Key result
Time-aligned unipolar electrogram eigenvalue dominance ratio (RA) achieved 94% accuracy in detecting atrial fibrosis compared to 86% for standard bipolar electrogram voltage maps.
Why the study?
Standard bipolar electrogram voltage mapping for atrial fibrosis disregards signal spatiotemporal information and is sensitive to catheter orientation.
Does the eigenvalue dominance ratio (EIGDR) of unipolar electrograms improve the detection accuracy of atrial fibrosis compared to standard bipolar voltage mapping?
Does the eigenvalue dominance ratio (EIGDR) of unipolar electrograms improve the detection accuracy of atrial fibrosis compared to standard bipolar voltage mapping?
Absolute Event Rate: 94% vs 86%
Eigenvalue dominance ratio of unipolar electrograms provides higher accuracy for detecting atrial fibrosis compared to standard bipolar voltage mapping in simulated models.
May refine fibrosis mapping in AF ablation; leaves open validation in human cohorts.
Atrial fibrosis plays a key role in the initiation and progression of atrial fibrillation (AF). Atrial fibrosis is typically identified by a peak-to-peak amplitude of bipolar electrograms (b-EGMs) lower than 0.5 mV, which may be considered as ablation targets. Nevertheless, this approach disregards signal spatiotemporal information and b-EGM sensitivity to catheter orientation. To overcome these limitations, we propose the dominant-to-remaining eigenvalue dominance ratio (EIGDR) of unipolar electrograms (u-EGMs) within neighbor electrode cliques as a waveform dispersion measure, hypothesizing that it is correlated with the presence of fibrosis. A simulated 2D tissue with a fibrosis patch was used for validation. We computed EIGDR maps from both original and time-aligned u-EGMs, denoted as R R and RA RA , respectively, also mapping the gain in eigenvalue concentration obtained by the alignment, Δ RA ΔRA . The performance of each map in detecting fibrosis was evaluated in scenarios including noise and variable electrode-tissue distance. Best results were achieved by RA RA , reaching 94% detection accuracy, versus the 86% of b-EGMs voltage maps. The proposed strategy was also tested in real u-EGMs from fibrotic and non-fibrotic areas over 3D electroanatomical maps, supporting the ability of the EIGDRs as fibrosis markers, encouraging further studies to confirm their translation to clinical settings. Graphical Abstract Upper panels: map of RA RA from 3×3 cliques for Ψ= 0 ∘ and bipolar voltage map V b - m , performed assuming a variable electrode-to-tissue distance and noisy u-EGMs (noise level σ v = 46.4 μ V ). Lower panels: detected fibrotic areas (brown), using the thresholds that maximize detection accuracy of each map
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Riccio et al. (2022) studied Atrial fibrosis and atrial fibrillation (n=1). Time-aligned unipolar electrogram eigenvalue dominance ratio (RA) vs. Bipolar electrogram (b-EGM) voltage maps was evaluated on Fibrosis detection accuracy. Time-aligned unipolar electrogram eigenvalue dominance ratio (RA) achieved 94% accuracy in detecting atrial fibrosis compared to 86% for standard bipolar electrogram voltage maps.
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