials acquired from three subjects during clinical procedures where the subjects' hearts were paced on their endocardia using a catheter device. Our geometric models were constructed using a set of CT scans limited in axial extent to the immediate region near the heart. The catheter system provides a reference location to which we compare our results. We compare our estimates of pacing site localization, in terms of both accuracy and stability, to those reported in a recent clinical publication , where a full set of CT scans were available and only epicardial potentials were reconstructed.

Realistic training data improve noninvasive reconstruction of heart-surface potentials

The inverse problem of electrocardiography is to noninvasively reconstruct electrical heart activity from body-surface electrocardiograms. Solving this problem is beneficial to clinical practice. However, reconstructions cannot be obtained straightforwardly due to the ill-posed nature of this problem. Therefore, regularization schemes are necessary to arrive at realistic solutions. To date, no electrophysiological data have been used in reconstruction methods and regularization schemes. In this study, we used a training set of simulated heart-surface potentials to create a realistic basis for reconstructions of electrical cardiac activity. We tested this method in computer simulations and in one patient. The quality of reconstruction improved significantly after projection of the results of traditional regularization methods on this new basis, both in silico (p&#60;0.01) and in vivo (p&#60;0.05). Thus, we demonstrate that the novel concept of applying electrophysiological data might be useful to improve noninvasive reconstruction of electrical heart activity.

Noninvasive cardiac activation imaging of ventricular arrhythmias during drug-induced QT prolongation in the rabbit heart

BACKGROUND

Imaging myocardial activation from noninvasive body surface potentials promises to aid in both cardiovascular research and clinical medicine.

OBJECTIVE

To investigate the ability of a noninvasive 3-dimensional cardiac electrical imaging technique for characterizing the activation patterns of dynamically changing ventricular arrhythmias during drug-induced QT prolongation in rabbits.

METHODS

Simultaneous body surface potential mapping and 3-dimensional intracardiac mapping were performed in a closed-chest condition in 8 rabbits. Data analysis was performed on premature ventricular complexes, couplets, and torsades de pointes (TdP) induced during intravenous administration of clofilium and phenylephrine with combinations of various infusion rates.

RESULTS

The drug infusion led to a significant increase in the QT interval (from 175 ± 7 to 274 ± 31 ms) and rate-corrected QT interval (from 183 ± 5 to 262 ± 21 ms) during the first dose cycle. All the ectopic beats initiated by a focal activation pattern. The initial beat of TdPs arose at the focal site, whereas the subsequent beats were due to focal activity from different sites or 2 competing focal sites. The imaged results captured the dynamic shift of activation patterns and were in good correlation with the simultaneous measurements, with a correlation coefficient of 0.65 ± 0.02 averaged over 111 ectopic beats. Sites of initial activation were localized to be ~5 mm from the directly measured initiation sites.

CONCLUSIONS

The 3-dimensional cardiac electrical imaging technique could localize the origin of activation and image activation sequence of TdP during QT prolongation induced by clofilium and phenylephrine in rabbits. It offers the potential to noninvasively investigate the proarrhythmic effects of drug infusion and assess the mechanisms of arrhythmias on a beat-to-beat basis.

A fast regularized least-squares method for retinal vascular oxygen tension estimation using a phosphorescence lifetime imaging model

Background

Monitoring retinal oxygenation is of primary importance in detecting the presence of some common eye diseases. To improve the estimation of oxygen tension in retinal vessels, regularized least-squares (RLS) method was shown to be very effective compared with the conventional least-squares (LS) estimation. In this study, we propose an accelerated RLS estimation method for the problem of assessing the oxygenation of retinal vessels from phosphorescence lifetime images.

Methods

In the previous work, gradient descent algorithms were used to find the minimum of the RLS cost function. This approach is computationally expensive, especially when the oxygen tension map is large. In this study, using a closed-form solution of the RLS estimation and some inherent properties of the problem at hand, the RLS process is reduced to the weighted averaging of the LS estimates. This decreases the computational complexity of the RLS estimation considerably without sacrificing its performance.

Results

Performance analyses are conducted using both real and simulated data sets. In terms of computational complexity, the proposed RLS estimation method is significantly better than RLS methods that use gradient descent algorithms to find the minimum of the cost function. Additionally, there is no significant difference between the estimates acquired by the proposed and conventional RLS estimation methods.

