Abstract:

This review article gives a comprehensive survey of the progress made in computa- tional modeling of the human atria during the last 10 years. Modeling the anatomy has emerged from simple peanut-like structures to very detailed models including atrial wall and fiber di- rection. Electrophysiological models started with just two cellular models in 1998. Today, five models exist considering e.g. details of intracellular compartments and atrial heterogeneity. On the pathological side, modeling atrial remodeling and fibrotic tissue are other important aspects. The bridge to data that are measured in the catheter laboratory and on the body surface (ECG) is under construction. Every measurement can be used either for model personalization or for validation. Potential clinical applications are briefly outlined and future research perspectives are suggested.

Abstract:

Atrial arrhythmias are frequently treated using catheter ablation during electrophysiological (EP) studies. However, success rates are only moderate and could be improved with the help of personalized simulation models of the atria. In this work, we present a workflow to generate and validate personalized EP simulation models based on routine clinical computed tomography (CT) scans and intracardiac electrograms. From four patient data sets, we created anatomical models from angiographic CT data with an automatic segmentation algorithm. From clinical intracardiac catheter recordings, individual conduction velocities were calculated. In these subject-specific EP models, we simulated different pacing maneuvers and measurements with circular mapping catheters that were applied in the respective patients. This way, normal sinus rhythm and pacing from a coronary sinus catheter were simulated. Wave directions and conduction velocities were quantitatively analyzed in both clinical measurements and simulated data and were compared. On average, the overall difference of wave directions was 15° (8%), and the difference of conduction velocities was 16 cm/s (17%). The method is based on routine clinical measurements and is thus easy to integrate into clinical practice. In the long run, such personalized simulations could therefore assist treatment planning and increase success rates for atrial arrhythmias.

Abstract:

Tissue heating during magnetic resonance measurements is a potential hazard at high-field MRI, and particularly, in the framework of parallel radiofrequency transmission. The heating is directly related to the radiofrequency energy absorbed during an magnetic resonance examination, that is, the specific absorption rate (SAR). SAR is a pivotal parameter in MRI safety regulations, requiring reliable estimation methods. Currently used methods are usually based on models which are neither patient-specific nor taken into account patient position and posture, which typically leads to the need for large safety margins. In this work, a novel approach is presented, which measures local SAR in a patient-specific manner. Using a specific formulation of Maxwell's equations, the local SAR is estimated via postprocessing of the complex transmit sensitivity of the radiofrequency antenna involved. The approximations involved in the proposed method are investigated. The presented approach yields a sufficiently accurate and patient-specific local SAR measurement of the brain within a scan time of less than 5 min.

Abstract:

Introduction: Atrial fibrillation (AF) is the most common cardiac arrhythmia affecting around 1% of the population. Several anti-arrhythmic drugs such as e.g. amiodarone or dronedarone influence cardiac electrophysiology reducing arrhythmias. However, the electrophysiological mechanisms underlying the initiation and persistence of AF are not completely understood yet.Methods: A mathematical model of atrial electrophysiology was modified to simulate the effects of chronic AF (cAF). Furthermore, ion channel conductivities were reduced according to the inhibition caused by two different concentrations of amiodarone and dronedarone. The resulting drug effects were investigated in healthy and cAF single-cells as well as in tissue. In a 1D tissue strand, restitution curves of the effective refractory period (ERP), the conduction velocity (CV) and the wavelength (WL) were computed. Furthermore, persistence of rotors in a 2D tissue patch was analyzed. For this purpose, four rotors were initiated in the cAF patch and then the drug effects were incorporated.Results: Dronedarone and amiodarone prolonged the atrial action potential duration of cAF cells, whereas high concentration of amiodarone slightly shortened it in healthy cells. Furthermore, both drugs increased the ERP and slowed the CV. Dronedarone shows the longer ERP and also a higher CV. As a result, the WL was prolonged by dronedarone and shortened by high concentration of amiodarone. Low concentration of amiodarone did not change the WL. In the 2D tissue patch, dronedarone altered significantly the trajectory of rotors, but did not terminate them.Conclusion: Computer simulations of the effects of antiarrhythmic drugs on cardiac electrophysiology are a helpful tool to better understand the mechanisms responsible for persistence and termination of AF. However, ion current measurement data available in literature show great variability of values depending on the species or temperature. Therefore, integration of drug effects into models of cardiac electrophysiology still needs to be improved.

