The effect of intrathoracic heart position on electrocardiogram autocorrelation maps

Corlan, Alexandru Dan; MacLeod, Robert S.; Ambroggi, L. De

doi:10.1016/j.jelectrocard.2004.10.006

Cited by 10 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The heart was shifted with 1-cm steps up to 6 cm to the left and to the right along the x-axis and up and down along the z-axis as these shift magnitudes were used in previous studies [5,12]. The heart was rotated with 5°steps up to 30°around the y-axis (anteroposterior) to a more horizontal or vertical orientation.…”

Section: Changes In Heart Position and Orientationmentioning

confidence: 99%

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects

Nguyên¹,

Potse²,

Regoli³

et al. 2015

Journal of Electrocardiology

View full text Add to dashboard Cite

Aim: The aim of this study was to investigate the influence of geometrical factors on the ECG morphology and vectorcardiogram (VCG) parameters. Methods: Patient-tailored models based on five heart-failure patients with intraventricular conduction defects (IVCDs) were created. The heart was shifted up to 6 cm to the left, right, up, and down and rotated ±30°around the anteroposterior axis. Precordial electrodes were shifted 3 cm down.Results: Geometry modifications strongly altered ECG notching/slurring and intrinsicoid deflection time. Maximum VCG parameter changes were small for QRS duration (− 6% to + 10%) and QRS-T angle (− 6% to + 3%), but considerable for QRS amplitude (− 36% to + 59%), QRS area (− 37% to + 42%), T-wave amplitude (− 41% to + 36%), and T-wave area (− 42% to + 33%). Conclusion:The position of the heart with respect to the electrodes is an important factor determining notching/slurring and voltage-dependent parameters and therefore must be considered for accurate diagnosis of IVCDs.

show abstract

Section: Changes In Heart Position and Orientationmentioning

confidence: 99%

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects

Nguyên¹,

Potse²,

Regoli³

et al. 2015

Journal of Electrocardiology

View full text Add to dashboard Cite

show abstract

“…In the evaluation of the role of anatomical features on the ECG, previous studies have typically performed perturbations to anatomical features (i.e., heart positioning and orientation) around a reference/original position to explore their individual effect (Corlan et al, 2005; Nguyên et al, 2015). In the present study, we sample the space of plausible anatomies and generate plausible instances by swapping ventricular anatomies together with torso-poses using their corresponding heart position and orientations (torso-poses) (see section “Reconstruction of Ventricular and Torso Anatomical Meshes From Clinical MRI”).…”

Section: Discussionmentioning

confidence: 99%

“…Electrocardiogram features, and specifically its QRS complex, are affected not only by microstructural and physiological factors such as fiber orientation, Purkinje, myocardial conduction pathways and ionic currents (Boineau and Spach, 1968), but also 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). Quantitative information on the latter is, however, scarce.…”

Section: Introductionmentioning

confidence: 99%

MRI-Based Computational Torso/Biventricular Multiscale Models to Investigate the Impact of Anatomical Variability on the ECG QRS Complex

et al. 2019

View full text Add to dashboard Cite

Aims Patient-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. Methods A 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. Results QRS 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 cm 3 of myocardial volume across all the leads while it hardly changed due to changes in torso volume. Conclusion Computer 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.

show abstract

Body Surface Potential Mapping

Ambroggi¹,

Corlan²

2011

Cardiac Arrhythmias and Mapping Techniques

View full text Add to dashboard Cite

The effect of intrathoracic heart position on electrocardiogram autocorrelation maps

Cited by 10 publications

References 12 publications

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects

MRI-Based Computational Torso/Biventricular Multiscale Models to Investigate the Impact of Anatomical Variability on the ECG QRS Complex

Body Surface Potential Mapping

Contact Info

Product

Resources

About