Electrocardiographic imaging of heart rhythm disorders: from bench to bedside

Systematic review of computational techniques, dataset utilization, and feature extraction in electrocardiographic imaging

This study aimed to analyze computational techniques in ECG imaging (ECGI) reconstruction, focusing on dataset identification, problem-solving, and feature extraction. We employed a PRISMA approach to review studies from Scopus and Web of Science, applying Cochrane principles to assess risk of bias. The selection was limited to English peer-reviewed papers published from 2010 to 2023, excluding studies that lacked computational technique descriptions. From 99 reviewed papers, trends show a preference for traditional methods like the boundary element and Tikhonov methods, alongside a rising use of advanced technologies including hybrid techniques and deep learning. These advancements have enhanced cardiac diagnosis and treatment precision. Our findings underscore the need for robust data utilization and innovative computational integration in ECGI, highlighting promising areas for future research and advances. This shift toward tailored cardiac care suggests significant progress in diagnostic and treatment methods.

High Density Body Surface Potential Mapping with Conducting Polymer-Eutectogel Electrode Arrays for ECG imaging

Electrocardiography imaging (ECGi) is a non-invasive inverse reconstruction procedure which employs body surface potential maps (BSPM) obtained from surface electrode array measurements to improve the spatial resolution and interpretability of conventional electrocardiography (ECG) for the diagnosis of cardiac dysfunction. ECGi currently lacks precision, which has prevented its adoption in clinical setups. The introduction of high-density electrode arrays could increase ECGi reconstruction accuracy but is not attempted before due to manufacturing and processing limitations. Advances in multiple fields have now enabled the implementation of such arrays which poses questions on optimal array design parameters for ECGi. In this work, a novel conducting polymer electrode manufacturing process on flexible substrates is proposed to achieve high-density, mm-sized, conformable, long-term, and easily attachable electrode arrays for BSPM with parameters optimally selected for ECGi applications. Temporal, spectral, and correlation analysis are performed on a prototype array demonstrating the validity of the chosen parameters and the feasibility of high-density BSPM, paving the way for ECGi devices fit for clinical application.

Uncertainty quantification of the effect of cardiac position variability in the inverse problem of electrocardiographic imaging

Objective.Electrocardiographic imaging (ECGI) is a functional imaging modality that consists of two related problems, the forward problem of reconstructing body surface electrical signals given cardiac bioelectric activity, and the inverse problem of reconstructing cardiac bioelectric activity given measured body surface signals. ECGI relies on a model for how the heart generates bioelectric signals which is subject to variability in inputs. The study of how uncertainty in model inputs affects the model output is known as uncertainty quantification (UQ). This study establishes develops, and characterizes the application of UQ to ECGI.Approach.We establish two formulations for applying UQ to ECGI: a polynomial chaos expansion (PCE) based parametric UQ formulation (PCE-UQ formulation), and a novel UQ-aware inverse formulation which leverages our previously established 'joint-inverse' formulation (UQ joint-inverse formulation). We apply these to evaluate the effect of uncertainty in the heart position on the ECGI solutions across a range of ECGI datasets.Main results.We demonstrated the ability of our UQ-ECGI formulations to characterize the effect of parameter uncertainty on the ECGI inverse problem. We found that while the PCE-UQ inverse solution provided more complex outputs such as sensitivities and standard deviation, the UQ joint-inverse solution provided a more interpretable output in the form of a single ECGI solution. We find that between these two methods we are able to assess a wide range of effects that heart position variability has on the ECGI solution.Significance.This study, for the first time, characterizes in detail the application of UQ to the ECGI inverse problem. We demonstrated how UQ can provide insight into the behavior of ECGI using variability in cardiac position as a test case. This study lays the groundwork for future development of UQ-ECGI studies, as well as future development of ECGI formulations which are robust to input parameter variability.

