Abstract:

BACKGROUND: Complementary to clinical and experimental studies, computational cardiac modeling serves to obtain a comprehensive understanding of the cardiovascular system in order to analyze dysfunction, evaluate existing, and develop novel treatment strategies. OBJECTIVES: We describe the basics of multiscale computational modeling of cardiac electrophysiology from the molecular ion channel to the whole body scale. By modeling cardiac ischemia, we illustrate how in silico experiments can contribute to our understanding of how the pathophysiological mechanisms translate into changes observed in diagnostic tools such as the electrocardiogram (ECG). MATERIALS AND METHODS: Quantitative in silico modeling spans a wide range of scales from ion channel biophysics to ECG signals. For each of the scales, a set of mathematical equations describes electrophysiology in relation to the other scales. Integration of ischemia-induced changes is performed on the ion channel, single-cell, and tissue level. This approach allows us to study how effects simulated at molecular scales translate to changes in the ECG. RESULTS: Ischemia induces action potential shortening and conduction slowing. Hence, ischemic myocardium has distinct and significant effects on propagation and repolarization of excitation, depending on the intramural extent of the ischemic region. For transmural and subendocardial ischemic regions, ST segment elevation and depression, respectively, were observed, whereas intermediate ischemic regions were found to be electrically silent (NSTEMI). CONCLUSIONS: In silico modeling contributes quantitative and mechanistic insight into fundamental ischemia-related arrhythmogenic mechanisms. In addition, computational modeling can help to translate experimental findings at the (sub-)cellular level to the organ and body context (e. g., ECG), thereby providing a thorough understanding of this routinely used diagnostic tool that may translate into optimized applications.

Abstract:

Radiofrequency ablation has become a first-line approach for curative therapy of many cardiac arrhythmias. Various existing catheter designs provide high spatial resolution to identify the best spot for performing ablation and to assess lesion formation. However, creation of transmural and nonconducting ablation lesions requires usage of catheters with larger electrodes and improved thermal conductivity, leading to reduced spatial sensitivity. As trade-off, an ablation catheter with integrated mini electrodes was introduced. The additional diagnostic benefit of this catheter is still not clear. In order to solve this issue, we implemented a computational setup with different ablation scenarios. Our in silico results show that peak-to-peak amplitudes of unipolar electrograms from mini electrodes are more suitable to differentiate ablated and nonablated tissue compared to electrograms from the distal ablation electrode. However, in orthogonal mapping position, no significant difference was observed between distal electrode and mini electrodes electrograms in the ablation scenarios. In conclusion, catheters with mini electrodes bring about additional benefit to distinguish ablated tissue from nonablated tissue in parallel position with high spatial resolution. It is feasible to detect conduction gaps in linear lesions with this catheter by evaluating electrogram data from mini electrodes.

Abstract:

The monodomain model and finite element method are often used together to compute electrical excitation conduction in cardiac tissue. It is known that the choice of using mass lumping as well as the used ionic current integration method affect the resulting conduction velocities (CVs), especially at coarse resolutions. We describe how the regularity of node arrangement in tetrahedral grids also affects simulated CVs in a similar magnitude. We compare activation times (ATs) over a distance of 21.4 mm at different resolutions to a high resolution reference solution from a previously published benchmark. We show that triangulated grids are able to be within 10% of the reference solution up to a grid resolution of 0.6 mm, while results from regular grids already diverge by more than that at 0.4 mm. At 0.7 mm, a regular grid yields an AT of 80.01 ms, where a triangulated grid with less nodes results in 47.52 ms (reference solution 42.82 ms). We investigate how gradual perturbation of nodes from a regular grid effects AT, finding that CV monotonically increases with degree of node perturbation.

Abstract:

Using OpenCL, we developed a cross-platform software to compute electrical excitation conduction in cardiac tissue. OpenCL allowed the software to run parallelized and on different computing devices (e.g., CPUs and GPUs).We used the macroscopic mono-domain model for excitation conduction and an atrial myocyte model by Courtemanche et al. for ionic currents. On a CPU with 12 HyperThreading-enabled Intel Xeon 2.7 GHz cores, we achieved a speed-up of simulations by a factor of 1.6 against existing software that uses OpenMPI. On two high-end AMD FirePro D700 GPUs the OpenCL software ran 2.4 times faster than the OpenMPI implementation. The more nodes the discretized simulation domain contained, the higher speed-ups were achieved.

