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Identification of cardiac rhythm features by mathematical analysis of vector fields

Identification of cardiac rhythm features by mathematical analysis of vector fields,10.1109/TBME.2004.839636,IEEE Transactions on Biomedical Engineeri

Identification of cardiac rhythm features by mathematical analysis of vector fields   (Citations: 4)
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Automated techniques for locating cardiac arrhythmia features are limited, and cardiologists generally rely on isochronal maps to infer patterns in the cardiac activation sequence during an ablation procedure. Velocity vector mapping has been proposed as an alternative method to study cardiac activation in both clinical and research environments. In addition to the visual cues that vector maps can provide, vector fields can be analyzed using mathematical operators such as the divergence and curl. In the current study, conduction features were extracted from velocity vector fields computed from cardiac mapping data. The divergence was used to locate ectopic foci and wavefront collisions, and the curl to identify central obstacles in reentrant circuits. Both operators were applied to simulated rhythms created from a two-dimensional cellular automaton model, to measured data from an in situ experimental canine model, and to complex three-dimensional human cardiac mapping data sets. Analysis of simulated vector fields indicated that the divergence is useful in identifying ectopic foci, with a relatively small number of vectors and with errors of up to 30° in the angle measurements. The curl was useful for identifying central obstacles in reentrant circuits, and the number of velocity vectors needed increased as the rhythm became more complex. The divergence was able to accurately identify canine in situ pacing sites, areas of breakthrough activation, and wavefront collisions. In data from human arrhythmias, the divergence reliably estimated origins of electrical activity and wavefront collisions, but the curl was less reliable at locating central obstacles in reentrant circuits, possibly due to the retrospective nature of data collection. The results indicate that the curl and divergence operators applied to velocity vector maps have the potential to add valuable information in cardiac mapping and can be used to supplement human pattern recognition.
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    • ...Conduction properties are rather assessed in terms of conduction time [11], or CV is calculated from time consuming local activation time maps [12]–[14]...

    Frank M. Weberet al. Conduction Velocity Restitution of the Human Atrium—An Efficient Measu...

    • ...Current approaches [6]–[8], however, require additional efforts...
    • ...A three-point method estimates the local direction of propagation and the CV [6], [7], and also vectorfield analysis has been performed [8]...
    • ...In other studies, plane wavefronts are assumed as well [8]...

    Frank M. Weberet al. Wave-Direction and Conduction-Velocity Analysis From Intracardiac Elec...

    • ...Alternatively or complementarily to the scalar description provided by isochronal maps, propagating wavefronts can be vectorially represented in terms of velocity vector fields [3-8]...
    • ...Conversely, the measurement of conduction velocity in humans in the clinical setting has been limitedly performed [5;11], being conditioned by the data access afforded by the mapping systems available during electrophysiological studies...
    • ...Finally, mathematical operators, such as the divergence and curl, could be applied to velocity vector fields to reveal or quantify peculiar features of arrhythmias (e.g., presence of ectopic foci or reentrant activity) [5;8], thus supporting the cardiologist activation pattern recognition...

    M. Masèet al. Automatic reconstruction of activation and velocity maps from electro-...

    • ...For instance the modulus of the velocity vector provides indication on the conductive properties of the atrial substrate, evidencing inhomogeneities and slow-conduction areas, while the application of the rotor operator to the velocity vector field, as proposed in [6], would allow the identification of reentrant activity...

    M. Masèet al. Velocity Field Analysis of Activation Maps in Atrial Fibrillation A Si...

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