Use of cardiac electric near-field measurements to determine activation times

Ann Biomed Eng. 2003 Oct;31(9):1066-76. doi: 10.1114/1.1603258.

Abstract

In a recent paper, we described the behavior of the cardiac electric near-field, E, parallel to the tissue surface during continuous conduction. We found that T(E), the time at which the peak near-field, E, occurs, is an accurate marker of local activation time. Examination of experimentally recorded E vector loops revealed a large variety of morphologies. We postulated that propagation around an obstacle could lead to the observed deviations in loop morphology. The purpose of this study was to determine if this was plausible, and if so, whether T(E) remains an accurate time marker of local activation under these conditions. We used a monodomain computer model of a sheet of cardiac tissue with a central conduction obstacle immersed in an unbounded volume conductor. Activation times T(Im), T(phi), and T(E) were derived from the transmembrane current I(m), the extracellular potential phi(e), and E, respectively. The obstacle led to deformations of the vector loops, morphologically similar to those observed experimentally, particularly during the initial and terminal phases, and to a lesser degree near the time of E. Despite these loop deformations, T(E) was an accurate time marker of local activation. We found that T(E) was significantly closer to T(Im) than T(phi). We concluded that isochrone maps computed from T(E) better reflect intracellular activation patterns than those computed from T(phi). For a given electrode spacing of 60 microm, the sensitivity to noise of E was significantly less than that of phi(e). Hence, T(E) was less affected by noise than T(phi).

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Atrial Function / physiology
  • Body Surface Potential Mapping / methods*
  • Computer Simulation
  • Electromagnetic Fields*
  • Heart Conduction System / physiology*
  • Models, Cardiovascular*
  • Models, Neurological*
  • Myocardial Contraction / physiology*
  • Neural Conduction / physiology*
  • Rabbits
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Stochastic Processes