Abstract:

Aims Amiodarone and cisapride are both known to prolong the QT interval, yet the two drugs have different effects on arrhythmia. Cisapride can cause torsades de pointes while amiodarone is found to be anti-arrhythmic. A computational model was used to investigate the action of these two drugs.Methods and results In a biophysically detailed model, the ion current conductivities affected by both drugs were reduced in order to simulate the pharmacological effects in healthy and ischaemic cells. Furthermore, restitution curves of the action potential duration (APD), effective refractory period, conduction velocity, wavelength, and the vulnerable window were determined in a one-dimensional (1D) tissue strand. Moreover, cardiac excitation propagation was computed in a 3D model of healthy ventricles. The corresponding body surface potentials were calculated and standard 12-lead electrocardiograms were derived. Both cisapride and amiodarone caused a prolongation of the QT interval and the refractory period. However, cisapride did not significantly alter the conduction-related properties, such as e.g. the wavelength or vulnerable window, whereas amiodarone had a larger impact on them. It slightly flattened the APD restitution slope and furthermore reduced the conduction velocity and wavelength.Conclusion Both drugs show similar prolongation of the QT interval, although they present different electrophysiological properties in the single-cell as well as in tissue simulations of cardiac excitation propagation. These computer simulations help to better understand the underlying mechanisms responsible for the initiation or termination of arrhythmias caused by amiodarone and cisapride.

Abstract:

Due to forthcoming use of MPI on humans there is an urgent need for a thorough research on possible adverse effects of this technique on patients health. However, the health impact of exposure to time-varying magnetic fields in a frequency range between 10 kHz and 100 MHz, such as the MPI drive field, are still poorly investigated.The current paper intends to give an overview on an in-silico approach to investigation of stimulating effects that could be caused by the MPI drive field. For this purpose, cell models of myocardiocyte, myocyte and neurocyte, as well as a suitable setup for the simulation of the exposure to time-varying magnetic fields have been developed. The evaluation of performed simulations was carried out on the basis of transmembrane voltage elevation and induced current densities.

Abstract:

The heart rate is mediated by the G protein-coupled muscarinic receptor (M2R) activating the acetylcholine (ACh)-dependent K+ current (IKACh). Here, a novel model for IKACh gating is presented based on recent findings that M2R agonist binding is voltage-sensitive. Furthermore, ACh and pilocarpine (Pilo) manifest opposite voltage-dependent IKACh modulation. In a previous work, a 4-state Markov model of M2R reconstructing the voltage-dependent change in agonist affinity was proposed. In this work, a 2-state Markov model of IKACh gating purely dependent on the Gβγ concentration is proposed. IKACh is modeled based on the description of Zhang et al. Measurement data are used to parametrize the combined M2R and IKACh model for both ACh and Pilo. The channel model has a linear Gβγ dependent forward and a constant backward rate. For ACh and Pilo, optimal values of model parameters are found reconstructing the measured opposite voltage-dependent change in agonist affinity. The combined model is able to reconstruct the measured data regarding the agonist and voltage-dependent properties of the M2R-IKACh channel complex. In future studies, this channel will be integrated in a sinus node model to investigate the effect of the channel properties on heart rate

Abstract:

Model-based segmentation approaches have been proven to produce very accurate segmentation results while simultaneously providing an anatomic labeling for the segmented structures. However, variations of the anatomy, as they are often encountered e.g. on the drainage pattern of the pulmonary veins to the left atrium, cannot be represented by a single model. Automatic model selection extends the model-based segmentation approach to handling significant variational anatomies without user interaction. Using models for the three most common anatomical variations of the left atrium, we propose a method that uses an estimation of the local fit of different models to select the best fitting model automatically. Our approach employs the support vector machine for the automatic model selection. The method was evaluated on 42 very accurate segmentations of MRI scans using three different models. The correct model was chosen in 88.1 % of the cases. In a second experiment, reflecting average segmentation results, the model corresponding to the clinical classification was automatically found in 78.0 % of the cases.

