Abstract: Acquiring adequate mapping data in patients with atrial fibrillation is still one of the main obstacles in the treatment of this atrial arrhythmia. Due to the lack of catheters with both a panoramic field of view and sufficient electrode density for simultaneous mapping, electrophysiologists are forced to fall back on sequential mapping techniques. But, because activation patterns change rapidly during atrial fibrillation, they cannot be mapped sequentially. We propose that mapping tissue properties which are time independent, in contrast, allows a sequential approach. Here, we use the shortest measured electrogram cycle length to estimate the effective refractory period of the underlying tissue in a simulation study. Atrial fibrillation was simulated in a spherical model of the left atrium comprised of regions with varied refractory period. We found that the minimal measured electrogram cycle length correlates with the effective refractory period of the underlying tissue if the regions with distinct refractory properties are large enough and if the absolute difference in effective refractory periods is sufficient. This approach is capable of identifying regions of lowered effective refractory period without the need for cardioversion. Those regions are likely to harbor drivers of atrial fibrillation, which emphasizes the necessity of their localization.
Abstract: This work aimed at the detection of rotor centers within the atrial cavity during atrial fibrillation on the basis of phase singularities. A voxel based method was established which employs the Hilbert transform and the phase of unipolar electrograms. The method provides a 3D overview of phase singularities at the endocardial surface and within the blood volume. Mapping those phase singularities from the inside of the atria at the endocardium yielded rotor center trajectories.We discuss the results for an unstable and a more stable rotor. The side length of the areas covered by the trajectories varied from 1.5mm to 10 mm. These results are important for cardiologists who target rotors with RF ablation in order to cure atrial fibrillation.
Abstract: Atrial fibrillation is a common irregular heart rhythm. Until today there is still a need for research to quantify typical signal characteristics of rotors, which can induce atrial fibrillation. In this work, signal characteristics of a stable and a more unstable rotor in a realistic heart model including fiber orientation were analyzed with the following methods: peak-to-peak amplitude, Hilbert phase, approximate entropy and RS-difference. In this simulation model the stable rotor rotated with a cycle length of 145 ms and stayed in an area of 1.5 mm x 3 mm. Another more unstable rotor with a cycle length of 190msmovedinanareaof10mmx4mm. Inadistance of 2 mm to the rotor tip, the peak-to-peak amplitude decreased significantly, whereas the RS-difference and the approximate entropy were maximal. The rotor center trajectories were detected by phase singularity points determined by the Hilbert transform. We showed that more unstable rotors resulted in more amplitude changes over time and also the cycle length differed more. Furthermore, we presented typical activation time patterns of the Lasso catheter centered at the rotor tip and in different distances to the rotor tip. We suggest that cardiologists use a combination of the described methods to determine a rotor tip position in a more robust manner.
Student Thesis (1)
L. A. Unger. Simulation based Estimation of Parameters for Reentries in Human Atria.
Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Bachelor Thesis. 2014
Abstract: Acquiring adequate mapping data in patients with atrial fibrillation (AFib) is one of the main obstacles in the treatment of this arrhythmia. Due to the lack of catheters with both a panoramic field of view and sufficient electrode density for simultaneous mapping, electrophysiologists are forced to fall back on sequential mapping techniques to identify activation patterns. However, this approach is insufficient for rapidly changing patterns as they typically occur during AFib. In contrast to activation time mapping, substrate mapping avoids this drawback by analyzing time independent tissue properties. While most of the existing methods for substrate mapping do not reflect actual tissue properties but certain electrogram features, the results suffer from dependencies on parameters of data analysis or are limited to harmonic signals. Here, we investigate the potential and limitations of measured electrogram cycle lengths to derive information about the effective refractory period of the underlying tissue during sequences of AFib. Following theoretical considerations, areas with decreased effective refractory period are likely to harbor AFib drivers.
In a first step, different parametrizations of the Courtemanche-Ramirez-Nattel model with varying ERP served as substrates for bidomain simulations of AFib in a spherical model of the left atrium. Circular regions of deviating effective refractory period with radii between 9 mm and 19 mm were imposed. We found that the minimal measured electrogram cycle length correlates with the effective refractory period of the underlying tissue if the regions with distinct refractory properties are large enough and if the absolute difference in effective refractory periods is significant. Rhythms of high complexity which cause many other mapping approaches to come up against limiting factors favor the here introduced method as statistics profit from the variability in observed events.
In a second step, the clinical feasibility of using measured cycle length statistics to conclude on the underlying ERP of the tissue was investigated. Lacking ground truth data providing reliable in vivo information on the ERP of the tissue, final validations of our hypotheses remain due. The 25 % quantile of cycle lengths was used rather than the minimum in favor of improved robustness in clinical application. The cycle length analysis in patient data yielded physiologically reasonable results with locally low gradients but globally differing statistics. Both the in silico and the clinical test of concept study suggested that applying statistical measures such as the 25 % quantile to measured electrogram cycle lengths is capable of revealing information on the effective refractory period of the underlying tissue. This, in turn, is of particular clinical interest, as regions of lowered effective refractory period are likely to harbor AFib drivers.