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

Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey

Cardiac digital twins (CDTs) are personalized virtual representations used to understand complex cardiac mechanisms. A critical component of CDT development is solving the ECG inverse problem, which enables the reconstruction of cardiac sources and the estimation of patient-specific electrophysiology (EP) parameters from surface ECG data. Despite challenges from complex cardiac anatomy, noisy ECG data, and the ill-posed nature of the inverse problem, recent advances in computational methods have greatly improved the accuracy and efficiency of ECG inverse inference, strengthening the fidelity of CDTs. This paper aims to provide a comprehensive review of the methods for solving ECG inverse problems, their validation strategies, their clinical applications, and their future perspectives. For the methodologies, we broadly classify state-of-the-art approaches into two categories: deterministic and probabilistic methods, including both conventional and deep learning-based techniques. Integrating physics laws with deep learning models holds promise, but challenges such as capturing dynamic electrophysiology accurately, accessing accurate domain knowledge, and quantifying prediction uncertainty persist. Integrating models into clinical workflows while ensuring interpretability and usability for healthcare professionals is essential. Overcoming these challenges will drive further research in CDTs.

A transferable in-silico augmented ischemic model for virtual myocardial perfusion imaging and myocardial infarction detection

This paper proposes an innovative approach to generate a generalized myocardial ischemia database by modeling the virtual electrophysiology of the heart and the 12-lead electrocardiography projected by the in-silico model can serve as a ready-to-use database for automatic myocardial infarction/ischemia (MI) localization and classification. Although the virtual heart can be created by an established technique combining the cell model with personalized heart geometry to observe the spatial propagation of depolarization and repolarization waves, we developed a strategy based on the clinical pathophysiology of MI to generate a heterogeneous database with a generic heart while maintaining clinical relevance and reduced computational complexity. First, the virtual heart is simplified into 11 regions that match the types and locations, which can be diagnosed by 12-lead ECG; the major arteries were divided into 3-5 segments from the upstream to the downstream based on the general anatomy. Second, the stenosis or infarction of the major or minor coronary artery branches can cause different perfusion drops and infarct sizes. We simulated the ischemic sites in different branches of the arteries by meandering the infarction location to elaborate on possible ECG representations, which alters the infraction's size and changes the transmembrane potential (TMP) of the myocytes associated with different levels of perfusion drop. A total of 8190 different case combinations of cardiac potentials with ischemia and MI were simulated, and the corresponding ECGs were generated by forward calculations. Finally, we trained and validated our in-silico database with a sparse representation classification (SRC) and tested the transferability of the model on the real-world Physikalisch Technische Bundesanstalt (PTB) database. The overall accuracies for localizing the MI region on the PTB data achieved 0.86, which is only 2% drop compared to that derived from the simulated database (0.88). In summary, we have shown a proof-of-concept for transferring an in-silico model to real-world database to compensate for insufficient data.

Localization of the ventricular pacing site from BSPM and standard 12-lead ECG: a comparison study

Inverse ECG imaging methods typically require 32-250 leads to create body surface potential maps (BSPM), limiting their routine clinical use. This study evaluated the accuracy of PaceView inverse ECG method to localize the left or right ventricular (LV and RV, respectively) pacing leads using either a 99-lead BSPM or the 12-lead ECG. A 99-lead BSPM was recorded in patients with cardiac resynchronization therapy (CRT) during sinus rhythm and sequential LV/RV pacing. The non-contrast CT was performed to localize precisely both ECG electrodes and CRT leads. From a BSPM, nine signals were selected to obtain the 12-lead ECG. Both BSPM and 12-lead ECG were used to localize the RV and LV lead, and the localization error was calculated. Consecutive patients with dilated cardiomyopathy, previously implanted with a CRT device, were enrolled (n = 19). The localization error for the RV/LV lead was 9.0 [IQR 4.8-13.6] / 7.7 [IQR 0.0-10.3] mm using the 12-lead ECG and 9.1 [IQR 5.4-15.7] / 9.8 [IQR 8.6-13.1] mm for the BSPM. Thus, the noninvasive lead localization using the 12-lead ECG was accurate enough and comparable to 99-lead BSPM, potentially increasing the capability of 12-lead ECG for the optimization of the LV/RV pacing sites during CRT implant or for the most favorable programming.

