Spectral analysis of activation time sequences.

Adequate spatial resolution of local activation is fundamental for the correct depiction of myocardial activation during ablative treatment of ventricular tachycardia. The widest allowable distances between recording sites that provide an accurate description of the field potential distribution is dictated by the Nyquist sampling theorem. Activation times are derived from the field potentials. However, because of noise intrinsic in activation detection algorithms, closer recording sites may be required than those theoretically computed. The purpose of this study is to examine the spatial frequency spectrum of epicardial activation time sequences computed by common activation detection algorithms, determine which algorithm is least noisy, and derive the recording site density necessary to avoid distortion of the epicardial activation map. Using 40 to 80 electrode linear arrays, monopolar and bipolar electrograms from the epicardium were recorded vertically (base to apex) and horizontally in 11 dogs. Activation times for bipolar electrograms were estimated using Peak, Fastest Zero Crossing, and Morphological algorithms. Activation times for monopolar electrograms were set equal to the time of the fastest negative deflection. Activation time sequences were analyzed using conventional Fourier techniques. Anomalous activation times from serially adjacent bipolar electrograms, which constitute algorithm noise, were studied. Horizontal and vertical interelectrode distances are 3.2 mm and 2.4 mm, respectively. Of the bipolar algorithms, the Morphological algorithm produced the fewest anomalous activation times. Mapping systems having more than 256 channels are required for accurate representation of epicardial activation in a typical 20-kg dog. The endocardial electrode spacing is unknown, but is expected to be at least as dense. Large global mapping systems or regionally dense arrays may offer advantages during catheter ablations for ventricular tachycardia and for studies into the mechanisms of ventricular tachycardia by accurately defining the cardiac activation pattern.

Duke Scholars

Author Carl F. Pieper Biostatistics & Bioinformatics, Division of Biostatistics