Diagnosis of atrial flutter caused by ablation of atrial fibrillation is complex due to ablation scars. This paper presents an approach to replicate the clinically measured flutter circuit in a dynamic computer model. In a first step, important anatomical features of the flutter circuit are extracted manually based on the clinical measurement. With the help of this information, the electrical excitation propagation is simulated on the atrial geometry using the fast marching method. The simulated flutter circuit is used to estimate the global and local conduction velocity by approximating it iteratively. The parameterized flutter simulation is supposed to support the physician during diagnosis and treatment of atrial flutter.
Electrocardiographic imaging (ECGI) facilitates the non-invasive reconstruction of electrical activity in the entire heart at once. ECGI requires both recordings of multi-channel ECG signals as well as an MRI-based model of the thorax. The model is used to solve the underlying Poissons problem, which relates the gradient of transmembrane voltages in the heart to the ECG and is a spatial differential equation. In ECGI, this relationship has to be established before starting inverse calculations, i.e. the forward problem has to be solved. It solution depends strongly on the spatial discretization of the model, as its resolution affects the representation of the source gradients. To study the convergence of resolution-related effects in the forward problem, we use a simplified thorax model which allows for very high resolutions. An ECG is produced for the excitation origin of a premature ventricular contraction in the apex. The study reveals that the greatest resolution-related effects vanish below a resolution of 5 mm of the cardiac tissue. At below 1 mm, resolution effects stabilize and only marginal effects from the spatial structure of the mesh persist down to a resolution of 0.25 mm.
This handout describes the simulation dataset KIT-20-PVC_Simulation-1906-10-30, which was contributed by the Karlsruhe Institute of Technology (KIT) to the Experimental Data and Geometric Analysis Repository (EDGAR) database.
Student Theses (2)
J. Trächtler. Development of Semi-Automatic Segmentation Tools in a Virtual Reality Setting for Preoperative Planning. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Masterarbeit. 2017
Preoperative planning of complex and multifragmentary bone fractures is important in order to ensure a safe and successful surgery. For this purpose, a surgical planning tool was developed in a virtual reality environment in a previous work. However, this preop- erative planning tool requires a surface model of the segmented bone fragments. In order to ensure a fast and convenient preoperative planning, the segmentation workflow for the data generation should be embedded into the same virtual reality environment. Therefore, innovative segmentation tools in a virtual reality setting were developed in this work. This comprises an initial semi-automatic segmentation based on the Graph Cut method, an automatic generation of a 3D surface mesh representing the segmentation on the basis of the Marching Cubes algorithm including an anti-aliasing filtering as well as novel virtual reality tools for manual postprocessing the surface mesh.The implemented Graph Cut segmentation was performed in 3D and yielded promising results in terms of accuracy and performance with little user effort. Especially for larger data, the computation time was quite good and much better compared to previous work. Moreover, the Graph Cut segmentation can be updated by setting new seed points inter- actively which performed even faster than the initial segmentation.In order to compensate for inaccuracies of the initial semi-automatic segmentation, vir- tual reality tools were developed to manually post-process the surface mesh. These tools combine 2D imaging tools within the clinical scan and 3D mesh forming tools in an in- novative approach. For instance these tools can be used to separate connected segments, to indent and inflate the surface mesh or to add and remove single voxels in the clinical scan. Certain optimizations allowed a performant interaction of the tools as well as the automatic update of the 3D surface mesh and the displayed segmentation within the clin- ical scan. The tools obtained good results in terms of accuracy, handling and usability. However, the accuracy of the mesh forming tools was limited by the voxel resolution of the clinical data due to the fact that the mesh forming tools were performed in the voxel domain.In addition to a quantitative evaluation of the segmentation result in terms of accuracy, computation time and user effort, the developed segmentation tools were evaluated qual- itatively with respect to usability by means of a research study of 20 test persons.
J. Trächtler. Analysis of electrogram morphology and parameterization of a simulation environment for clinical cases of atrial flutter. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Bachelorarbeit. 2014
In the course of this work, two clinical cases of AFlut were examined with the goal of simulating the clinical flutter circuit in a computer model in order to support the physician during diagnosis and therapy of AFlut. Initially, anatomical features of the flutter circuit such as scars, were detected manually. With the help of the manual detection, the electrodes were classified and their signals analyzed. The analysis results did not show correlations between the morphology of the intracardiac EGM and the anatomical feature of the location of the corresponding electrode. Thus, the analysis results did not allow an automated detection of anatomical characteristics of the flutter circuit. The manual detection was used to parametrize the flutter circuit. Subsequently, the latter was simulated using the FaMa algorithm. The implemented methods enabled the FaMaS to deal with anatomical conditions of the clinical geometry, and thus to simulate clinical flutter circuits. In a further step, the FaMaS was used to estimate the global CV which provided good results. For the simulation of clinical cases of AFlut, it was necessary to estimate the local CV, for example to consider slow conduction areas. For simulated test cases, the estimation of the local CV led to good results. The local estimation for clinical cases of AFlut required several constraints. The clinical LAT maps which provided a basis for the approximation of the local CV, were interpolated and manually modified in the range of clinically realistic values. Besides, the range of the permissible CV was limited. By estimating the local CV, the propagation on the atrial surface can be approximated. The clinical measurement was not patterned exactly as the resulting LATs showed. To conclude, the FaMa algorithm was extended by implementations which enabled the fast simulation of clinical cases of AFlut, at which anatomical features of the flutter circuit were detected manually. The average CV can be approximated by the implemented global estimation method. With the help of the local estimation, the excitation propagation can be described, but the LAT results deviated too much from the clinical measurement. Due to manual editing, the procedure is not yet usable for automatic processing of clinical cases of AFlut. All in all, this work provided the interface between the clinical measurement and the simulation of AFlut in a fast computer model. The simulated flutter circuit was parametrized, and described the clinical measurement qualitatively.