Conclusion

The proposed RLS estimation method for computing the retinal oxygen tension is computationally efficient, and produces estimates with negligible difference from those obtained by iterative RLS methods. Further, the results of this study can be applied to other lifetime imaging problems that have similar properties.

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.

Reconstruction of multiple gastric electrical wave fronts using potential-based inverse methods

One approach for non-invasively characterizing gastric electrical activity, commonly used in the field of electrocardiography, involves solving an inverse problem whereby electrical potentials on the stomach surface are directly reconstructed from dense potential measurements on the skin surface. To investigate this problem, an anatomically realistic torso model and an electrical stomach model were used to simulate potentials on stomach and skin surfaces arising from normal gastric electrical activity. The effectiveness of the Greensite-Tikhonov or the Tikhonov inverse methods were compared under the presence of 10% Gaussian noise with either 84 or 204 body surface electrodes. The stability and accuracy of the Greensite-Tikhonov method were further investigated by introducing varying levels of Gaussian signal noise or by increasing or decreasing the size of the stomach by 10%. Results showed that the reconstructed solutions were able to represent the presence of propagating multiple wave fronts and the Greensite-Tikhonov method with 204 electrodes performed best (correlation coefficients of activation time: 90%; pacemaker localization error: 3 cm). The Greensite-Tikhonov method was stable with Gaussian noise levels up to 20% and 10% change in stomach size. The use of 204 rather than 84 body surface electrodes improved the performance; however, for all investigated cases, the Greensite-Tikhonov method outperformed the Tikhonov method.

MANIFOLD LEARNING FOR ANALYSIS OF LOW-ORDER NONLINEAR DYNAMICS IN HIGH-DIMENSIONAL ELECTROCARDIOGRAPHIC SIGNALS

The dynamical structure of electrical recordings from the heart or torso surface is a valuable source of information about cardiac physiological behavior. In this paper, we use an existing data-driven technique for manifold identification to reveal electrophysiologically significant changes in the underlying dynamical structure of these signals. Our results suggest that this analysis tool characterizes and differentiates important parameters of cardiac bioelectric activity through their dynamic behavior, suggesting the potential to serve as an effective dynamic constraint in the context of inverse solutions.

Reconstruction of multiple gastric electrical wave fronts using potential based inverse methods

The ability to reconstruct gastric electrical activity (termed slow waves) non-invasively from potential field measurements made on the torso surface would be a useful tool to aid in the clinical diagnosis of a number of gastric disorders. This is mathematically akin to the inverse problem of electrocardiography. To investigate this problem, an anatomically realistic torso model and an electrical stomach model were used to simulate potentials on the stomach and skin surfaces arising from normal gastric electrical activity. Gaussian noise was added to the torso potentials to represent experimental signal noise. The stomach potentials, activation profiles and gastric slow wave velocities were inversely reconstructed from the torso potentials, using the Tikhonov-Greensite inverse method with regularisation determined using an L-curve method. The inverse solutions were then compared with the known input solutions. The reconstructed solutions were able to represent the presence of multiple propagating wave fronts, determine average activation times to within 5 s and average velocities to within 1 mm/s. When more virtual body surface electrodes were used in the inverse calculations, the accuracy of the reconstructed activity improved.

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 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.

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.

Three-dimensional imaging of ventricular activation and electrograms from intracavitary recordings

Three-dimensional (3-D) mapping of the ventricular activation is of importance to better understand the mechanisms and facilitate management of ventricular arrhythmias. The goal of this study was to develop and evaluate a 3-D cardiac electrical imaging (3DCEI) approach for imaging myocardial electrical activation from the intracavitary electrograms (EGs) and heart-torso geometry information over the 3-D volume of the heart. The 3DCEI was evaluated in a swine model undergoing intracavitary noncontact mapping (NCM). Each animal's preoperative MRI data were acquired to construct the heart-torso model. NCM was performed with the Ensite 3000 system during acute ventricular pacing. Subsequent 3DCEI analyses were performed on the measured intracavitary EGs. The estimated initial sites (ISs) were compared to the precise pacing locations, and the estimated activation sequences (ASs) and EGs were compared to those recorded by the NCM system over the endocardial surface. In total, six ventricular sites from two pigs were paced. The averaged localization error of IS was 6.7 ± 2.6 mm. The endocardial ASs and EGs as a subset of the estimated 3-D solutions were consistent with those reconstructed from the NCM system. The present results demonstrate that the intracavitary-recording-based 3DCEI approach can well localize the sites of initiation and can obtain physiologically reasonable ASs as well as EGs in an in vivo setting under control/paced conditions. This study suggests the feasibility of tomographic imaging of 3-D ventricular activation and 3-D EGs from intracavitary recordings.

