Abstract
Rotational activations, or spiral waves, are one of the proposed mechanisms for atrial fibrillation (AF) maintenance. We present a system for assessing the presence of rotational activity from intracardiac electrograms (EGMs). Our system is able to operate in real-time with multi-electrode catheters of different topologies in contact with the atrial wall, and it is based on new local activation time (LAT) estimation and rotational activity detection methods. The EGM LAT estimation method is based on the identification of the highest sustained negative slope of unipolar signals. The method is implemented as a linear filter whose output is interpolated on a regular grid to match any catheter topology. Its operation is illustrated on selected signals and compared to the classical Hilbert-Transform-based phase analysis. After the estimation of the LAT on the regular grid, the detection of rotational activity in the atrium is done by a novel method based on the optical flow of the wavefront dynamics, and a rotation pattern match. The methods have been validated using in silico and real AF signals.
Highlights
Atrial fibrillation (AF) is one of the most frequent sustained arrhythmias in clinical practice (Kirchhof et al, 2016), and is associated to increased morbidity (Wakili et al, 2011)
The rotational activity detection system is based on an analog to digital converter (ADC), a processing unit and a monitor to display the results
For this reason unipolar configuration is preferred as the electrical activation timing is well defined by the point of maximum negative slope, and activation maps can be built, on the expense of recording farfield ventricle activity, which can be later removed by using signal processing techniques
Summary
Atrial fibrillation (AF) is one of the most frequent sustained arrhythmias in clinical practice (Kirchhof et al, 2016), and is associated to increased morbidity (heart failure, ictus) (Wakili et al, 2011). The traditional theory for AF maintenance relies on multiple wavelets propagating at random in the atrial tissue (Moe, 1962; Allessie et al, 1985). Spatiotemporal stable sources (rotors) were proposed as the maintenance mechanism of AF (Jalife et al, 2002). The temporal stability characteristic of a rotor and its spiral wave pattern, compared to the multiple wavelet irregular propagation, facilitates the development of new algorithms that could detect and confirm the role of rotors as AF drivers. In the clinical practice the role of rotors as AF drivers is still controversial, with no confirmation nor acceptance of the rotor paradigm (Allessie and de Groot, 2014a,b; Narayan and Jalife, 2014)
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