Abstract
AimsPatient-to-patient anatomical differences are an important source of variability in the electrocardiogram, and they may compromise the identification of pathological electrophysiological abnormalities. This study aims at quantifying the contribution of variability in ventricular and torso anatomies to differences in QRS complexes of the 12-lead ECG using computer simulations.MethodsA computational pipeline is presented that enables computer simulations using human torso/biventricular anatomically based electrophysiological models from clinically standard magnetic resonance imaging (MRI). The ventricular model includes membrane kinetics represented by the biophysically detailed O’Hara Rudy model modified for tissue heterogeneity and includes fiber orientation based on the Streeter rule. A population of 265 torso/biventricular models was generated by combining ventricular and torso anatomies obtained from clinically standard MRIs, augmented with a statistical shape model of the body. 12-lead ECGs were simulated on the 265 human torso/biventricular electrophysiology models, and QRS morphology, duration and amplitude were quantified in each ECG lead for each of the human torso-biventricular models.ResultsQRS morphologies in limb leads are mainly determined by ventricular anatomy, while in the precordial leads, and especially V1 to V4, they are determined by heart position within the torso. Differences in ventricular orientation within the torso can explain morphological variability from monophasic to biphasic QRS complexes. QRS duration is mainly influenced by myocardial volume, while it is hardly affected by the torso anatomy or position. An average increase of 0.12 ± 0.05 ms in QRS duration is obtained for each cm3 of myocardial volume across all the leads while it hardly changed due to changes in torso volume.ConclusionComputer simulations using populations of human torso/biventricular models based on clinical MRI enable quantification of anatomical causes of variability in the QRS complex of the 12-lead ECG. The human models presented also pave the way toward their use as testbeds in silico clinical trials.
Highlights
The electrocardiogram (ECG) is the most widely used clinical tool for evaluation of cardiac function
We develop a computational pipeline to conduct highperformance computing (HPC) electrophysiological simulations using biophysically detailed computational human models with ventricular and torso anatomies obtained from clinically standard cardiac magnetic resonance imaging (MRI) acquisitions
The present study demonstrates the computational evaluation of the effect of heart-torso position and anatomy on the QRS complex using human torso/biventricular electrophysiology models derived from clinically standard MRI
Summary
The electrocardiogram (ECG) is the most widely used clinical tool for evaluation of cardiac function. Electrocardiogram features, and its QRS complex, are affected by microstructural and physiological factors such as fiber orientation, Purkinje, myocardial conduction pathways and ionic currents (Boineau and Spach, 1968), and by anatomical characteristics such as heart size and orientation, ventricular wall thickness, and body mass index (Hoekema et al, 1999, 2001; van Oosterom et al, 2000; Corlan et al, 2005). Sánchez et al (2018) provided insights into the key factors determining the ECG characteristics based on data for six heart failure patients These studies highlight the potential of computer simulation studies using image-based models to shed light into the anatomical basis governing ECG variability and the QRS complex
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