Determination of local myocardial electrical activation for activation sequence mapping. A statistical approach.

Abstract

Electrical activation sequence mapping requires accurate identification of local activation, but because extracellular recordings do not exclusively reflect local events, complex electrograms may be difficult to interpret. In such cases, the assignment of local activation is subject to error that could affect interpretation of the resulting activation maps. The purpose of this investigation was to develop an approach that would provide quantitative indexes of error in the determination of local activation. An electrode array with 64 closely spaced unipolar electrodes was used to record from the left ventricular surface during open heart surgery. Electrograms with multiple deflections were recorded from four patients with scarred myocardium; two other patients with normal myocardial function served as controls. Each of 784 deflections was scored on the basis of three features: evidence for propagation, the configuration of the bipolar signal, and the effect of changing from the chest to an average reference. Local activation was considered probable if evidence for all three features was present and improbable if none of the three features was present. Deflections that were ambiguous with respect to this standard were excluded. Of over 30 test variables analyzed, the three with the greatest power to discriminate signals due to local activation from those due to distant activity were 1) a linear combination of the extracellular potential plus the ratio of the second derivative and the extracellular potential, 2) the second derivative, and 3) the minimum (greatest negative) first derivative. For each of these variables, the threshold value providing the greatest performance was identified by the maximum quality of efficiency, an index of agreement. This statistical approach provides an objective basis for determining local activation and provides a quantitative assessment of error that could enhance interpretation of electrical activation sequence maps.