Noninvasive Mapping of Transmural Potentials During Activation in Swine Hearts From Body Surface Electrocardiograms

Abstract

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 the present 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 pre-operative 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 present 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.

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

“…Technical validation encompasses a broad range of cardiac source models, forward model formulations, inverse methods, and pre- and post-processing techniques. These studies are typically executed using either analytical ( Rudy et al, 1979 ) or simulated potentials ( Dubois et al, 2016 ; Figuera et al, 2016 ; Svehlikova et al, 2018 ), ex vivo torso tank experiments ( Oster et al, 1997 ; Shome and Macleod, 2007 ; Bear et al, 2018a ) and in vivo animal studies ( Liu et al, 2012 ; Oosterhoff et al, 2016 ; Cluitmans et al, 2017 ; Bear et al, 2018b ), with more limited results from humans ( Ghanem et al, 2005 ; Sapp et al, 2012 ; Erem et al, 2014 ; Schulze, 2015 ; Punshchykova et al, 2016 ). For simplicity, here we have organized technical validation according to the different features that may be extracted from ECGI, irrespective of source models.…”

“…Electrograms are one of the most common features reconstructed with ECGI, as they provide useful information to clinicians, directly relatable to invasive recordings. Ground truth data is available through simulations ( Simms and Geselowitz, 1995 ; Wang et al, 2010 ; Figuera et al, 2016 ; Janssen et al, 2017 ), recordings obtained with epicardial, endocardial and transmural electrode arrays (with upwards of 200 electrodes) in ex vivo ( Oster et al, 1997 ; Shome and Macleod, 2007 ; Bear et al, 2018b ) and in vivo ( Zhang et al, 2005 ; Han et al, 2011 ; Liu et al, 2012 ; Oosterhoff et al, 2016 ; Cluitmans et al, 2017 ; Bear et al, 2018b ) experimental models, and invasive mapping clinically ( Ghanem et al, 2005 ; Sapp et al, 2012 ; Punshchykova et al, 2016 ). Most validation studies to date use a global evaluation of the QRS, T, or QRS-T waveform reconstruction using correlation and/or error metrics, to demonstrate the accuracy in the overall topology and/or amplitude of electrograms (example in Figure 3 ).…”

“…The earliest site of activation of paced beats is often reconstructed and compared to the known location of pacing, yielding a localization error. For example, animal validation studies with pacing localization exist for potential-based ( Cluitmans et al, 2017 ; Bear et al, 2018b ) and activation/recovery-based approaches ( Han et al, 2011 ; Liu et al, 2012 ; Oosterhoff et al, 2016 ).…”

“…Over the past four decades, ECGI has seen considerable development, from purely analytical studies ( Rudy et al, 1979 ; Figuera et al, 2016 ; Svehlikova et al, 2018 ), to torso tank ( Oster et al, 1997 , 1998 ; Ramanathan and Rudy, 2001 ; Shome and Macleod, 2007 ; Bear et al, 2018a ) and large animal models ( Liu et al, 2012 ; Oosterhoff et al, 2016 ; Cluitmans et al, 2017 ; Bear et al, 2018b ) and finally application in humans ( Ghanem et al, 2005 ; Horáček et al, 2011 ; Haissaguerre et al, 2014 ; Schulze, 2015 ; Punshchykova et al, 2016 ). It is now increasingly used for academic research and in clinical practice.…”

Activation recovery interval imaging of premature ventricular contraction

“…A 3D cardiac electrical imaging (3DCEI) technique [ 32 – 35 ] was developed to estimate the equivalent current density at each cardiac source location from BSPMs and derived the activation time from the time course of current density. This method has been quantitatively evaluated in animal models under different conditions such as pacing, ventricular tachycardia, drug-induced QT prolongation and non-ischemic heart failure [ 36 – 41 ]. 3DCEI was also applied to atrial arrhythmias by extracting frequency features from the reconstructed current density [ 42 ].…”