Recurrent wavefront morphologies: a method for quantifying the complexity of epicardial activation patterns

Ann Biomed Eng. 1997 Sep-Oct;25(5):761-8. doi: 10.1007/BF02684160.

Abstract

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.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms
  • Animals
  • Biomedical Engineering
  • Electrodes
  • Electrophysiology
  • Pericardium / physiopathology*
  • Signal Processing, Computer-Assisted
  • Software
  • Swine
  • Ventricular Fibrillation / etiology
  • Ventricular Fibrillation / physiopathology*