Cardiac Activation Maps Reconstruction: A Comparative Study Between Data-Driven and Physics-Based Methods

One of the essential diagnostic tools of cardiac arrhythmia is activation mapping. Noninvasive current mapping procedures include electrocardiographic imaging. It allows reconstructing heart surface potentials from measured body surface potentials. Then, activation maps are generated using the heart surface potentials. Recently, a study suggests to deploy artificial neural networks to estimate activation maps directly from body surface potential measurements. Here we carry out a comparative study between the data-driven approach DirectMap and noninvasive classic technique based on reconstructed heart surface potentials using both Finite element method combined with L1-norm regularization (FEM-L1) and the spatial adaptation of Time-delay neural networks (SATDNN-AT). In this work, we assess the performance of the three approaches using a synthetic single paced-rhythm dataset generated on the atria surface. The results show that data-driven approach DirectMap quantitatively outperforms the two other methods. In fact, we observe an absolute activation time error and a correlation coefficient, respectively, equal to 7.20 ms, 93.2% using DirectMap, 14.60 ms, 76.2% using FEM-L1 and 13.58 ms, 79.6% using SATDNN-AT. In addition, results show that data-driven approaches (DirectMap and SATDNN-AT) are strongly robust against additive gaussian noise compared to FEM-L1.

Prediction of atrial fibrillation using the recurrence complex network of body surface potential mapping signals

OBJECTIVE:

Atrial fibrillation (AF) is the most common type of persistent arrhythmia. Early diagnosis and intervention of AF is essential to avert the further fatality. The technique of noninvasive electrical mapping, especially the body surface potential mapping (BSPM), has a more practical application in the study of predicting AF, when compared with the invasive electrical mapping methods such as the epicardial mapping and interventional catheter mapping. However, the prediction of AF with noninvasive signals has been inadequately studied. Thus, the aim of this paper was to analyze the properties of atrial dynamic system based on the noninvasive BSPM signals (BSPMs), using the recurrence complex network, and consequently to evaluate its role in predicting the recurrence of AF in clinical aspect.

METHOD:

Twelve patients with persistent AF were included in this study. Their preoperative and postoperative BSPMs were recorded. Initially, the preoperative BSPMs were transformed into the recurrence complex network to characterize the complexity property of the atria. Subsequently, the parameters of recurrence ratio (REC), determinism (DET), entropy of the diagonal structure distribution (ENTR), and laminarity (LAM) were calculated. Furthermore, the difference in the parameters in the four regions of the body and the difference obtained from the dominant frequency (DF) method were compared. Finally, the results obtained for the atrial dynamic system complexity from a 12-lead electrocardiogram (ECG) from the BSPMs were discussed.

RESULTS:

Our study revealed that the patients whose REC is greater than an average threshold, and with a lower LAM presented a much higher possibility of AF recurrence, after the AF surgery.

CONCLUSIONS:

The recurrence complex network is a useful and convenient way to evaluate the nonlinear properties of the BSPMs in patients with AF. It has good immunity to the lead position and has a potential role in the understanding of predicting the recurrence of AF.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Noninvasive Activation Imaging of Ventricular Arrhythmias by Spatial Gradient Sparse in Frequency Domain-Application to Mapping Reentrant Ventricular Tachycardia

The aim of this paper is to develop and evaluate a novel imaging method [spatial gradient sparse in frequency domain (SSF)] for the reconstruction of activation sequences of ventricular arrhythmia from noninvasive body surface potential map (BSPM) measurements. We formulated and solved the electrocardiographic inverse problem in the frequency domain, and the activation time was encoded in the phase information of the imaging solution. A cellular automaton heart model was used to generate focal ventricular tachycardia (VT). Different levels of Gaussian white noise were added to simulate noise-contaminated BSPM. The performance of SSF was compared with that of weighted minimum norm inverse solution. We also evaluated the method in a swine model with simultaneous intracardiac and body surface recordings. Four reentrant VTs were observed in pigs with myocardial infarction generated by left anterior descending artery occlusion. The imaged activation sequences of reentrant VTs were compared with those obtained from intracardiac electrograms. In focal VT simulation, SSF has increased the correlation coefficient (CC) by 5% and decreased localization errors (LEs) by 2.7 mm on average under different noise levels. In the animal validation with reentrant VT, SSF has achieved an average CC of 88% and an average LE of 6.3 mm in localizing the earliest and latest activation site in the reentry circuit. Our promising results suggest that the SSF provides noninvasive imaging capability of detecting and mapping macro-reentrant circuits in 3-D ventricular space. The SSF may become a useful imaging tool of identifying and localizing the potential targets for ablation of focal and reentrant VT.

