Detection of phase singularities in triangular meshes.

OBJECTIVES: Phase singularities have become a key marker in animal and computer models of atrial and ventricular fibrillation. However, existing algorithms for the automatic detection of phase singularities are limited to regular, quadratic mesh grids. We present an algorithm to automatically and exactly detect phase singularities in triangular meshes. METHODS: For each node an oriented path inscribing the node with one unit of spatial discretization is identified. At each time step the phase information is calculated for all nodes. The so-called topological charge is also computed for each node. A non-zero (+/- 2pi) charge is obtained for all nodes with a path enclosing a phase singularity. Thus all charged nodes belonging to the same phase singularity have to be clustered. RESULTS: With the use of the developed algorithm, phase singularities can be detected in triangular meshes with an accuracy of below 0.2 mm - independent of the type of membrane kinetics used. CONCLUSIONS: With the possibility to detect phase singularities automatically and exactly, important quantitative data on cardiac fibrillation can be gained.

Localizing the accessory pathway in ventricular preexcitation patients using a score based algorithm.

OBJECTIVES: Clinical data was analyzed to find an efficient way to localize the accessory pathway in patients with ventricular preexcitation. METHODS: The delta wave morphologies and ablation sites of 186 patients who underwent catheter ablation were analyzed and an algorithm ("locAP") to localize the accessory pathway was developed from the 84 data sets with a PQ interval ≤0.12s and a QRS width ≥0.12s. Fifty additional patients were included for a prospective validation. The locAP algorithm ranks 13 locations according to the likelihood that the accessory pathway is localized there. The algorithm is based on the locAP score which uses the standardized residuals of the available data sets. RESULTS: The locAP algorithm's accuracy is 0.54 for 13 locations, with a sensitivity of 0.84, a specificity of 0.97, and a positive likelihood ratio of 24.94. If the two most likely locations are regarded, the accuracy rises to 0.79, for the three most likely locations combined the accuracy is 0.82. This new algorithm performs better than Milstein's, Fitzpatrick's, and Arruda's algorithm both in the original study population as well as in a prospective study. CONCLUSIONS: The locAP algorithm is a valid and valuable tool for clinical practice in a cardiac electrophysiology laboratory. It could be shown that use of the locAP algorithm is favorable over the localizing algorithms that are in clinical use today.