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| Comparison of simulated BSP obtained from the three different geometries during ventricular activation. (A) BSP obtained for control case, the thick-walled and dilated geometry during simulated ectopic activation initiated in the right ventricular lateral wall (RV-LAT) at different instants of time: (i) 25 ms, (ii) 75 ms, (iii) 125 ms, and (iv) 175 ms. (B) (i) RMS for each case and (ii) rRMSe and (iii) PCC calculated vs. the control case.
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Background: Non-invasive cardiac mapping—also known as Electrocardiographic imaging (ECGi)—is a novel, painless and relatively economic method to map the electrical activation and repolarization patterns of the heart, providing a valuable tool for early identification and diagnosis of conduction abnormalities and arrhythmias. Moreover, the ability...
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... effects of the different geometries on the BSP were quantified by comparing the thick-walled and dilated geometries vs. the control during ventricular activation (Figure 2). Small differences were observed in the BSP maps at different instants of time (Figure 2A), quantitative measurements are plotted for comparison. ...
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... effects of the different geometries on the BSP were quantified by comparing the thick-walled and dilated geometries vs. the control during ventricular activation (Figure 2). Small differences were observed in the BSP maps at different instants of time (Figure 2A), quantitative measurements are plotted for comparison. A similar RMS was obtained for the three cases which produced relatively small rRMSe values ( Figure 2B). ...
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... differences were observed in the BSP maps at different instants of time (Figure 2A), quantitative measurements are plotted for comparison. A similar RMS was obtained for the three cases which produced relatively small rRMSe values ( Figure 2B). However, the largest values were observed early during the activation sequence (first 75 ms). ...
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... general increase in correlation over the time of the activation sequence is attributed to the increase in area of active tissue. RMS, rRMSe, and PCC were similar for all three heart geometries, although in general the control geometry exhibited the smallest errors and largest correlation and the dilated geometry exhibited the largest errors and smallest correlation (Figure 3; Table 2). ...
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... this study, we used an in silico approach to evaluate the impact of different ventricular anatomical morphologies and heart rate on the accuracy of epicardial reconstructions attained through the application of the inverse solution to the BSP. We have demonstrated that the different cardiac anatomical states resulted in small but measurable differences in the BSP (Figure 2). Furthermore, we demonstrated that differences between actual underlying cardiac anatomy (i.e., the heart model on which electrical activation was simulated) and the reconstructed anatomy (i.e., the heart model on which the inverse solution was applied) led to errors in the reconstruction of both epicardial potential maps and activation patterns (Figure 3; Table 2). ...
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... was used as the baseline comparison between BSP prior to obtaining the inverse solution. Using RMS, rRMSe, and PCC to quantify the similarity or differences between the BSP observed under these different conditions demonstrated that cardiac anatomy had a measurable effect on the details of the BSP but did not significantly alter the primary spatio-temporal features of normal activation (Figure 2). Then, we observed how modifying the anatomy of the ventricles in the forward solution but not in the inverse approach had an effect on the accuracy of reconstructed ectopic activation. ...
Citations
... Similarly, the size of our model's left ventricle is exaggerated near the apex. Nonetheless, our 3D model allows for useful ischemia prediction since the maximum rRMSe has been shown to be minimal in a thick walled heart model compared to a normal wall model [34]. ...
Every year, nine million people die globally from ischemic heart disease (IHD). There are many methods of early detection of IHD which can help prevent death, but few are able to determine the configuration and severity of this disease. Our study aims to determine the severity and configuration of ischemic zones by implementing the reaction-diffusion analysis of cardiac excitation in a model of the left ventricle of the human heart. Initially, this model is applied to compute twenty thousand in-silico ECG signals with stochastic distribution of ischemic parameters. Furthermore, generated data is effectively (r2=0.85) implemented for training a one-dimensional convolutional neural network to determine the severity and configuration of ischemia using only two lead surface ECG. Our results readily demonstrate that using a minimally configured portable ECG system can be instrumental for monitoring IHD and allowing early tracking of acute ischemic events.
... The module for cellular electrophysiology is based on the 2006 version of the 'ten Tusscher-Panfilov' (TP) ionic model, which is described in detail elsewhere [20] and has been widely used in electrophysiological studies [20,[29][30][31][32]. The TP model describes ionic currents across the membrane and generation of the action potential (AP) (see Fig. 1 for details). ...