Evaluation of multivariate adaptive non-parametric reduced-order model for solving the inverse electrocardiography problem: a simulation study

In the inverse electrocardiography (ECG) problem, the goal is to reconstruct the heart's electrical activity from multichannel body surface potentials and a mathematical model of the torso. Over the years, researchers have employed various approaches to solve this ill-posed problem including regularization, optimization, and statistical estimation. It is still a topic of interest especially for researchers and clinicians whose goal is to adopt this technique in clinical applications. Among the wide range of mathematical tools available in the fields of operational research, inverse problems, optimization, and parameter estimation, spline-based techniques have been applied to inverse problems in several areas. If proper spline bases are chosen, the complexity of the problem can be significantly reduced while increasing estimation accuracy. However, there are few studies within the context of the inverse ECG problem that take advantage of this property of the spline-based approaches. In this paper, we evaluate the performance of Multivariate Adaptive Regression Splines (MARS)-based method for the solution of the inverse ECG problem using two different collections of simulated data. The results show that the MARS-based method improves the inverse ECG solutions and is "robust" to modeling errors, especially in terms of localizing the arrhythmia sources. Graphical Abstract Multivariate adaptive non-parametric model for inverse ECG problem.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Activation recovery interval imaging of premature ventricular contraction

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

[Rhythm analysis of body surface potential mapping recordings from atrial fibrillation patients based on autocorrelation function]

The study of atrial fibrillation (AF) has been known as a hot topic of clinical concern. Body surface potential mapping (BSPM), a noninvasive electrical mapping technology, has been widely used in the study of AF. This study adopted 10 AF patients' preoperative and postoperative BSPM data (each patient's data contained 128 channels), and applied the autocorrelation function method to obtain the activation interval of the BSPM signals. The activation interval results were compared with that of manual counting method and the applicability of the autocorrelation function method was verified. Furthermore, we compared the autocorrelation function method with the commonly used fast Fourier transform (FFT) method. It was found that the autocorrelation function method was more accurate. Finally, to find a simple rule to predict the recurrence of atrial fibrillation, the autocorrelation function method was used to analyze the preoperative BSPM signals of 10 patients with persistent AF. Consequently, we found that if the patient's proportion of channels with dominant frequency larger than 2.5 Hz in the anterior left region is greater than the other three regions (the anterior right region, the posterior left region, and the posterior right region), he or she might have a higher possibility of AF recurrence. This study verified the rationality of the autocorrelation function method for rhythm analysis and concluded a simple rule of AF recurrence prediction based on this method.

Cardiac electrical dyssynchrony is accurately detected by noninvasive electrocardiographic imaging

BACKGROUND

Poor identification of electrical dyssynchrony is postulated to be a major factor contributing to the low success rate for cardiac resynchronization therapy.

OBJECTIVE

The purpose of this study was to evaluate the sensitivity of body surface mapping and electrocardiographic imaging (ECGi) to detect electrical dyssynchrony noninvasively.

METHODS

Langendorff-perfused pig hearts (n = 11) were suspended in a human torso-shaped tank, with left bundle branch block (LBBB) induced through ablation. Recordings were taken simultaneously from a 108-electrode epicardial sock and 128 electrodes embedded in the tank surface during sinus rhythm and ventricular pacing. Computed tomography provided electrode and heart positions in the tank. Epicardial unipolar electrograms were reconstructed from torso potentials using ECGi. Dyssynchrony markers from torso potentials (eg, QRS duration) or ECGi (total activation time, interventricular delay [D-LR], and intraventricular markers) were correlated with those recorded from the sock.

RESULTS

LBBB was induced (n = 8), and sock-derived activation maps demonstrated interventricular dyssynchrony (D-LR and total activation time) in all cases (P < .05) and intraventricular dyssynchrony for complete LBBB (P < .05) compared to normal sinus rhythm. Only D-LR returned to normal with biventricular pacing (P = .1). Torso markers increased with large degrees of dyssynchrony, and no reduction was seen during biventricular pacing (P > .05). Although ECGi-derived markers were significantly lower than recorded (P < .05), there was a significant strong linear relationship between ECGi and recorded values. ECGi correctly diagnosed electrical dyssynchrony and interventricular resynchronization in all cases. The latest site of activation was identified to 9.1 ± 0.6 mm by ECGi.

CONCLUSION

ECGi reliably and accurately detects electrical dyssynchrony, resynchronization by biventricular pacing, and the site of latest activation, providing more information than do body surface potentials.

Spatially Coherent Activation Maps for Electrocardiographic Imaging

OBJECTIVE

Cardiac mapping is an important diagnostic step in cardiac electrophysiology. One of its purposes is to generate a map of the depolarization sequence. This map is constructed in clinical routine either by directly analyzing cardiac electrograms (EGMs) recorded invasively or an estimate of these EGMs obtained by a noninvasive technique. Activation maps based on noninvasively estimated EGMs often show artefactual jumps in activation times. To overcome this problem, we present a new method to construct the activation maps from reconstructed unipolar EGMs.

METHODS

On top of the standard estimation of local activation time from unipolar intrinsic deflections, we propose to mutually compare the EGMs in order to estimate the delays in activation for neighboring recording locations. We then describe a workflow to construct a spatially coherent activation map from local activation times and delay estimates in order to create more accurate maps. The method is optimized using simulated data and evaluated on clinical data from 12 different activation sequences.