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.

Noninvasive three-dimensional cardiac activation imaging on a rabbit model

Three-dimensional cardiac activation imaging (3-DCAI) aims at imaging the activation sequence throughout the 3-D myocardium. In the present study, the performance of 3-DCAI was validated through both in vivo animal experiments and computer simulations under a pacing protocol. The non-invasively imaged activation sequence from body surface potential maps (BSPMs) was quantitatively compared with the measured activation sequence obtained from the simultaneous intramural recording using a 3-D intra-cardiac mapping technique in a rabbit model. In addition, computer simulations were conducted to provide further assessment of the performance of the 3-DCAI algorithm in a realistic-geometry rabbit heart-torso model. The encouraging results suggest that 3-DCAI can non-invasively image the activation sequence and localize the origin of activation with good accuracy.

Cardiac source localization by means of a single moving dipole solution during endocardial pacing in an animal model

The accuracy of localizing the initiation site of cardiac activation by noninvasively estimating a single moving dipole (SMD) was investigated in a swine model. Body surface potential mapping (BSPM) and intracavitary noncontact mapping (NCM) were performed simultaneously during acute left ventricular (LV) endocardial pacing. For each animal, the boundary element model was constructed from preoperative magnetic resonance images (MRI). In each pacing study, the initiation site was localized by inversely estimating the location of an SMD from BSPM data. The results were compared with the precise pacing sites recorded by the NCM system. In total, four pacing sites from two pigs were analyzed, and the averaged source localization error was 16.8 +/- 2.3 mm. The present results indicate the potential of localizing focal cardiac events by estimating single moving dipole.

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.

Application of L1-norm regularization to epicardial potential solution of the inverse electrocardiography problem

The electrocardiographic inverse problem of computing epicardial potentials from multi-electrode body-surface ECG measurements, is an ill-posed problem. Tikhonov regularization is commonly employed, which imposes penalty on the L2-norm of the potentials (zero-order) or their derivatives. Previous work has indicated superior results using L2-norm of the normal derivative of the solution (a first order regularization). However, L2-norm penalty function can cause considerable smoothing of the solution. Here, we use the L1-norm of the normal derivative of the potential as a penalty function. L1-norm solutions were compared to zero-order and first-order L2-norm Tikhonov solutions and to measured 'gold standards' in previous experiments with isolated canine hearts. Solutions with L1-norm penalty function (average relative error [RE] = 0.36) were more accurate than L2-norm (average RE = 0.62). In addition, the L1-norm method localized epicardial pacing sites with better accuracy (3.8 +/- 1.5 mm) compared to L2-norm (9.2 +/- 2.6 mm) during pacing in five pediatric patients with congenital heart disease. In a pediatric patient with Wolff-Parkinson-White syndrome, the L1-norm method also detected and localized two distinct areas of early activation around the mitral valve annulus, indicating the presence of two left-sided pathways which were not distinguished using L2 regularization.

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.

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.

Three-dimensional ventricular activation imaging by means of equivalent current source modeling and estimation

This paper presents a novel electrocardiographic inverse approach for imaging the 3-D ventricular activation sequence based on the modeling and estimation of the equivalent current density throughout the entire myocardial volume. The spatio-temporal coherence of the ventricular excitation process is utilized to derive the activation time from the estimated time course of the equivalent current density. At each time instant during the period of ventricular activation, the distributed equivalent current density is noninvasively estimated from body surface potential maps (BSPM) using a weighted minimum norm approach with a spatio-temporal regularization strategy based on the singular value decomposition of the BSPMs. The activation time at any given location within the ventricular myocardium is determined as the time point with the maximum local current density estimate. Computer simulation has been performed to evaluate the capability of this approach to image the 3-D ventricular activation sequence initiated from a single pacing site in a physiologically realistic cellular automaton heart model. The simulation results demonstrate that the simulated "true" activation sequence can be accurately reconstructed with an average correlation coefficient of 0.90, relative error of 0.19, and the origin of ventricular excitation can be localized with an average localization error of 5.5 mm for 12 different pacing sites distributed throughout the ventricles.