Abstract:

The analysis of the heart rate turbulence (HRT) can be used to evaluate the risk of sudden cardiac death. For that purpose ectopic beats have to be classified. A method for automatic ectopic beat detection and classification based on a Support-Vector-Machine (SVM) was developed before. In this work an analysis similar to the HRT was carried out on the morphological features of the QRS complex and the T wave of the ECG following a ventricular premature contractions (VPC). A study of 56 subjects, suffering from a various number of ventricular premature contractions was conducted.

Abstract:

Die Analyse der Herz Raten Turbulenz (HRT) dient der Vorhersage eines ploetzlichen Herztodes. Hierzu muessen die ektopen Schlaege im EKG ausgewertet werden. Zur automatischen Detektion und Klassifikation ektoper Schlaege wurde 2010 eine Methode entwickelt, welche auf Basis einer Support-Vector-Machine (SVM) die Schlaege klassifiziert. Artefakte im EKG-Signal fuehren nicht selten zur Fehlklassifizierung, da sie nicht vollstaendig von ektopen Schlaegen unterschieden werden koennen. Um die Genauigkeit die HRT Analyse zu verbessern, wurde ein Algorithmus zur automatischen Unterscheidung von Artefakten und ektopen Schlaegen entwickelt.

Abstract:

Whole organ scale patient specific biophysical simulations contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmia. However, many individual steps are required to bridge the gap from an anatomical scan to a personal- ized biophysical model. In biophysical modeling, differential equations are solved on spatial domains represented by volumetric meshes of high resolution and in model-based segmentation, surface or volume meshes represent the patients geometry. We simplify the personalization pro- cess by representing the simulation mesh and additional relevant struc- tures relative to the segmentation mesh. Using a surface correspondence preserving model-based segmentation algorithm, we facilitate the inte- gration of anatomical information into biophysical models avoiding a complex processing pipeline. In a simulation study, we observe surface correspondence of up to 1.6mm accuracy for the four heart chambers. We compare isotropic and anisotropic atrial excitation propagation in a personalized simulation.

Abstract:

In this paper we propose an iteratively regularized Gauss-Newton method to solve the inverse ECG problem and efficiently choose the parameter of regularization. The classical stopping criterium for this regularization technique Morozov discrepancy principle, cannot be used in our application because the noise level estimate and problem model error are typically not available. We formulate the stopping rule based on the statistical formulation of the parameter and the physiological nature of the sought solution. With Laplace operator as a regularization matrix, the regularization parameter can be seen as an indirect measure of deviation in the solution: smaller parameters lead to a broader solution range. From our knowledge about electrophysiology of the heart we can assume values of −85 mV and +25 mV as a lower and an upper estimates for transmembrane potentials. Under this assumption we stop Gaus-Newton iteration as soon as the difference between solution smallest and largest values achieves 110 mV. Three simulation protocols confirm our ansatz: the proposed method was compared with the commonly used in the feld L-curve based Tikhonov method, showing superior performance during an initial phase of an ectopic heart activation sequence.

Abstract:

Cardiac electrophysiology procedures are routinely used to treat patients with rhythm disorders. The success rates of ablation procedures and cardiac resynchronization therapy are still sub-optimal. Recent advances in medical imaging, image processing and cardiac biophysical modeling have the potential to improve patient outcome. This manuscript provides an overview of how these advances have been translated into the clinical environment.

Abstract:

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and is mainly sustained by reentrant circuits and rapid ectopic activity. In the present study, we performed computer simulations using a 3D human atrial model including fibre orientation, electrophysiological heterogeneities and tissue anisotropy. Membrane kinetics were described as in the human atrial action potential model by Maleckar et al., including AF-induced ionic remodeling. The impact of ionic changes on reentrant activity was investigated by characterizing arrhythmia stability, rotor dynamics and dominant frequency (DF). Our simulations show that reentrant circuits tend to organize around the pulmonary veins and the right atrial appendage. Simulated IK1 and INa blocks lead to slower DF in the whole atria, expanded wave meandering and reduction of secondary wavelets. INaK block slightly reduces DF and does not notably change the propagation pattern. Regularity and coupling indices of electrograms are usually higher in the right atrium than in the left atrium, entailing a higher likelihood of arrhythmia generation in the latter, as occurs in AF patients.

