A new algorithm to diagnose atrial ectopic origin from multi lead ECG systems--insights from 3D virtual human atria and torso.

Rapid atrial arrhythmias such as atrial fibrillation (AF) predispose to ventricular arrhythmias, sudden cardiac death and stroke. Identifying the origin of atrial ectopic activity from the electrocardiogram (ECG) can help to diagnose the early onset of AF in a cost-effective manner. The complex and rapid atrial electrical activity during AF makes it difficult to obtain detailed information on atrial activation using the standard 12-lead ECG alone. Compared to conventional 12-lead ECG, more detailed ECG lead configurations may provide further information about spatio-temporal dynamics of the body surface potential (BSP) during atrial excitation. We apply a recently developed 3D human atrial model to simulate electrical activity during normal sinus rhythm and ectopic pacing. The atrial model is placed into a newly developed torso model which considers the presence of the lungs, liver and spinal cord. A boundary element method is used to compute the BSP resulting from atrial excitation. Elements of the torso mesh corresponding to the locations of the placement of the electrodes in the standard 12-lead and a more detailed 64-lead ECG configuration were selected. The ectopic focal activity was simulated at various origins across all the different regions of the atria. Simulated BSP maps during normal atrial excitation (i.e. sinoatrial node excitation) were compared to those observed experimentally (obtained from the 64-lead ECG system), showing a strong agreement between the evolution in time of the simulated and experimental data in the P-wave morphology of the ECG and dipole evolution. An algorithm to obtain the location of the stimulus from a 64-lead ECG system was developed. The algorithm presented had a success rate of 93%, meaning that it correctly identified the origin of atrial focus in 75/80 simulations, and involved a general approach relevant to any multi-lead ECG system. This represents a significant improvement over previously developed algorithms.

Optimal iodine staining of cardiac tissue for X-ray computed tomography.

X-ray computed tomography (XCT) has been shown to be an effective imaging technique for a variety of materials. Due to the relatively low differential attenuation of X-rays in biological tissue, a high density contrast agent is often required to obtain optimal contrast. The contrast agent, iodine potassium iodide ([Formula: see text]), has been used in several biological studies to augment the use of XCT scanning. Recently I2KI was used in XCT scans of animal hearts to study cardiac structure and to generate 3D anatomical computer models. However, to date there has been no thorough study into the optimal use of I2KI as a contrast agent in cardiac muscle with respect to the staining times required, which has been shown to impact significantly upon the quality of results. In this study we address this issue by systematically scanning samples at various stages of the staining process. To achieve this, mouse hearts were stained for up to 58 hours and scanned at regular intervals of 6-7 hours throughout this process. Optimal staining was found to depend upon the thickness of the tissue; a simple empirical exponential relationship was derived to allow calculation of the required staining time for cardiac samples of an arbitrary size.

Image-based model of atrial anatomy and electrical activation: a computational platform for investigating atrial arrhythmia.

Computer models provide a powerful platform for investigating mechanisms that underlie atrial rhythm disturbances. We have used novel techniques to build a structurally-detailed, image-based model of 3-D atrial anatomy. A volume image of the atria from a normal sheep heart was acquired using serial surface macroscopy, then smoothed and down-sampled to 50 µm(3) resolution. Atrial surface geometry was identified and myofiber orientations were estimated throughout by eigen-analysis of the 3-D image structure tensor. Sinus node, crista terminalis, pectinate muscle, Bachman's bundle, and pulmonary veins were segmented on the basis of anatomic characteristics. Heterogeneous electrical properties were assigned to this structure and electrical activation was simulated on it at 100 µm(3) resolution, using both biophysically-detailed and reduced-order cell activation models with spatially-varying membrane kinetics. We confirmed that the model reproduced key features of the normal spread of atrial activation. Furthermore, we demonstrate that vulnerability to rhythm disturbance caused by structural heterogeneity in the posterior left atrium is exacerbated by spatial variation of repolarization kinetics across this region. These results provide insight into mechanisms that may sustain paroxysmal atrial fibrillation. We conclude that image-based computer models that incorporate realistic descriptions of atrial myofiber architecture and electrophysiologic properties have the potential to analyse and identify complex substrates for atrial fibrillation.

A novel computational sheep atria model for the study of atrial fibrillation.