Innovations in ventricular tachycardia ablation

Catheter ablation of ventricular arrhythmias (VAs) has evolved significantly over the past decade and is currently a well-established therapeutic option. Technological advances and improved understanding of VA mechanisms have led to tremendous innovations in VA ablation. The purpose of this review article is to provide an overview of current innovations in VA ablation. Mapping techniques, such as ultra-high density mapping, isochronal late activation mapping, and ripple mapping, have provided improved arrhythmogenic substrate delineation and potential procedural success while limiting duration of ablation procedure and potential hemodynamic compromise. Besides, more advanced mapping and ablation techniques such as epicardial and intramyocardial ablation approaches have allowed operators to more precisely target arrhythmogenic substrate. Moreover, advances in alternate energy sources, such as electroporation, as well as stereotactic radiation therapy have been proposed to be effective and safe. New catheters, such as the lattice and the saline-enhanced radiofrequency catheters, have been designed to provide deeper and more durable tissue ablation lesions compared to conventional catheters. Contact force optimization and baseline impedance modulation are important tools to optimize VT radiofrequency ablation and improve procedural success. Furthermore, advances in cardiac imaging, specifically cardiac MRI, have great potential in identifying arrhythmogenic substrate and evaluating ablation success. Overall, VA ablation has undergone significant advances over the past years. Innovations in VA mapping techniques, alternate energy source, new catheters, and utilization of cardiac imaging have great potential to improve overall procedural safety, hemodynamic stability, and procedural success.

ECG Electrode Localization: 3D DS Camera System for Use in Diverse Clinical Environments

Models of the human body representing digital twins of patients have attracted increasing interest in clinical research for the delivery of personalized diagnoses and treatments to patients. For example, noninvasive cardiac imaging models are used to localize the origin of cardiac arrhythmias and myocardial infarctions. The precise knowledge of a few hundred electrocardiogram (ECG) electrode positions is essential for their diagnostic value. Smaller positional errors are obtained when extracting the sensor positions, along with the anatomical information, for example, from X-ray Computed Tomography (CT) slices. Alternatively, the amount of ionizing radiation the patient is exposed to can be reduced by manually pointing a magnetic digitizer probe one by one to each sensor. An experienced user requires at least 15 min. to perform a precise measurement. Therefore, a 3D depth-sensing camera system was developed that can be operated under adverse lighting conditions and limited space, as encountered in clinical settings. The camera was used to record the positions of 67 electrodes attached to a patient's chest. These deviate, on average, by 2.0 mm ±1.5 mm from manually placed markers on the individual 3D views. This demonstrates that the system provides reasonable positional precision even when operated within clinical environments.

Effect of different alcohol consumption levels on the left atrial size: A cross-sectional study in rural China

OBJECTIVE

Previous studies have investigated the relationship between alcohol and ventricular structure; however, few studies have evaluated the relation between alcohol consumption and the atrium size. In this study, we aimed to test the association between alcohol consumption and left atrium (LA) size in the general population.

METHODS

A population-based sample of 10,211 subjects aged ≥35 years and free from hypertension at baseline were followed from January 2012 to August 2013. Left atrial enlargement (LAE) was defined as the ratio of LA diameter to body surface area exceeding 2.4 cm/m2 in both the sexes. Independent factors for LAE were estimated by multiple logistic regression analyses.

RESULTS

The study included 10,211 participants (4,751 men and 5,460 women). Left atrial diameter/body surface area (LAD/BSA) was higher in the moderate and heavy alcohol consumption groups than in the non-drinker group (non-drinker, 20.5±0.03 cm/m2; moderate, 20.8±0.09 cm/m2; and heavy, 20.6±0.06 cm/m2; p<0.001). Both the groups of moderate and heavy drinkers had a higher incidence of LAE than the non-drinker group (6.9% of non-drinkers, 9.9% of moderate drinkers, and 8.4% of heavy drinkers; p<0.001). After adjusting for related risk factors, multiple logistic regression analyses showed that moderate drinkers had an approximately 1.4-fold higher risk of LAE [odds ratio (OR): 1.387, 95% confidence interval (CI) 1.056-1.822, p=0.019] compared with the non-drinkers, and the heavy drinkers had an approximately 1.2-fold higher risk of LAE (OR: 1.229, 95% CI: 1.002-1.508, p=0.047) compared with that of the non-drinkers.

