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We examine the effects of cardiac geometry and architecture on re-entrant scroll wave dynamics by quantifying the scroll wave filament in two biophysically-detailed heterogeneous models of the human left ventricular free wall – a simple cuboid model and a wedge model constructed using DT-MRI data. For any given geometry, changing the architecture results in changes to the filament meander pattern, increases in filament length, changes to the filament curvature and local filament twist, and increases in the maximum twist along a single filament. Changes to the geometry also affect scroll wave dynamics, mainly due to the size of the tissue. We conclude that such differences in re-entrant scroll wave dynamics should be taken into account when interpreting results from simulations that use simple cardiac geometries and architectures.

Over the past several decades, the mouse has gained prominence in the cardiac electrophysiology literature as the animal model of choice. Using computer models of the mouse and human ECG, this paper is a step toward understanding when the mouse succeeds and fails to mimic functional changes resulting from disease states and drug interactions.

We relate aspects of discontinuous cardiac activation to the mesoscale myocardial structural feature of interlaminae clefts or cleavage planes. Specialized numerical and computational procedures have been developed for modeling cardiac activation which accounts for detailed myocardial geometric structures derived from specific tissue samples. This modeling allows both study and analysis of the effects of cleavage planes and other structural barriers to myocardial current flow. The results show that mesoscale discontinuities significantly affect the formation of virtual electrodes, and can result in discontinuous activation with midwall pacing.

This article reviews major problems and difficulties faced by the authors along more than twenty years of clinical application of magnetocardiography (MCG) as a tool to improve the diagnosis of arrhythmogenic mechanism(s), non-invasively. It is also emphasized that an exhaustive understanding of individual electrophysiology is mandatory before any intervention, which can modify the substrate and complicate the treatment of patients in the case of ablation failure. The reasons for scarce acceptance of MCG, compared with the success of recent methods for invasive three-dimensional electroanatomical imaging (3D-EAI), are discussed to provide suggestions for needed changes in R&D strategy. MCG might be a powerful method for non-invasive 3D-EAI, but appropriate tools for its clinical applicability are still lacking and need to be urgently developed, through serious investments and interdisciplinary cooperation.

We present preliminary results of the numerical simulation of electrocardiograms (ECG). We consider the bidomain equations to model the electrical activity of the heart and a Laplace equation for the torso. The ionic activity is modeled with a Mitchell-Schaeffer dynamics. We use adaptive semi-implicit BDF schemes for the time discretization and a Neumann-Robin domain decomposition algorithm for the space discretization. The obtained ECGs, although not completely satisfactory, are promising. They allow to discuss various modelling assumptions, for example the relevance of cells heterogeneity, the fiber orientation and the coupling conditions with the torso.

The time of the minimum time derivative of the extracellular potentials ( Φ ^ ∧ ) is a marker for the instant of activation when the depolarizing sodium current reaches its maximum rate of increase. This study examined the normalized averaged value of Φ ^ ∧ , $\Phi{^\wedge_{na}}$ , as an index of electrical activity under metabolic and hypoxic stresses. Electrical mapping was performed using a 64-electrode cage array on Langendorff perfused isolated mouse hearts at three different glucose and insulin levels during hypoxia. The lower levels of glucose and/or insulin resulted in the largest decrease of $\Phi^\wedge_{na}$ during hypoxia. A significant decrease in $\Phi^\wedge_{na}$ was a predictor of increased total activation time and propagation pattern change, and irreversible damage was predicted by a 60% decrease of $\Phi^\wedge_{na}$ . These results supported $\Phi^\wedge_{na}$ as an potentially useful index of electrical activity.

The purpose of this study is to introduce unique experimental measurements of extracellular potentials mapped from the epicardial surface of mouse hearts that reflect the same structural features seen in larger mammalian hearts. The measurements obtained in this study provide an important tool for studying the impacts of structural changes on propagation in genetically modified mouse models of cardiac disease. Unipolar electrograms were recorded using a high-resolution electrode array to map the epicardial surface of mouse hearts during atrial drive and at increasing transmural pacing depths. The extracellular potential maps revealed the underlying fiber structure of the mouse heart that is shown to be similar to those previously published from other species. This imaging technique, when integrated with computer models and diffusion tensor imaging can substantially contribute to our understanding of innovative genetic mouse models being used in the study of human cardiac disease.

Computing the epicardial potentials from the body surface potentials constitutes one form of the ill-posed inverse problem of electrocardiography (ECG). In this paper, we employ hybrid methods combining the least square QR (LSQR) with truncated singular-value decomposition (TSVD) to solve the inverse problem of ECG. Hybrid methods are based on the Lanczos process, which yields a sequence of small bidiagonal systems approximating the original ill-posed problem, and on another additional direct regularization (the truncated SVD method is used in the present investigation), which is used to stabilize the iteration. The results show that determining of regularization parameters based on the final projected problem rather than on the original discretization one has firmer justification and it takes much less computational cost. The computation time could be reduced by several tenfolds typically, while the performance of the hybrid method is maintained well compared with TSVD, LSQR and GMRes methods. In addition, comparing with LSQR method, the hybrid method can obtain the inverse solutions without facing the “semi-convergence” problem.

In the efforts towards noninvasive imaging of cardiac electrophysiology from body surface potential recordings, it is of particular clinical interests to identify patient specific arrhythmogenesis and arrhythmic patterns. Since cardiac arrhythmias always involve intramural focal activities or transmural propagations, 3D cardiac transmembrane potential (TMP) mapping exhibits considerable potential utility. We have developed a general model-constrained Bayesian framework for noninvasive 3D TMP imaging from body surface potential maps (BSPMs). In this paper, it is adapted to imaging various cardiac arrhythmias, with proper specifications in accordance to different arrhythmogenic mechanisms under study. Representative phantom experiments are studied, with a focus on 1), demonstrating the benefits of 3D TMP imaging in cardiac arrhythmias; and 2), exploring the capability of the BSPM-based and general-model-constrained paradigm in complicate pathological conditions. In-depth post-analysis not only demonstrates the applicability of the framework in imaging cardiac arrhythmias and localizing intramural ectopic foci, but also indicate its merits and limitations for further improvements.

The construction of geometry models of heart-torso is critical for solving the forward and inverse problems of magneto- and electro-cardiography (MCG/ECG). Boundary element method (BEM) is a commonly used numerical approach for the solution of these problems and it requires the modeling of interfaces between various tissue regions. In this study, a new BEM (h-adaptive type) has been applied to the ECG forward/inverse problems. Compared with those traditional BEMs, the adaptive BEM can self-adjust the number and size of the boundary element (BE) meshes according to an error indicator, and thus can save a lot of computational time and also improve the accuracy of the forward and inverse solutions. In this paper, the procedure of the adaptive triangular mesh generation is detailed and the algorithm is tested using a concentric sphere model and a realistic heart-torso model. For the realistic torso model, to improve the numerical accuracy, a number of new nodes are added on the basis of initial torso BE meshes, and the corresponding node coordinates are determined using an approach called Parametric Fourier Representation (PFR) of closed polygons. The simulation results show that the adaptive BEM is more accurate and efficient than traditional BEMs and therefore it is a very promising numerical scheme for ECG forward/inverse problems.