Sheep are often used as animal models for experimental studies into the underlying mechanisms of cardiac arrhythmias. Previous studies have shown that biophysically detailed computer models of the heart provide a powerful alternative to experimental animal models for underpinning such mechanisms. In this study, we have developed a family of mathematical models for the electrical action potentials of various sheep atrial cell types. The developed cell models were then incorporated into a three-dimensional anatomical model of the sheep atria, which was recently reconstructed and segmented based on anatomical features within different regions. This created a novel biophysically detailed computational model of the three-dimensional sheep atria. Using the model, we then investigated the mechanisms by which paroxysmal rapid focal activity in the pulmonary veins can transit to sustained atrial fibrillation. It was found that the anisotropic property of the atria arising from the fibre structure plays an important role in facilitating the development of fibrillatory atrial excitation waves, and the electrical heterogeneity plays an important role in its initiation.

An image-based model of atrial muscular architecture: effects of structural anisotropy on electrical activation.

BACKGROUND: Computer models that capture key features of the heterogeneous myofiber architecture of right and left atria and interatrial septum provide a means of investigating the mechanisms responsible for atrial arrhythmia. The data necessary to implement such models have not previously been available. The aims of this study were to characterize surface geometry and myofiber architecture throughout the atrial chambers and to investigate the effects of this structure on atrial activation. METHODS AND RESULTS: Atrial surface geometry and myofiber orientations were reconstructed in 3D at 50×50×50-µm(3) resolution from serial images acquired throughout the sheep atrial chambers. Myofiber orientations were determined by Eigen-analysis of the structure tensor. These data have been incorporated into an anatomic model that provides the first quantitative representation of myofiber architecture throughout the atrial chambers. By simulating activation on this 3D structure, we have confirmed the roles of specialized myofiber tracts such as the crista terminalis, pectinate muscles, and the Bachman bundle on the spread of activation from the sinus node. We also demonstrate how the complex myocyte arrangement in the posterior left atrium contributes to activation time dispersion adjacent to the pulmonary veins and increased vulnerability to rhythm disturbance generated by ectopic stimuli originating in the pulmonary vein sleeves. CONCLUSIONS: We have developed a structurally detailed, image-based model of atrial anatomy that provides deeper understanding of the role that myocyte architecture plays in normal and abnormal atrial electric function.

Electrophysiological models for the heterogeneous canine atria: computational platform for studying rapid atrial arrhythmias.

Heterogeneity in the electrical action potential (AP) properties can provide a substrate for atrial arrhythmias, especially at rapid pacing rates. In order to quantify such substrates, we develop a family of detailed AP models for canine atrial cells. An existing model for the canine right atrial (RA) myocyte was modified based on electrophysiological data from dog to create new models for the canine left atrium (LA), the interatrial Bachmann's bundle (BB), and the pulmonary vein (PV). The heterogeneous AP models were incorporated into a tissue strand model to simulate the AP propagation, and used to quantify conditions for conduction abnormalities (primarily, conduction block at rapid pacing rated) in the canine atria.

Mechanistic links between Na+ channel (SCN5A) mutations and impaired cardiac pacemaking in sick sinus syndrome.

RATIONALE: Familial sick sinus syndrome (SSS) has been linked to loss-of-function mutations of the SCN5A gene, which result in decreased inward Na(+) current, I(Na). However, the functional role of I(Na) in cardiac pacemaking is controversial, and mechanistic links between mutations and sinus node dysfunction in SSS are unclear. OBJECTIVE: To determine mechanisms by which the SCN5A mutations impair cardiac pacemaking. METHODS AND RESULTS: Action potential (AP) models for rabbit sinoatrial node (SAN) cells were modified to incorporate experimentally reported I(Na) changes induced by 2 groups of SCN5A gene mutations (affecting the activation and inactivation of I(Na), respectively). The cell models were incorporated into an anatomically detailed 2D model of the intact SAN-atrium. Effects of the mutations and vagal nerve activity on cardiac pacemaking at the single-cell and tissue levels were studied. Multielectrode extracellular potential recordings of activation pattern from intact SAN-atrium preparations were performed to test predictions of the models. At the single-cell level, the mutations slowed down pacemaking rates in peripheral, but not in central SAN cells that control the heart rhythm. However, in tissue simulations, the mutations not only slowed down pacemaking, but also compromised AP conduction across the SAN-atrium, leading to a possible SAN exit block or sinus arrest, the major features of SSS. Simulated vagal nerve activity amplified the bradycardiac effects of the mutations. Two groups of SCN5A mutations showed subtle differences in impairing the ability of the SAN to drive the surrounding atrium, primarily attributable to their differential effects on atrial excitability and conduction safety. Experimental data with tetrodotoxin and carbachol confirmed the simulation outcomes. CONCLUSIONS: Our study substantiates the causative link between SCN5A gene mutations and SSS and illustrates mechanisms by which the mutations impair the driving ability of the SAN.