CONCLUSION

Both heavy and moderate drinkers had increased odds for LAE compared with participants with no alcohol consumption in the general population.

Body Surface Potential Mapping: Contemporary Applications and Future Perspectives

Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.

The Use of Electrocardiographic Imaging in Localising the Origin of Arrhythmias During Catheter Ablation of Ventricular Tachycardia

Non-invasive electrocardiographic imaging (ECGI) is a novel clinical tool for mapping ventricular arrhythmia. Using multiple body surface electrodes to collect unipolar electrograms and conventional medical imaging of the heart, an epicardial shell can be created to display calculated electrograms. This calculation is achieved by solving the inverse problem and allows activation times to be calculated from a single beat. The technology was initially pioneered in the US using an experimental torso-shaped tank. Accuracy from studies in humans has varied. Early data was promising, with more recent work suggesting only moderate accuracy when reproducing cardiac activation. Despite these limitations, the system has been successfully used in pioneering work with non-invasive cardiac radioablation to treat ventricular arrhythmia. This suggests that the resolution may be sufficient for treatment of large target areas. Although untested in a well conducted clinical study it is likely that it would not be accurate enough to guide more discreet radiofrequency ablation.

The electrocardiographic forward problem: A benchmark study

BACKGROUND

Electrocardiographic forward problems are crucial components for noninvasive electrocardiographic imaging (ECGI) that compute torso potentials from cardiac source measurements. Forward problems have few sources of error as they are physically well posed and supported by mature numerical and computational techniques. However, the residual errors reported from experimental validation studies between forward computed and measured torso signals remain surprisingly high.

OBJECTIVE

To test the hypothesis that incomplete cardiac source sampling, especially above the atrioventricular (AV) plane is a major contributor to forward solution errors.

METHODS

We used a modified Langendorff preparation suspended in a human-shaped electrolytic torso-tank and a novel pericardiac-cage recording array to thoroughly sample the cardiac potentials. With this carefully controlled experimental preparation, we minimized possible sources of error, including geometric error and torso inhomogeneities. We progressively removed recorded signals from above the atrioventricular plane to determine how the forward-computed torso-tank potentials were affected by incomplete source sampling.

RESULTS

We studied 240 beats total recorded from three different activation sequence types (sinus, and posterior and anterior left-ventricular free-wall pacing) in each of two experiments. With complete sampling by the cage electrodes, all correlation metrics between computed and measured torso-tank potentials were above 0.93 (maximum 0.99). The mean root-mean-squared error across all beat types was also low, less than or equal to 0.10 mV. A precipitous drop in forward solution accuracy was observed when we included only cage measurements below the AV plane.

CONCLUSION

First, our forward computed potentials using complete cardiac source measurements set a benchmark for similar studies. Second, this study validates the importance of complete cardiac source sampling above the AV plane to produce accurate forward computed torso potentials. Testing ECGI systems and techniques with these more complete and highly accurate datasets will improve inverse techniques and noninvasive detection of cardiac electrical abnormalities.

Updates in Ventricular Tachycardia Ablation

Sudden cardiac death (SCD) due to recurrent ventricular tachycardia is an important clinical sequela in patients with structural heart disease. As a result, ventricular tachycardia (VT) has emerged as a major clinical and public health problem. The mechanism of VT is predominantly mediated by re-entry in the presence of arrhythmogenic substrate (scar), though focal mechanisms are also important. Catheter ablation for VT, when compared to standard medical therapy, has been shown to improve VT-free survival and burden of device therapies. Approaches to VT ablation are dependent on the underlying disease process, broadly classified into idiopathic (no structural heart disease) or structural heart disease (ischemic or non-ischemic heart disease). This update aims to review recent advances made for the treatment of VT ablation, with respect to current clinical trials, peri-procedure risk assessments, pre-procedural cardiac imaging, electro-anatomic mapping and advances in catheter and non-catheter based ablation techniques.