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.

On the possibility for computing the transmembrane potential in the heart with a one shot method: an inverse problem

We analyze the possibility for using body surface potential maps (BSPMs), a priori information about the voltage distribution in the heart and the bidomain equations to compute the transmembrane potential throughout the myocardium. Our approach is defined in terms of an inverse problem for elliptic partial differential equations (PDEs). More precisely, we formulate it in terms of an output least squares framework in which a goal functional is minimized subject to suitable PDE constraints. The problem is highly unstable and, even under optimal recording conditions, it does not have a unique solution. We propose a methodology for stabilizing and enforcing uniqueness for this inverse problem. Moreover, a fully implicit method for solving the involved minimization problem is presented. In other words, we show how one may solve it in terms of a system consisting of three linear elliptic PDEs, i.e. we derive a so-called one shot method (also commonly referred to as an all-at-once method). Finally, our theoretical findings are illuminated by a series of numerical experiments. These examples indicate that, in the presence of regional ischemia, it might be possible to approximately recover the transmembrane potential during the resting and plateau phases of the heart cycle. This is probably due to the fact that rather accurate a priori information is available during these time intervals. The problem of computing the transmembrane potential at an arbitrary time instance during a heart beat is still an open problem.

Three-dimensional activation sequence imaging in a rabbit model

This paper evaluates a biophysical-model based three-dimensional (3-D) activation sequence imaging approach in a rabbit model. In this approach, cardiac electrical sources within the myocardial volume are represented by distributed equivalent current densities; a realistic heart-torso volume conductor model is built from the CT scans of the rabbit's torso; spatial-temporal regularization is applied when solving the inverse problem of current density estimation; and the activation time at every myocardial location is determined as the time point when the estimated local current density reaches its maximum amplitude. Computer simulations have been conducted to image the activation sequence initiated by pacing 11 sites throughout the ventricular myocardium. Under 20muV Gaussian white noise, the average correlation coefficient (CC) between the imaged and the simulated activation sequences is 0.92, the average relative error (RE) is 0.19, and the average localization error (LE) is 4.99mm averaged over 11 pacing sites. Even under 60muV Gaussian white noise, reasonable results can still be achieved by the present approach with CC = 0.89, RE = 0.22, and LE = 6.85mm. The simulation results demonstrate that the present 3-D imaging approach has reasonable accuracy and robustness against recording noises.

Noninvasive reconstruction of three-dimensional ventricular activation sequence from the inverse solution of distributed equivalent current density

We propose a new electrocardiographic (ECG) inverse approach for imaging the three-dimensional (3-D) ventricular activation sequence based on the modeling and estimation of the equivalent current density throughout the entire volume of the ventricular myocardium. The spatio-temporal coherence of the ventricular excitation process has been utilized to derive the activation time from the estimated time course of the equivalent current density. In the present study, we explored four different linear inverse algorithms (the minimum norm and weighted minimum norm estimates in combination with two regularization schemes: the instant-by-instant regularization and the isotropy method) to estimate the current density at each time instant during the ventricular depolarization. The activation time at any given location within the ventricular myocardium was determined as the time point with the occurrence of the maximum local current density estimate. Computer simulations were performed to evaluate this approach using single- and dual-site pacing protocols in a physiologically realistic cellular automaton heart model. The performance and stability of the proposed approach was evaluated with respect to the various levels of measurement noise (0, 5, 10, 20, 40, and 60 microV), the various numbers of ECG electrodes and the modeling errors on the torso geometry and heart position. The simulation results demonstrate that: 1) the single-site paced 3-D activation sequence can be well reconstructed from 200-channel body surface potential maps with additive Gaussian white noise of 20 microV (correlation coefficient = 0.90, relative error = 0.19, and localization error = 5.49 mm); 2) a higher imaging accuracy can be obtained when the activation is initiated from the left/right ventricle (LV/RV) compared to from the septum; 3) the isotropy method gives rise to a better performance than the conventional instant-by-instant regularization; 4) a decreased imaging accuracy results from a larger noise level, a fewer number of electrodes, or the volume conductor modeling errors; however, a reasonable imaging accuracy can still be obtained with a 60 microV noise level, 64 electrodes, or mild errors on both the torso geometry and heart position, respectively; 5) the dual-site paced 3-D activation sequence can be imaged when the two sites are paced either simultaneously or with a time delay of 20 ms; 6) two pacing sites can be resolved and localized in the imaged 3-D activation sequence when they are located at the contralateral sides of ventricles or at the ventricular lateral wall and the apex, respectively.

