Validation and Opportunities of Electrocardiographic Imaging: From Technical Achievements to Clinical Applications

Abstract

Electrocardiographic imaging (ECGI) reconstructs the electrical activity of the heart from a dense array of body-surface electrocardiograms and a patient-specific heart-torso geometry. Depending on how it is formulated, ECGI allows the reconstruction of the activation and recovery sequence of the heart, the origin of premature beats or tachycardia, the anchors/hotspots of re-entrant arrhythmias and other electrophysiological quantities of interest. Importantly, these quantities are directly and non-invasively reconstructed in a digitized model of the patient's three-dimensional heart, which has led to clinical interest in ECGI's ability to personalize diagnosis and guide therapy. Despite considerable development over the last decades, validation of ECGI is challenging. Firstly, results depend considerably on implementation choices, which are necessary to deal with ECGI's ill-posed character. Secondly, it is challenging to obtain (invasive) ground truth data of high quality. In this review, we discuss the current status of ECGI validation as well as the major challenges remaining for complete adoption of ECGI in clinical practice. Specifically, showing clinical benefit is essential for the adoption of ECGI. Such benefit may lie in patient outcome improvement, workflow improvement, or cost reduction. Future studies should focus on these aspects to achieve broad adoption of ECGI, but only after the technical challenges have been solved for that specific application/pathology. We propose 'best' practices for technical validation and highlight collaborative efforts recently organized in this field. Continued interaction between engineers, basic scientists, and physicians remains essential to find a hybrid between technical achievements, pathological mechanisms insights, and clinical benefit, to evolve this powerful technique toward a useful role in clinical practice.

Keywords: ECG imaging; electrocardiography; electrophysiology; experiment; validation.

FIGURE 1

Describes the validation continuum, from purely technical studies to pathological/clinical validation and socioeconomic benefit studies. Whereas the technical validation of ECGI is extensive, as is its use in disease mechanisms studies and validation of the true clinical benefit is still lacking.

FIGURE 2

Electrocardiographic imaging requires recording of body-surface potentials and the acquisition of a torso-heart geometry through computed tomography (CT) or magnetic resonance (MR) imaging. The electrical characteristics of the heart can then be computed by employing one of the “source models,” i.e., models of cardiac electrical activity that explain the recorded body-surface potentials. Globally, these source models are categorized as: transmembrane voltage (TMV) models, surface-potential models (either epicardial-only or endo-epicardial surface), and activation/recovery-based models. It is possible to compute surface potentials and electrograms from TMVs, and to compute activation and recovery sequences from electrograms, but not the other way around. Image in part reproduced with permission from: Cluitmans (2016); Weiss et al. (2007), and Van Dam et al. (2009).

FIGURE 3

Top: epicardial geometry with reconstructed potentials from a canine in vivo study, for a sinus beat (A) and a LV-paced beat (B). White dots indicate the position of invasive electrodes used for validation recordings. Bottom: recorded (red) and ECGI-reconstructed (black) electrograms for electrodes numbered in geometry above. CC, correlation coefficient between recorded and reconstructed electrograms. RA, right atrijm; RV, right ventricle. Adapted with permission from Cluitmans et al. (2017).

FIGURE 4

Epicardial potential maps derived from ECGI (left) and recorded (right) epicardial electrograms at three instants during ventricular activation during epicardial pacing from the anterior RV free wall (ECG shown left). During the early and late phases of activation, only small regions of the heart are activated, leading to distorted values of error metrics such as correlation (right, showing different reconstruction approaches in different colors). Adapted with permission from Bear et al. (2018b).

FIGURE 5

Validation of ECGI derived activation maps using an ex vivo torso tank set up has demonstrated that, in electrical dyssynchrony, ECGi (right) produces a “line of activation block” that is not present in recorded signals (left) using an epicardial electrode sock [adapted with permission from Bear et al. (2018a)].

FIGURE 6

During atrial (AF) or ventricular fibrillation, the mechanism of fibrillation can be assessed using phase and/or frequency mapping. (A) [adapted with permission from Haissaguerre et al. (2014)], ECGI derived phase maps of ≥1000-ms-long AF window show reentry events involving the posterior upper right atrium; sites 1–12 show the pre-phase electrograms around its core. By tracking phase singularities (PS) for reentrant activity of at least one full rotation, PS density maps illustrate arrhythmogenic drivers that may be targets for ablation. (B) [adapted with permission from Pedrón-Torrecilla et al. (2016)], dominant frequency (DF) using invasive CARTO (top) and non-invasive ECGI (bottom) in AF patients demonstrate good correspondence. Region of high DF (purple) identify arrhythmogenic drivers that may be targets for ablation.

FIGURE 7

Example of ECGI-guided ablation in a patient. Top: 12-lead ECG recorded during ECGI (white background) and clinical recording during symptoms (pink background), both with a sinus beat and subsequent premature ventricular complex (PVC). Bottom: Live view as visible to the cardiologist-electrophysiologist during the ablation procedure when using the Carto 3 cardiac mapping system. The 3D anatomy as determined by the Carto catheter (white structures) is overlaid with the activation map of the PVC as created pre-procedurally with ECGI (red-to-blue: early-to-late activation time; blue dot: PVC origin). The cardiologist can use this live view during the procedure to navigate the catheter to the area suspected of the PVC origin. Adapted with permission from: Cluitmans et al. (2016).