Dominant Frequency Mapping of Atrial Fibrillation: Comparison of Contact and Noncontact Approaches

• Published in: Journal of cardiovascular electrophysiology 2009-09, Vol.20 (9), p.997-1004
• Main Authors: GOJRATY, SATTAR, LAVI, NIMROD, VALLES, ERMENGOL, KIM, STEVEN J., MICHELE, JOHN, GERSTENFELD, EDWARD P.
• Format: Article
• Language: English
• Subjects: Algorithms; Animals; atrial fibrillation; Atrial Fibrillation - diagnosis; Atrial Fibrillation - physiopathology; Body Surface Potential Mapping - methods; Diagnosis, Computer-Assisted - methods; Dogs; Fourier transform; noncontact mapping; Reproducibility of Results; Sensitivity and Specificity; signal processing
• ISSN: 1045-3873; 1540-8167
• DOI: 10.1111/j.1540-8167.2009.01488.x

Introduction: The ability to acquire a dominant frequency (DF) map during atrial fibrillation (AF) instantaneously using noncontact mapping has significant advantages over the current sequential contact mapping approach; however, the relationship between DFs determined from contact bipolar and noncontact unipolar recordings is unknown. We sought to determine the difference between DFs determined using contact bipolar, contact unipolar, noncontact unipolar, and noncontact pseudobipolar recordings. Methods: Sustained AF was induced in 5 canines with 10 weeks of atrial tachy‐pacing at 440 ppm. A noncontact multielectrode array was positioned in the left atrium (LA). Two simultaneous contact signals (unipolar and bipolar) and 3 noncontact signals (unipolar, pseudobipolar, and pseudobipolar Laplacian) were recorded from multiple LA sites. Fourier analysis was performed, and the DFs of contact and noncontact signals were compared. Results: Recordings were obtained from 389 LA locations in 5 canines. The correlation was best between contact bipolar and noncontact QRS‐subtracted unipolar signals (r = 0.58, P < 0.001), and weaker between contact bipolar and noncontact best‐fit pseudobipolar (r = 0.50, P < 0.01) and noncontact Laplacian bipolar (r = 0.49, P < 0.01). There was no significant difference in the mean DFs between contact bipolar and noncontact unipolar signals; however, there was a significant difference in the DFs comparing contact bipolar to noncontact pseudobipolar signals (11.6 ± 1.8 vs 11.2 ± 2.5 Hz; P = 0.004) and a small nonsignificant difference comparing contact bipolar DF and noncontact pseudobipolar Laplacian DF (11.4 ± 1.8 vs 11.1 ± 1.6 Hz; P = NS). Conclusions: We found that estimation of DFs using noncontact mapping is feasible and that QRS‐subtracted noncontact unipolar signals perform better than noncontact pseudobipolar signals at estimating contact bipolar DFs. This has important implications for developing algorithms for noncontact frequency mapping of AF.