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. 2021 Mar 26:12:652128.
doi: 10.3389/fphys.2021.652128. eCollection 2021.

Signal Fingerprinting as a Novel Diagnostic Tool to Identify Conduction Inhomogeneity

Affiliations

Signal Fingerprinting as a Novel Diagnostic Tool to Identify Conduction Inhomogeneity

Ziliang Ye et al. Front Physiol. .

Abstract

Background: Inhomogeneous intra-atrial conduction facilitates both initiation and perpetuation of atrial fibrillation (AF) and is reflected in electrogram (EGM) morphology.

Objective: The primary objective of this study is to investigate regional differences in features of different EGM types during sinus rhythm (SR) and to design a patient-specific signal fingerprint, which quantifies the severity and extensiveness of inhomogeneity in conduction.

Methods: Patients (N = 189, 86% male; mean age 65 ± 9 years) undergoing coronary artery bypass grafting (CABG) underwent high-resolution mapping of the right atrium (RA), left atrium (LA), and pulmonary vein area (PVA) including Bachmann's bundle (BB). EGMs during 5 s of SR were classified as single potentials (SPs), short double potentials (SDPs, interval between deflections < 15 ms), long double potentials (LDPs, deflection interval > 15 ms), or fractionated potentials (FPs, ≥3 deflections). Of all SPs, differences in relative R- and S-wave amplitude were calculated (R/S ratios). Time difference between first and last deflection was determined (fractionation duration, FD) and potentials with amplitudes < 1.0 mV were labeled as low-voltage. Conduction block (CB) was defined as a difference in local activation time (LAT) between adjacent electrodes of ≥12 ms.

Results: A total of 1,763,593 EGMs (9,331 ± 3,336 per patient) were classified (Table 1).

Conclusion: The signal fingerprint, consisting of quantified EGM features, including the R/S ratio of SPs, the relative frequency distribution of unipolar voltages, the proportion of low-voltage areas, the proportion of the different types of EGMs, and durations of LDP and FDP, may serve as a diagnostic tool to determine the severity and extensiveness of conduction inhomogeneity. Further studies are required to determine whether the signal fingerprint can be used to identify patients at risk for AF onset or progression.

Keywords: cardiac surgery; conduction; electrogram analysis; mapping; sinus rhythm.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The upper left panel demonstrates a schematic presentation of the 192-unipolar electrode array and the projection of this array on a schematic posterior view of the atria. The lower left panel demonstrates typical examples of the different types of EGMs classified in this study. The right panel shows a color-coded activation map; isochrones (thin black lines) are drawn at 10 ms intervals and the black arrow indicates wavefront propagation. IVC, inferior vena cava; SVC, superior vena cava; RA, right atrium; BB, Bachmann’s bundle; LA, left atrium; PV(A), pulmonary vein (area); EGM, electrogram; SP, single potential; SDP, short double potential; LDP, long double potential; FP, fractionated potential.
FIGURE 2
FIGURE 2
The upper left panel shows the proportion of long double and fractionated potentials for each individual patient; patients are ranked according to an increase in fractionation. The lower panel demonstrates typical examples of color-coded signal maps from four different patients, showing the proportion of the different EGM types at the various recording sites. These maps correspond to the patients marked in the graph by colored dots (green, yellow, orange, and red). FP, fractionated potential; EGM, electrogram; LDP, long double potential; SDP, short double potential; SP, single potential.
FIGURE 3
FIGURE 3
Median R/S ratios, voltage, and proportion of low-voltage areas plotted for each individual patient; patients are ranked according to increasing values of these parameters. The median value of each parameter is indicated by the horizontal line.
FIGURE 4
FIGURE 4
Relative incidence of fractionated potentials at Bachmann’s bundle of a subset of 123 patients who were mapped with the 192-electrode array. LA, left atrium; RA, right atrium.
FIGURE 5
FIGURE 5
Histograms of the relative frequency distribution of all voltages (upper), R/S ratios (middle), and fractionation durations (lower) recorded at the right atrium (blue), Bachmann’s bundle (orange), pulmonary vein area (green), and left atrium (red). Median voltage values are indicated by the black dotted lines. All histograms are subdivided and stacked according to the potential type classification (SP, SDP, LDP, or FP). SP, single potential; SDP, short double potential; LDP, long double potential; FP, fractionated potential.
FIGURE 6
FIGURE 6
Boxplots depicting the median value of the EGM features for each region separately. Statistical significance for comparison between all other atrial regions is indicated by an asterisk. SP, single potential; SDP, short double potential; LDP, long double potential; FP, fractionated potential; FD, fractionation duration.
FIGURE 7
FIGURE 7
Two examples of a signal fingerprint obtained from one patient with a low and one with a high degree of inhomogeneity in conduction. The upper panels show the distribution of potential types of the entire (left, pie plot) and for each region separately (right, stacked bars). The middle left plot shows the R/S ratio distribution of all SPs of the entire atrium. The middle center bar plot displays the number of low-voltage potentials plotted for each region separately. The middle right plot shows the distribution of voltages (mV) of SPs (green), SDPs (yellow), LDPs (orange), and FPs (red) from all atrial regions. The lower panel displays the distribution of fractionation duration (ms) for LDPs (left) and FPs (right). SP, single potential; SDP, short double potential; LDP, long double potential; FP, fractionated potential; FD, fractionation duration.

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