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.
Electrophysiological simulations of the atria could improve diagnosis and treatment of cardiac arrhythmia, like atrial fibrillation or flutter. For this purpose, a precise segmentation of both atria is needed. However, the atrial epicardium and the electrophysiological structures needed for electrophysiological simulations are barely or not at all detectable in CT-images. Therefore, a model based segmentation of only the atrial endocardium was developed as a landmark generator to facilitate the registration of a finite wall thickness model of the right and left atrial myocardium. It further incorporates atlas information about tissue structures relevant for simulation purposes like Bachmanns bundle, terminal crest, sinus node and the pectinate muscles. The correct model based segmentation of the atrial endocardium was achieved with a mean vertex to surface error of 0.53 mm for the left and 0.18 mm for the right atrium respectively. The atlas based myocardium segmentation yields physiologically correct results well suited for electrophysiological simulations.
Atrial myofiber orientation is complex and has multiple discrete layers and bundles. A novel robust semi-automatic method to incorporate atrial anisotropy and heterogeneities into patient-specific models is introduced. The user needs to provide 22 distinct seed-points from which a network of auxiliary lines is constructed. These are used to define fiber orientation and myocardial bundles. The method was applied to 14 patient-specific volumetric models derived from CT, MRI and photographic data. Initial electrophysiological simulations show a significant influence of anisotropy and heterogeneity on the excitation pattern and P-wave duration (20.7% shortening). Fiber modeling results show good overall correspondence with anatomical data. Minor modeling errors are observed if more than four pulmonary veins exist in the model. The method is an important step towards creating realistic patient-specific atrial models for clinical applications.
Student Theses (1)
P. Neher. Model-based segmentation of the right atrium for electrophysiological simulations. Institut für Biomedizinische Technik, Karlsruher Institut für Technologie (KIT). Diplomarbeit. 2010