RESULTS

We found that the standard methodology created lines of artificially strong activation time gradient. The proposed workflow enhanced these maps significantly.

CONCLUSION

Estimating delays between neighbors is an interesting option for activation map computation in electrocardiographic imaging.

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.

Introduction to noninvasive cardiac mapping

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

Temporal Sparse Promoting Three Dimensional Imaging of Cardiac Activation

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

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.

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.

Spatial differences in corneal electroretinogram potentials measured in rat with a contact lens electrode array

Purpose

It has been known for several decades that the magnitude of the corneal electroretinogram (ERG) varies with position on the eye surface, especially in the presence of focal or asymmetric stimuli or retinal lesions. However, this phenomenon has not been well-characterized using simultaneous measurements at multiple locations on the cornea. This work provides the first characterization of spatial differences in the ERG across the rat cornea.

Methods

A contact lens electrode array was employed to record ERG potentials at 25 corneal locations simultaneously following brief full-field flash stimuli in normally sighted Long-Evans rats. These multi-electrode electroretinogram (meERG) responses were analyzed for spatial differences in a-wave and b-wave amplitudes and implicit times.

Results

Spatially distinct ERG potentials could be recorded reliably. Comparing relative amplitudes across the corneal locations suggested a slight non-uniform distribution when using full-field, near-saturating stimuli. Amplitudes of a- and b-waves were approximately 3 % lower in the inferior quadrant than in the superior quadrant of the cornea.

Conclusions

The present results comprise the start of the first normative meERG database for rat eyes and provide a basis for comparison of results from eyes with functional deficit. Robust measures of spatial differences in corneal potentials will also support optimization and validation of computational source models of the ERG. To fully utilize the information contained in the meERG data, a detailed understanding of the roles of the many determinants of local corneal potentials will eventually be required.

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.

Sequential targeted delivery of paclitaxel and camptothecin using a cross-linked "nanosponge" network for lung cancer chemotherapy

The applicability of a HVGGSSV peptide targeted "nanosponge" drug delivery system for sequential administration of a microtubule inhibitor (paclitaxel) and topoisomerase I inhibitor (camptothecin) was investigated in a lung cancer model. Schedule-dependent combination treatment with nanoparticle paclitaxel (NP PTX) and camptothecin (NP CPT) was studied in vitro using flow cytometry and confocal imaging to analyze changes in cell cycle, microtubule morphology, apoptosis, and cell proliferation. Results showed significant G2/M phase cell cycle arrest, changes in microtubule dynamics that produced increased apoptotic cell death and decreased proliferation with initial exposure to NP PTX, followed by NP CPT in lung cancer cells. In vivo molecular imaging and TEM studies validated HVGGSSV-NP tumor binding at 24 h and confirmed the presence of Nanogold labeled HVGGSSV-NPs in tumor microvascular endothelial cells. Therapeutic efficacy studies conducted with sequential HVGGSSV targeted NP PTX and NP CPT showed 2-fold greater tumor growth delay in combination versus monotherapy treated groups, and 4-fold greater delay compared to untargeted and systemic drug controls. Analytical HPLC/MS methods were used to quantify drug content in tumor tissues at various time points, with significant paclitaxel and camptothecin levels in tumors 2 days postinjection and continued presence of both drugs up to 23 days postinjection. The efficacy of the NP delivery system in sequential treatments was corroborated in both in vitro and in vivo lung cancer models showing increased G2/M phase arrest and microtubule disruption, resulting in enhanced apoptotic cell death, decreased cell proliferation and vascular density.

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.

Challenges and opportunities in cardiovascular health informatics

Cardiovascular health informatics is a rapidly evolving interdisciplinary field concerning the processing, integration/interpretation, storage, transmission, acquisition, and retrieval of information from cardiovascular systems for the early detection, early prediction, early prevention, early diagnosis, and early treatment of cardiovascular diseases (CVDs). Based on the first author's presentation at the first IEEE Life Sciences Grand Challenges Conference, held on October 4-5, 2012, at the National Academy of Sciences, Washington, DC, USA, this paper, focusing on coronary arteriosclerotic disease, will discuss three significant challenges of cardiovascular health informatics, including: 1) to invent unobtrusive and wearable multiparameter sensors with higher sensitivity for the real-time monitoring of physiological states; 2) to develop fast multimodal imaging technologies with higher resolution for the quantification and better understanding of structure, function, metabolism of cardiovascular systems at the different levels; and 3) to develop novel multiscale information fusion models and strategies with higher accuracy for the personalized predication of the CVDs. At the end of this paper, a summary is given to suggest open discussions on these three and more challenges that face the scientific community in this field in the future.

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.

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.

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.

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.