Wavefront-based models for inverse electrocardiography

We introduce two wavefront-based methods for the inverse problem of electrocardiography, which we term wavefront-based curve reconstruction (WBCR) and wavefront-based potential reconstruction (WBPR). In the WBCR approach, the epicardial activation wavefront is modeled as a curve evolving on the heart surface, with the evolution governed by factors derived phenomenologically from prior measured data. The body surface potential/wavefront relationship is modeled via an intermediate mapping of wavefront to epicardial potentials, again derived phenomenologically. In the WBPR approach, we iteratively construct an estimate of epicardial potentials from an estimated wavefront curve according to a simplified model and use it as an initial solution in a Tikhonov regularization scheme. Initial simulation results using measured canine epicardial data show considerable improvement in reconstructing activation wavefronts and epicardial potentials with respect to standard Tikhonov solutions. In particular the WBCR method accurately finds the anisotropic propagation early after epicardial pacing, and the WBPR method finds the wavefront (regions of sharp gradient of the potential) both accurately and with minimal smoothing.

Use of group theory in the selection and description of regularization methods for functional source imaging

Commonly, functional source imaging problems are "partial" rather than "ordinary" inverse problems--wherein the defining operator consists of component operators that individually do not address all variables of the unknown. When this ordinary-to-partial transition is minimally constrained, algebraic principles can be used to derive a favored methodology--which we do here. The resulting Isotropy method is compared to two other regularization methods proposed for functional source imaging (Kalman and Joint Regularization). This theoretical support for the favored status of the Isotropy method is consistent with its favorable computational performance in low prior information settings, as indicated in recent publications.

Computing the Size and Location of Myocardial Ischemia Using Measurements of ST-Segment Shift

It is well known that the presence of myocardial ischemia can be observed as a shift in the ST segment of an electrocardiogram (ECG) recording. The question we address in this paper is whether or not ST shift can be used to compute approximations of the size and location of the ischemic region. We begin by investigating a cost functional (measuring the difference between synthetic recorded data and simulated values of ST shift) for a parameter identification problem to locate the ischemic region. We then formulate a more flexible representation of the ischemia using a level set framework and solve the associated minimization problem for the size and position of the ischemia. We apply this framework to a set of ECG data generated by the Bidomain model using the cell model of Winslow et al. Based on this data, we show that values of ST shift recorded at the body surface are capable of identifying the position and (roughly) the size of the ischemia.

Visualization of three-dimensional cardiac electrical excitation using standard heart model and anterior and posterior magnetocardiogram

Our aim in this study is to obtain novel three-dimensional (3-D) images of cardiac electrical excitation that include morphological information on the whole heart. We obtain these 3-D images by projecting anterior and posterior two-dimensional (2-D) current-arrow maps (CAMs) onto a 3-D standard heart model. This standard heart model is adjusted to the individual subject's heart position by using the coordinates of the sinus node, which are obtained from magnetocardiogram (MCG) signals. The anterior and posterior CAMs are calculated by taking the orthogonal partial derivatives of the normal component of the anterior and posterior MCGs. After adjusting the base current values of the anterior and posterior CAMs, the adjusted CAMs are projected onto the standard heart model. We generated the projected CAMs (PCAMs) of the six phases (atrial, and ventricular, excitation) for seven healthy subjects. The validity of PCAM was evaluated by extracting the maximal current directions and positions from the PCAMs. The maximal current directions and positions during each excitation phase were almost in the same in the seven healthy subjects. Therefore, the PCAMs give us a clear view of the anterior and posterior myocardial excitation for the respective electrophysiological phases.