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:

The SuLMaSS project [1] will advance, develop, build, evaluate, and test infrastructure for sustainable lifecycle management of scientific software. The infrastructure is tested and evaluated by an existing cardiac electrophysiology simulation software project, which is currently in the prototype state and will be advanced towards optimal usability and a large and active user community. Thus, SuLMaSS is focused on designing and implementing application-oriented e-research technologies and the impact is three-fold: - Provision of a high quality, user-friendly cardiac electrophysiology simulation software package that accommodates attestable needs of the scientific community. - Delivery of infrastructure components for testing, safe-keeping, referencing, and versioning of all phases of the lifecycle of scientific software. - Serve as a best practice example for sustainable scientific software management. Scientific software development in Germany and beyond shall benefit through both the aforementioned best practice role model and the advanced infrastructure that will, in part, be available for external projects as well. With adding value for the wider scientific cardiac electrophysiology community, the software will be available under an open source license and be provided for a large share of people and research groups that can potentially leverage computational cardiac modeling methods. Institutional infrastructure will be extended to explore, evaluate and establish the basis for research software development regarding testing, usage, maintenance and support. The cardiac electrophysiology simulator will drive and showcase the infrastructure formation, thus serving as a lighthouse project. The developed infrastructure can be used by other scientific software projects in future and aims to support the full research lifecycle from exploration through conclusive analysis and publication, to archival, and sharing of data and source code, thus increasing the quality of research results. Moreover it will foster a community-based collaborative development and improve sustainability of research software.

Abstract:

Atrial fibrillation is a common cardiac arrhythmia. The disturbance of the normal repolarization process due to heterogeneous myocyte-fibroblast coupling might play a role for this disease. We investigate this interaction in the heterogeneous atrium using a computational approach. Human atrial myocyte computational models represent- ing 10 different regions of the atrium were each coupled to a human atrial fibroblast model and the impact of the myocyte-fibroblast coupling on action potential measures was investigated. Myocytes from the pulmonary vein are affected most by the coupling to fibroblasts. Action potential amplitude is reduced from 105 mV to 94 mV and the upstroke velocity changes from 192 V/s to 152 V/s, potentially reducing the conduction velocity. In general, the action potential dura- tion of myocytes with short action potentials is prolonged and that of those with long is shortened. The large effect on pulmonary vein action potentials is mainly due to reduced IK1 in these cells compared to other regions of the atrium. The strong effects of fibroblast cou- pling to pulmonary vein myocytes are likely to be an addi- tional reason for the crucial role of the pulmonary veins in atrial fibrillation.

Abstract:

Radiofrequency ablation (RFA) is a standard clinical procedure for treating many cardiac arrhythmias. In order to increase the success rate of this treatment, the evaluation of lesion development with the help of intracardiac electrogram (EGM) criteria has to be improved further. We are investigating in-vitro the electrophysiological characteristics of cardiac tissue by using fluorescence-optical and electrical techniques. In this project, it is intended to create ablation lesions under defined conditions in rat atria or ventricle and to determine the electrical activity in the myocardium surrounding these lesions less than 1 s after the ablation. Therefore, we developed a semi-automatic RFA procedure, which was integrated into an existing experimental setup. Firstly, a controllable protection circuit board was designed to galvanically isolate the sensitive amplifiers for measuring extracellular potentials during the ablation. Secondly, a real-time system was implemented to control and to autonomously monitor the RFA procedure. We verified each component as well as the different sequences of the RFA procedure. In conclusion, the expanded setup will be used in future in-vitro experiments to determine new EGM criteria to assess lesion formation during the RFA procedure.

Abstract:

Computational cardiac electrophysiology is an important tool in researching cardiovas- cular diseases and their treatments. This thesis describes mathematical models and nu- merical methods to compute electrophysiological activity in computational models of the heart and human body. The models presented comprise the mono- and bidomain models for electrically active tissue, as well as mathematical models of single cardiac cells.The mono- and bidomain models pose partial differential equations (PDEs). The finite dif- ferences method (FDM) and the more flexible finite element method (FEM) are presented as appropriate solution techniques. Both methods transform the PDEs into problems of linear algebra, namely sparse matrix-vector equations, which can be solved using itera- tive algorithms. Single cell models are posed in form of ordinary differential equations for which appropriate solution methods are described as well.The numerical methods and their various parameters are tested thoroughly in an estab- lished benchmark setup of the monodomain model. Results show that the newly imple- mented FEM produces more accurate results especially on coarse geometries. In fact, spa- tial resolution becomes almost irrelevant (within the tested range of 0.1 mm to 0.5 mm) when using the variant with a consistent mass matrix and a sufficiently irregular spatial sampling.Subsequently, similar tests are performed using the bidomain model, both on isolated tis- sue models, and on such that are surrounded with a passive conductive medium. Lastly, the methods are applied to a realistic geometry. A setup from a previously published sim- ulation study based on monodomain FDM simulations is redone using bidomain FEM simulations, greatly reducing the size of the simulation geometry from 181 million to less than half a million nodes. Resulting simulated body surface potential maps (BSPMs) and electrocardiograms (ECGs) do not completely match the previously simulated, but are promising first steps. Work remains to be done on proper adaption of bidomain con- ductivities to the monodomain setup or measured data. The results obtained using FEM are especially promising with regard to a possible coupling of electrophysiological simu- lations with mechanical simulations, where the simulation geometry is deformed during simulation.