Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps with Manifold Harmonics

[EN] Introduction: Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysio-logical studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. Objective: We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR). Methods: Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units. Results: With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the "early-meets-late" in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm. Conclusion: The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.This work was partly supported by Spanish Research Projects TEC2013-48439-C4-1-R, TEC2016-75361-R, and TEC2016-75161-C2-1-4.Sanroman-Junquera, M.; Mora-Jimenez, I.; Garcia-Alberola, A.; Caamano, AJ.; Trénor Gomis, BA.; Rojo-Alvarez, JL. (2018). Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps with Manifold Harmonics. IEEE Transactions on Biomedical Engineering (Online). 65(4):723-732. https://doi.org/10.1109/TBME.2017.2716189S72373265

Long-term characterization of persistent atrial fibrillation: wave morphology, frequency, and irregularity analysis

Short-term properties of atrial fibrillation (AF) frequency, f-wave morphology, and irregularity parameters have been thoroughly studied, but not long-term properties. In the present work, f-wave morphology is characterized by principal component analysis, introducing a novel temporal parameter defined by the cumulative normalized variance of the three largest principal components . Based on 7-day recordings from nine patients with stable chronic heart failure and persistent AF, long-term properties were studied in terms of , AF frequency, and sample entropy . The main result of the present study is that detection of circadian rhythms depends on the parameter considered: rhythms were found in six and five (AF frequency) patients, but not always in the same patient. Another important result is that circadian rhythms detected in 7-day recordings could not always be detected in 24-h periods, thus shedding new light on the results in previous studies which all were based on 24-h recordings. Infradian rhythms were found in four and one (AF frequency) patients