Atrial conduction velocity mapping algorithms can be classified into local, global, and inverse methods, each with distinct advantages regarding biophysics, uncertainty quantification, and atrial geometry.
Characterizing patient-specific atrial conduction properties is important for understanding arrhythmia drivers, for predicting potential arrhythmia pathways, and for personalising treatment approaches. One metric that characterizes the health of the myocardial substrate is atrial conduction velocity, which describes the speed and direction of propagation of the electrical wavefront through the myocardium. Atrial conduction velocity mapping algorithms are under continuous development in research laboratories and in industry. In this review article, we give a broad overview of different categories of currently published methods for calculating CV, and give insight into their different advantages and disadvantages overall. We classify techniques into local, global, and inverse methods, and discuss these techniques with respect to their faithfulness to the biophysics, incorporation of uncertainty quantification, and their ability to take account of the atrial manifold.
Coveney et al. (Fri,) conducted a review in Atrial arrhythmias. Atrial conduction velocity mapping was evaluated. Atrial conduction velocity mapping algorithms can be classified into local, global, and inverse methods, each with distinct advantages regarding biophysics, uncertainty quantification, and atrial geometry.
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