Novel experimental model for studying the spatiotemporal electrical signature of acute myocardial ischemia: a translational platform

Myocardial ischemia is one of the most common cardiovascular pathologies and can indicate many severe and life threatening diseases. Despite these risks, current electrocardiographic detection techniques for ischemia are mediocre at best, with reported sensitivity and specificity ranging from 50%-70% and 70%-90%, respectively.

OBJECTIVE

To improve this performance, we set out to develop an experimental preparation to induce, detect, and analyze bioelectric sources of myocardial ischemia and determine how these sources reflect changes in body-surface potential measurements.

APPROACH

We designed the experimental preparation with three important characteristics: (1) enable comprehensive and simultaneous high-resolution electrical recordings within the myocardial wall, on the heart surface, and on the torso surface; (2) develop techniques to visualize these recorded electrical signals in time and space; and (3) accurately and controllably simulate ischemic stress within the heart by modulating the supply of blood, the demand for perfusion, or a combination of both.

MAIN RESULTS

To achieve these goals we designed comprehensive system that includes (1) custom electrode arrays (2) signal acquisition and multiplexing units, (3) a surgical technique to place electrical recording and myocardial ischemic control equipment, and (4) an image based modeling pipeline to acquire, process, and visualize the results. With this setup, we are uniquely able to capture simultaneously and continuously the electrical signatures of acute myocardial ischemia within the heart, on the heart surface, and on the body surface.

SIGNIFICANCE

This novel experimental preparation enables investigation of the complex and dynamic nature of acute myocardial ischemia that should lead to new, clinically translatable results.

Evaluation of ECG Imaging to Map Hemodynamically Stable and Unstable Ventricular Arrhythmias

BACKGROUND

ECG imaging (ECGI) has been used to guide treatment of ventricular ectopy and arrhythmias. However, the accuracy of ECGI in localizing the origin of arrhythmias during catheter ablation of ventricular tachycardia (VT) in structurally abnormal hearts remains to be fully validated.

METHODS

During catheter ablation of VT, simultaneous mapping was performed using electroanatomical mapping (CARTO, Biosense-Webster) and ECGI (CardioInsight, Medtronic) in 18 patients. Sites of entrainment, pace-mapping, and termination during ablation were used to define the VT site of origin (SoO). Distance between SoO and the site of earliest activation on ECGI were measured using co-registered geometries from both systems. The accuracy of ECGI versus a 12-lead surface ECG algorithm was compared.

RESULTS

A total of 29 VTs were available for comparison. Distance between SoO and sites of earliest activation in ECGI was 22.6, 13.9 to 36.2 mm (median, first to third quartile). ECGI mapped VT sites of origin onto the correct AHA segment with higher accuracy than a validated 12-lead ECG algorithm (83.3% versus 38.9%; P=0.015).

CONCLUSIONS

This simultaneous assessment demonstrates that CardioInsight localizes VT circuits with sufficient accuracy to provide a region of interest for targeting mapping for ablation. Resolution is not sufficient to guide discrete radiofrequency lesion delivery via catheter ablation without concomitant use of an electroanatomical mapping system but may be sufficient for segmental ablation with radiotherapy.