Abstract:

In this work, a simulation study is performed that demonstrates how activation times of cardiac action potentials can be reconstructed from body surface potential maps (BSPMs). An extrasystole is simulated in the ventricles, which are affected by myocardial ischemia or necrosis, and the related BSPM is calculated. Initial estimates are required for iterative algorithms that solve the related non-linear reconstruction problem. As a good initial estimate is essential for a proper reconstruction, the robustness of two methods is tested against the influence of pathological conditions: the critical times method and a linear timeintegral based method. While the first method extrapolates activation times into inactive tissue in this study, the latter carves out ischemic or necrotic tissue as homogeneous regions. In an outlook, a concept for the combination of both methods is proposed.

Abstract:

Generally, models of cardiac electrophysiology describe physiologic conditions in detail. However, other conditions, such as drug interactions or mutations of ion channels are of interest for research. Therefore, the simulated ion currents have to be fitted to measured voltage or patch clamp data. In this work, three different methods for the model parametrization were compared: one based on Powells algorithm implemented in a modular C++ framework and two optimization techniques realized in Matlab. The latter two approaches differed in solving the ordinary differential equations describing the channel gating. They can either be approximated numerically or solved analytically, since the transmembrane voltage is a piecewise constant function during the applied clamp protocol. All three methods were compared regarding computing time and quality of the fit using least squares. The modular C++ framework was slower than the numerical Matlab method, which took longer than the analytical one. The quality of the fit was similar for almost all analyzed methods. Therefore, the analytical method grants a fast and reliable solution for the calibration of ion current models for applications with constant membrane voltage, as e.g. in case of voltage or patch clamp data.

Abstract:

Various types of heart disease are associated with structural remodeling of cardiac cells. In this work, we present a software framework for automated analyses of structures and protein distributions involved in excitation-contraction coupling in cardiac muscle cells (myocytes). The software framework was designed for processing sets of three-dimensional image stacks, which were created by fluorescent labeling and scanning confocal microscopy of ventricular myocytes from a rabbit infarction model. Design of the software framework reflected the large data volume of image stacks and their large number by selection of efficient and automated methods of digital image processing. Specifically, we selected methods with small user interaction and automated parameter identification by analysis of image stacks. We applied the software framework to exemplary data yielding quantitative information on the arrangement of cell membrane (sarcolemma), the density of ryanodine receptor clusters and their distance to the sarcolemma. We suggest that the presented software framework can be used to automatically quantify various aspects of cellular remodeling, which will provide insights in basic mechanisms of heart diseases and their modeling using computational approaches. Further applications of the developed approaches include clinical cardiological diagnosis and therapy planning.

Abstract:

Anatomically realistic computational models provide a powerful platform for investigating mechanisms that underlie atrial rhythm disturbances. In recent years, novel techniques have been developed to construct structurally-detailed, image-based models of 3D atrial anatomy. However, computational models still do not contain full descriptions of the atrial intramural myofiber architecture throughout the entire atria. To address this, a semi-automatic rule-based method was developed for generating multi-layer myofiber orientations in the human atria. The rules for fiber generation are based on the careful anatomic studies of Ho, Anderson and co-workers using dissection, macrophotography and visual tracing of fiber tracts. Separately, a series of high color contrast images were obtained from sheep atria with a novel confocal surface microscopy method. Myofiber orientations in the normal sheep atria were estimated by eigen-analyis of the 3D image structure tensor. These data have been incorporated into an anatomical model that provides the quantitative representation of myofiber architecture in the atrial chambers. In this study, we attempted to compare the two myofiber generation approaches. We observed similar myo-bundle structure in the human and sheep atria, for example in Bachmann's bundle, atrial septum, pectinate muscles, superior vena cava and septo-pulmonary bundle. Our computational simulations also confirmed that the preferential propagation pathways of the activation sequence in both atrial models is qualitatively similar, largely due to the domination of the major muscle bundles.