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Published on: July 29, 2011
Evaluating fluctuations in human atrial fibrillatory cycle length using monophasic action potentials
Sanjiv M Narayan1, David E Krummen, Andrew M Kahn
1Electrophysiology Service, University of California and Veterans Affairs Medical Centers, San Diego, California 92161, USA. snarayan@ucsd.edu
Insights
Autocorrelation accurately measures atrial fibrillation cycle length, outperforming spectral dominant frequency, especially in bipolar signals. Stable measurements require over 10 seconds, revealing that cycle length changes precede organization shifts.
Area of Science:
- Electrophysiology
- Cardiac Arrhythmias
- Signal Processing in Medicine
Background:
- Identifying short atrial fibrillation (AF) cycle length (CL) sites is crucial for ablation targets, as cycle lengthening predicts success.
- Optimal methods for measuring AF CL and its stability remain unclear, necessitating advanced signal analysis techniques.
- Spectral dominant frequency (DF) may be prone to double counting, while autocorrelation offers a potentially more accurate estimation method.
Purpose of the Study:
- To investigate fluctuations in intracardiac atrial fibrillation (AF) cycle length (CL).
- To compare the accuracy and stability of autocorrelation versus spectral dominant frequency (DF) for AF CL measurement.
- To determine the optimal duration for stable AF CL assessment.
Main Methods:
- Analysis of 49 AF epochs from 28 patients using monophasic action potentials (MAPs) from the high (HRA) and low (LRA) right atrium.
- Estimation of AF CL using spectral DF and autocorrelation over varying durations (2 seconds, 10 seconds, 2 minutes) in MAPs and filtered bipoles.
- Comparison of measurement accuracy and error rates between spectral DF and autocorrelation methods.
Main Results:
- Autocorrelation demonstrated superior accuracy in estimating both MAP (R=0.92) and bipolar (R=0.83) AF CL compared to spectral DF.
- Spectral DF showed poor correlation with bipolar signals (R=0.31) but good correlation with MAPs (R=0.73), indicating susceptibility to double counting.
- Changes in DF consistently preceded reciprocal changes in organization, while AF CL measurements were stable when analyzed over 10 seconds or longer.
Conclusions:
- Autocorrelation is a more reliable method for estimating AF CL than spectral DF, particularly for bipolar signals.
- AF CL measurements are stable and reliable when analyzed over durations exceeding 10 seconds.
- Observed fluctuations indicate that AF CL changes precede organization changes, offering insights into AF dynamics.
Objective:
To study fluctuations in intracardiac atrial fibrillation (AF) cycle length (CL).
Background:
Sites of short AF CL may be good ablation targets, and cycle lengthening predicts ablation success. However, the optimum method for measuring AF CL, and its stability, are unclear. We hypothesized that autocorrelation better estimates AF CL than spectral dominant frequency (DF), which is susceptible to double counting, using monophasic action potentials (MAPs) to separate atrial activation from artifact.
Methods:
In 28 patients with paroxysmal or persistent AF, we analyzed 49 AF epochs using MAPs at the high (HRA) and low (LRA) right atrium. We estimated AF CL over 2 seconds, 10 seconds, and 2 minutes using spectral DF and autocorrelation in MAPs and filtered bipoles.
Results:
In the HRA, manually measured CL was 167 +/- 25 ms. Spectral DF poorly estimated AF CL in bipolar signals (R = 0.31; P = NS), due to double counting, but accurately estimated MAP CL (R = 0.73, P < 0.001). Autocorrelation estimated MAP (R = 0.92; P < 0.001) and bipolar (R = 0.83; P < 0.001) CL, with lower errors than spectral DF (P < 0.0001). Over time, changes in DF consistently preceded reciprocal changes in organization (P < 0.001). Finally, excluding inaccurate spectra, DF and AF organization differed between HRA and LRA over 2 seconds, but correlated over 10 seconds and 2 minutes (P < 0.05).
Conclusions:
AF CL is better estimated by autocorrelation than spectral DF, particularly for bipoles, and stable when measured for >10 seconds. Notably, changes in AF CL preceded reciprocal changes in organization, yet changes in organization did not precede changes in AF CL. These results may help to interpret AF CL fluctuations.
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