Molecular Imaging of the Heart

Multimodality cardiovascular imaging is routinely used to assess cardiac function, structure, and physiological parameters to facilitate the diagnosis, characterization, and phenotyping of numerous cardiovascular diseases (CVD), as well as allows for risk stratification and guidance in medical therapy decision-making. Although useful, these imaging strategies are unable to assess the underlying cellular and molecular processes that modulate pathophysiological changes. Over the last decade, there have been great advancements in imaging instrumentation and technology that have been paralleled by breakthroughs in probe development and image analysis. These advancements have been merged with discoveries in cellular/molecular cardiovascular biology to burgeon the field of cardiovascular molecular imaging. Cardiovascular molecular imaging aims to noninvasively detect and characterize underlying disease processes to facilitate early diagnosis, improve prognostication, and guide targeted therapy across the continuum of CVD. The most-widely used approaches for preclinical and clinical molecular imaging include radiotracers that allow for high-sensitivity in vivo detection and quantification of molecular processes with single photon emission computed tomography and positron emission tomography. This review will describe multimodality molecular imaging instrumentation along with established and novel molecular imaging targets and probes. We will highlight how molecular imaging has provided valuable insights in determining the underlying fundamental biology of a wide variety of CVDs, including: myocardial infarction, cardiac arrhythmias, and nonischemic and ischemic heart failure with reduced and preserved ejection fraction. In addition, the potential of molecular imaging to assist in the characterization and risk stratification of systemic diseases, such as amyloidosis and sarcoidosis will be discussed. © 2019 American Physiological Society. Compr Physiol 9:477-533, 2019.

Reducing Error in ECG Forward Simulations With Improved Source Sampling

A continuing challenge in validating electrocardiographic imaging (ECGI) is the persistent error in the associated forward problem observed in experimental studies. One possible cause of this error is insufficient representation of the cardiac sources; cardiac source measurements often sample only the ventricular epicardium, ignoring the endocardium and the atria. We hypothesize that measurements that completely cover the pericardial surface are required for accurate forward solutions. In this study, we used simulated and measured cardiac potentials to test the effect of different levels of spatial source sampling on the forward simulation. Not surprisingly, increasing the source sampling over the atria reduced the average error of the forward simulations, but some sampling strategies were more effective than others. Uniform and random distributions of samples across the atrial surface were the most efficient strategies in terms of lowest error with the fewest sampling locations, whereas “single direction” strategies, i.e., adding to the atrioventricular (AV) plane or atrial roof only, were the least efficient. Complete sampling of the atria is needed to eliminate errors from missing cardiac sources, but while high density sampling that covers the entire atria yields the best results, adding as few as 11 electrodes on the atria can significantly reduce these errors. Future validation studies of the ECG forward simulations should use a cardiac source sampling that takes these considerations into account, which will, in turn, improve validation and understanding of ECGI.

The Early Repolarization ECG Pattern – An Update

Early repolarization pattern (ERP), a form of J-wave syndromes, was considered long time a benign ECG phenomenon. However, recent data confirmed that certain phenotypes of ERP are related to an increased risk of sudden cardiac death (idiopathic ventricular fibrillation). Our paper gives a short and practical update regarding the main issues related to ERP: epidemiological data, molecular and electrophysiological background, clinical significance and risk stratification. At the end, the future directions of research and clinical management related to ERP are presented.

The Consortium for Electrocardiographic Imaging

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

Computational Electrocardiography: Revisiting Holter ECG Monitoring

BACKGROUND

Since 1942, when Goldberger introduced the 12-lead electrocardiography (ECG), this diagnostic method has not been changed.

OBJECTIVES

After 70 years of technologic developments, we revisit Holter ECG from recording to understanding.

METHODS

A fundamental change is fore-seen towards "computational ECG" (CECG), where continuous monitoring is producing big data volumes that are impossible to be inspected conventionally but require efficient computational methods. We draw parallels between CECG and computational biology, in particular with respect to computed tomography, computed radiology, and computed photography. From that, we identify technology and methodology needed for CECG.

RESULTS

Real-time transfer of raw data into meaningful parameters that are tracked over time will allow prediction of serious events, such as sudden cardiac death. Evolved from Holter's technology, portable smartphones with Bluetooth-connected textile-embedded sensors will capture noisy raw data (recording), process meaningful parameters over time (analysis), and transfer them to cloud services for sharing (handling), predicting serious events, and alarming (understanding). To make this happen, the following fields need more research: i) signal processing, ii) cycle decomposition; iii) cycle normalization, iv) cycle modeling, v) clinical parameter computation, vi) physiological modeling, and vii) event prediction.