Experiments on animal hearts (rat, rabbit, guinea pig, etc.) have demonstrated that mechano-calcium feedback (MCF) and mechano-electric feedback (MEF) are very important for myocardial self-regulation because they adjust the cardiomyocyte contractile function to various mechanical loads and to mechanical interactions between heterogeneous myocardial segments in the ventricle walls. In in vitro experiments on these animals, MCF and MEF manifested themselves in several basic classical phenomena (e.g., load dependence, length dependence of isometric twitches, etc.), and in the respective responses of calcium transients and action potentials. However, it is extremely difficult to study simultaneously the electrical, calcium, and mechanical activities of the human heart muscle in vitro. Mathematical modeling is a useful tool for exploring these phenomena. We have developed a novel model to describe electromechanical coupling and mechano-electric feedbacks in the human cardiomyocyte. It combines the 'ten Tusscher-Panfilov' electrophysiological model of the human cardiomyocyte with our module of myocardium mechanical activity taken from the 'Ekaterinburg-Oxford' model and adjusted to human data. Using it, we simulated isometric and afterloaded twitches and effects of MCF and MEF on excitation-contraction coupling. MCF and MEF were found to affect significantly the duration of the calcium transient and action potential in the human cardiomyocyte model in response to both smaller afterloads as compared to bigger ones and various mechanical interventions applied during isometric and afterloaded twitches.
... Alday et al. have previously studied the effect of obtaining an inverse solution on the heart in an in silico study. [6] They reported that increasing the size of the heart for the inverse solution relative to the forward solution would give an increase of ~2mm in Euclidean distance error for estimating the focal excitation location. Even though we did not directly assess focal excitation location, the magnitude of the reconstruction error seems to be in line with their study. ...
... The module for cellular electrophysiology is based on the 2006 version of 'ten Tusscher -Panfilov' (TP) ionic model, which is described in detail elsewhere [20] and has been widely used in electrophysiological studies [29][30][31][32]. The TP model describes ionic currents across the membrane and generation of the action potential (AP) (see Fig. 1 for details). ...
Experiments on animal hearts (rat, rabbit, guinea pig, etc.) showed that mechano-calcium feedback (MCF) and mechano-electric feedback (MEF) are very important for myocardial self-regulation. This is because they adjust cardiomyocyte contractile function to various mechanical loads and to the mechanical interaction of heterogeneous myocardial segments in the ventricle walls. In the in vitro experiments on these animals MCF and MEF manifested themselves in several basic classic phenomena (e.g. load dependence, length dependence of isometric twitches, etc.), and in the respective responses of calcium transients and action potentials. However, simultaneous study of electrical, calcium, and mechanical activity of the human heart muscle in vitro is extremely difficult. Here we apply mathematical modeling to study these phenomena. We develop a novel model describing electromechanical coupling and mechano-electric feedbacks in the human cardiomyocyte. This model combines the 'ten Tusscher - Panfilov' electrophysiological model of the human cardiomyocyte with our module of the myocardium mechanical activity taken from the 'Ekaterinburg - Oxford' model and adjusted to human data. Using it we model isometric and isotonic twitches and study effects of MCF and MEF on the excitation-contraction coupling. We have shown that MCF and MEF both for smaller afterloads as compared to bigger ones and for various mechanical interventions during isometric and isotonic twitches substantially affect durations of calcium transient and action potential in the human cardiomyocyte model.
... As an additional comparator, a rule-based (RB) assignment of myocyte orientations was performed on the ventricular geometry, based on methods described previously (25,26). Briefly, an idealized bi-ventricular geometry, wherein the left ventricle (LV) and right ventricle (RV) were modeled as Myocyte Orientations and Arrhythmias ...
