Mapping of dominant frequency and complex fractionated electrograms in atrial fibrillation patients: Caveat medicus

Spatiotemporal behavior of high dominant frequency during paroxysmal and persistent atrial fibrillation in the human left atrium

BACKGROUND

Sites of high dominant frequency (DF(peak)) are thought to indicate the location of drivers of atrial fibrillation (AF), but characterization of their spatiotemporal distribution and stability, critical to their relevance as targets for catheter ablation, requires simultaneous global mapping of the left atrium.

METHODS AND RESULTS

Noncontact electrograms recorded simultaneously from 256 left atrial sites during spontaneous AF were analyzed. After subtraction of the ventricular component, fast Fourier transform identified the DF at each site. Focal areas of DF(peak) were defined as those having a DF >20% above all neighboring sites. Twenty-four patients with spontaneous AF (11 paroxysmal and 13 persistent) were studied. In paroxysmal AF, sites of DF(peak) (mean DF, 11.6±2.9 Hz) were observed in 100% of patients (present during 65% of the mapping period). In contrast, DF(peak) was detected in only 31% of patients with persistent AF (P<0.001) and for only 5% of the mapping period (P<0.001). In both groups, locations of DF(peak) varied widely in both consecutive and separated segments of AF (κ coefficient range, -0.07-0.22). Activation sequences around sites of DF(peak) did not demonstrate centrifugal activation that would be expected from focal drivers.

CONCLUSIONS

Focal areas of high DF are more frequent in paroxysmal than persistent AF, are spatiotemporally unstable, are not the source of centrifugal activation, and are not, therefore, indicative of fixed drivers of AF. In the absence of spatiotemporal stability, the success of ablation at sites of DF(peak) cannot be explained by elimination of fixed drivers.

Catheter ablation of atrial fibrillation guided by electrogram fractionation and dominant frequency analysis

Catheter ablation is an established therapeutic option for certain patients with atrial fibrillation (AF), but the reported success rates of anatomically oriented ablation techniques are low compared with those for other ablation indications, particularly for persistent AF. Electrophysiologically oriented ablation techniques have emerged over the last decade that aim at modifying the arrhythmogenic substrate to the extent that it cannot maintain fibrillatory activity. Electrogram-guided ablation procedures are the most common substrate-targeted ablation approaches and can be broadly divided into procedures that target atrial sites with particular electrogram characteristics in either the time domain (complex fractionated electrograms) or frequency components in the frequency domain (dominant frequencies). The concept of electrogram-based catheter ablation of AF by identifying complex fractionated electrograms and dominant frequency sites is valid only if these sites are temporally stable.

Frequency domain and time complex analyses manifest low correlation and temporal variability when calculating activation rates in atrial fibrillation patients

BACKGROUND

Atrial fibrillation (AF) activation rates have been calculated using both frequency domain and time complex analyses. Direct comparisons of these methods are limited. We report: (1) their correlation when measuring AF activation rates, (2) comparisons of recording durations required to minimize variability, and (3) differences in the temporal reproducibility.

METHODS

AF activation rates were calculated using domain frequency (DF) (via fast Fourier transform) and time complex (TC) (via beat-to-beat activation measurements) analyses. We compared: (1) AF frequencies derived from each method; (2) successively longer subinterval durations to their 16-second reference intervals, and (3) the correlation between consecutively collected 8-second segments and segments collected 10 minutes apart.

RESULTS

There was low intraclass correlation coefficient (ICC = 0.234) when comparing AF activation rates derived using DF versus TC analysis. There was no difference in the frequencies between any of the subintervals compared to their 16-second reference intervals, but variability of measurements was higher for intervals <8 seconds (P < 0.01). Correlations between successive segments and segments taken 10 minutes apart were 0.92 and 0.75 using DF analysis (P < 0.001), and 0.72 and 0.49 using TC analysis (P < 0.001).

CONCLUSIONS

There is low correlation between the DF and TC methods of analyzing AF activation rates. While AF rates do not differ between subintervals and 16-second reference electrograms, the variability of measurements is dependent upon the subinterval duration, and increases for durations less than 8 seconds. AF rates were prone to change over a 10-minute time period. These results point out existing clinical limitations of measuring atrial activation rates in AF patients.