CONCLUSIONS

We shall start immediately developing methodology for CECG analysis and understanding.

Early Repolarization Syndrome; Mechanistic Theories and Clinical Correlates

The early repolarization (ER) pattern on the 12-lead electrocardiogram is characterized by J point elevation in the inferior and/or lateral leads. The ER pattern is associated with an increased risk of ventricular arrhythmias and sudden cardiac death (SCD). Based on studies in animal models and genetic studies, it has been proposed that J point elevation in ER is a manifestation of augmented dispersion of repolarization which creates a substrate for ventricular arrhythmia. A competing theory regarding early repolarization syndrome (ERS) proposes that the syndrome arises as a consequence of abnormal depolarization. In recent years, multiple clinical studies have described the characteristics of ER patients with VF in more detail. The majority of these studies have provided evidence to support basic science observations. However, not all clinical observations correlate with basic science findings. This review will provide an overview of basic science and genetic research in ER and correlate basic science evidence with the clinical phenotype.

Generation of Combined-Modality Tetrahedral Meshes

Registering and combining anatomical components from different image modalities, like MRI and CT that have different tissue contrast, could result in patient-specific models that more closely represent underlying anatomical structures. In this study, we combined a pair of CT and MRI scans of a pig thorax to make a tetrahedral mesh and compared different registration techniques including rigid, affine, thin plate spline morphing (TPSM), and iterative closest point (ICP), to superimpose the segmented bones from the CT scan on the soft tissues segmented from the MRI. The TPSM and affine-registered bones remained close to, but not overlapping, important soft tissue. Simulation models, including an ECG forward model and a defibrillation model, were computed on generated multi-modality meshes after TPSM and affine registration and compared to those based on the original torso mesh.

Non-invasive cardiac mapping in clinical practice: Application to the ablation of cardiac arrhythmias

Ten years ago, electrocardiographic imaging (ECGI) started to demonstrate its efficiency in clinical settings. The initial application to localize focal ventricular arrhythmias such as ventricular premature beats was probably the easiest to challenge and validates the concept. Our clinical experience in using this non-invasive mapping technique to identify the sources of electrical disorders and guide catheter ablation of atrial arrhythmias (premature atrial beat, atrial tachycardia, atrial fibrillation), ventricular arrhythmias (premature ventricular beats) and ventricular pre-excitation (Wolff-Parkinson-White syndrome) is described here.

Experimental Data and Geometric Analysis Repository-EDGAR

INTRODUCTION

The "Experimental Data and Geometric Analysis Repository", or EDGAR is an Internet-based archive of curated data that are freely distributed to the international research community for the application and validation of electrocardiographic imaging (ECGI) techniques. The EDGAR project is a collaborative effort by the Consortium for ECG Imaging (CEI, ecg-imaging.org), and focused on two specific aims. One aim is to host an online repository that provides access to a wide spectrum of data, and the second aim is to provide a standard information format for the exchange of these diverse datasets.

METHODS

The EDGAR system is composed of two interrelated components: 1) a metadata model, which includes a set of descriptive parameters and information, time signals from both the cardiac source and body-surface, and extensive geometric information, including images, geometric models, and measure locations used during the data acquisition/generation; and 2) a web interface. This web interface provides efficient, search, browsing, and retrieval of data from the repository.

RESULTS

An aggregation of experimental, clinical and simulation data from various centers is being made available through the EDGAR project including experimental data from animal studies provided by the University of Utah (USA), clinical data from multiple human subjects provided by the Charles University Hospital (Czech Republic), and computer simulation data provided by the Karlsruhe Institute of Technology (Germany).

CONCLUSIONS

It is our hope that EDGAR will serve as a communal forum for sharing and distribution of cardiac electrophysiology data and geometric models for use in ECGI research.