Heart rhythm disorders affect a significant part of the global population. Computational approaches have been increasingly used to better understand the dynamics of cardiac arrhythmias. Several recent clinical and experimental studies suggest that atrial fibrillation (AF) episodes can be initiated by ectopic beats and are maintained by re-entrant drivers (e.g. rotors) which, in many circumstances, have an organising centre (tip of the rotor).
In 3D computational models of the atria, rotors are scroll waves that rotate around a line of point singularities (PSs) called filaments. When such a filament intersects the surface of the atrium, a single PS occurs on the surface. Various methods have been proposed to automatically detect these PSs avoiding visual inspection.
In this work, the student will perform a quantitative analysis of both filaments and phase singularities dynamics in different arrhythmic episodes initiated by ectopic beats. The student will focus on discriminating stable from unstable rotors, obtaining the number of PSs and duration of each episode, discerning areas vulnerable to initiation from areas prone to maintain reentries. The result of the thesis will be a set of metrics based on filament dynamics to assess vulnerability of a given atrial model.
To do so, the student will exploit the phase singularity detection method already implemented in Cardiac Arrhythmia Research Package (CARP), which outputs for each time step the location of the detected re-entrant drivers. The student will implement a method to automatically track rotor dynamics from the output of the filament detection algorithm.