Cardiac electrical excitation-propagation is influenced by myocyte orientations (cellular organisation). Quantitatively understanding this relationship presents a significant research challenge, especially during arrhythmias where excitation patterns become complex. Tissue-scale simulations of cardiac electrophysiology, incorporating both dynamic action potential (AP) behaviour and image-based myocardial architecture, provide an approach to investigate three-dimensional (3D) propagation of excitation waves in the heart. In this study we aimed to assess the importance of natural variation in myocyte orientations on cardiac arrhythmogenesis using 3D tissue electrophysiology simulations. Three anatomical models (i.e. describing myocyte orientations) of healthy rat ventricles – obtained using diffusion tensor imaging (DTI) at 100 μm resolution – were registered to a single bi-ventricular geometry (i.e. a single cardiac shape), in which the myocyte orientations could be represented by each of the DTI datasets or by an idealised rule-based description. The Fenton-Karma cellular excitation model was modified to reproduce rat ventricular AP duration restitution to create reaction-diffusion cardiac electrophysiology models. Over 250 3D simulations were performed in order to investigate the effects of myocyte orientations on: (i) ventricular activation, (ii) location-dependent arrhythmia induction via rapid pacing, and (iii) dynamics of re-entry averaged over multiple episodes. It was shown that: (i) myocyte orientation differences manifested themselves in local activation times but the influence on total activation time was small; (ii) differences in myocyte orientations could critically affect the inducibility and persistence of arrhythmias for specific stimulus-location/cycle-length combinations, and (iii) myocyte orientations alone could be an important determinant of scroll wave-break, although no significant differences were observed in averaged arrhythmia dynamics between the four myocyte orientation scenarios considered. Our results show that myocyte orientations are an important determinant of arrhythmia inducibility, persistence, and scroll wave-break. These findings suggest that where specificity is desired, for example when predicting location-dependent, patient-specific arrhythmia inducibility, subject-specific myocyte orientations may be important.
Introduction: Premature ventricular contractions (PVCs) are one of the most commonly targeted pathologies for ECGI validation, often through ventricular stimulation to mimic the ectopic beat. However, it remains unclear if such stimulated beats faithfully reproduce spontaneously occurring PVCs, particularly in the case of the R-on-T phenomenon. The objective of this study was to determine the differences in ECGI accuracy when reconstructing spontaneous PVCs as compared to ventricular-stimulated beats and to explore the impact of pathophysiological perturbation on this reconstruction accuracy.
Methods: Langendorff-perfused pig hearts ( n = 3) were suspended in a human torso-shaped tank, and local hyperkalemia was induced through perfusion of a high-K ⁺ solution (8 mM) into the LAD. Recordings were taken simultaneously from the heart and tank surfaces during ventricular pacing and during spontaneous PVCs (including R-on-T), both at baseline and high K ⁺ . Epicardial potentials were reconstructed from torso potentials using ECGI.
Results: Spontaneously occurring PVCs were better reconstructed than stimulated beats at baseline in terms of electrogram morphology [correlation coefficient (CC) = 0.74 ± 0.05 vs. CC = 0.60 ± 0.10], potential maps (CC = 0.61 ± 0.06 vs. CC = 0.51 ± 0.12), and activation time maps (CC = 0.86 ± 0.07 vs. 0.76 ± 0.10), though there was no difference in the localization error (LE) of epicardial origin (LE = 14 ± 6 vs. 15 ± 11 mm). High K ⁺ perfusion reduced the accuracy of ECGI reconstructions in terms of electrogram morphology (CC = 0.68 ± 0.10) and AT maps (CC = 0.70 ± 0.12 and 0.59 ± 0.23) for isolated PVCs and paced beats, respectively. LE trended worse, but the change was not significant (LE = 17 ± 9 and 20 ± 12 mm). Spontaneous PVCs were less well when the R-on-T phenomenon occurred and the activation wavefronts encountered a line of block.
Conclusion: This study demonstrates the differences in ECGI accuracy between spontaneous PVCs and ventricular-paced beats. We also observed a reduction in this accuracy near regions of electrically inactive tissue. These results highlight the need for more physiologically realistic experimental models when evaluating the accuracy of ECGI methods. In particular, reconstruction accuracy needs to be further evaluated in the presence of R-on-T or isolated PVCs, particularly when encountering obstacles (functional or anatomical) which cause line of block and re-entry.
Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2+/−-deficient AF conditions by realistic in silico AF modeling.
Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.
Results: We compared the wild-type and PITX2+/− deficiency in terms of the action potential duration (APD90), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2+/−-deficient model exhibited a shorter APD90 (p < 0.001), a lower Smax (p < 0.001), mean DF (p = 0.012), PS number (p < 0.001), and a longer AF cycle length (AFCL, p = 0.011). Five V-AADs changed the electrophysiology in a dose-dependent manner. AAD-induced AFCL lengthening (p < 0.001) and reductions in the CV (p = 0.033), peak DF (p < 0.001), and PS number (p < 0.001) were more significant in PITX2+/−-deficient than wild-type AF. PITX2+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018).
Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.
