Recurrent wavefront morphologies: a method for quantifying the complexity of epicardial activation patterns.
We have developed a method for quantifying the complexity of activation patterns observed during ventricular fibrillation (VF) that is based on our previously reported methodology for decomposing epicardial mapping data into a set of isolated wavefronts. One-half second datasets are acquired from a 21 x 24 array of unipolar electrodes (1 mm spacing), and the wavefronts are isolated. A correlation technique is used to compute the similarity between all possible pairs of the isolated wavefronts. From these data, the wavefronts are sorted into clusters, each of which represents a recurring wavefront morphology. We define multiplicity (M) as the number of clusters needed to account for 90% of the total activations in the VF episode. M measures the complexity of the rhythm. In repetitive patterns (e.g., sinus rhythm), M = 1, indicating that the same morphology repeatedly activates the mapped region. Typically, in VF, M > 1, with larger numbers representing more complex, disorganized patterns. As an example, we computed M at 5, 10, 15, and 20 sec after electrical induction of VF in six pigs. M decreased significantly (p < 0.001), suggesting increasing organization during this period.
Rogers
J M
JM
Department of Medicine, University of Alabama, Birmingham 35294-0019, USA.
Usui
M
M
KenKnight
B H
BH
Ideker
R E
RE
Smith
W M
WM
D000465:Algorithms; D000818:Animals; D001698:Biomedical Engineering; D004566:Electrodes; D004594:Electrophysiology; D010496:Pericardium / Q000503:physiopathology*; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013552:Swine; D014693:Ventricular Fibrillation / Q000209:etiology / Q000503:physiopathology*