Abstract:
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[EN] Objective: Atrial dominant frequency (DF) maps undergoing atrial fibrillation (AF) presented good
spatial correlation with those obtained with the non-invasive body surface potential mapping
(BSPM). In this study, a ...[+]
[EN] Objective: Atrial dominant frequency (DF) maps undergoing atrial fibrillation (AF) presented good
spatial correlation with those obtained with the non-invasive body surface potential mapping
(BSPM). In this study, a robust BSPM-DF calculation method based on wavelet analysis is
proposed. Approach: Continuous wavelet transform along 40 scales in the pseudo-frequency range
of 3¿30 Hz is performed in each BSPM signal using a Gaussian mother wavelet. DFs are estimated
from the intervals between the peaks, representing the activation times, in the maximum energy
scale. The results are compared with the traditionally widely applied Welch periodogram and the
robustness was tested on different protocols: increasing levels of white Gaussian noise, artificial DF
harmonics presence and reduction in the number of leads. A total of 11 AF simulations and 12 AF
patients are considered in the analysis. For each patient, intracardiac electrograms were acquired in
15 locations from both atria. The accuracy of both methods was assessed by calculating the
absolute errors of the highest DFBSPM (HDFBSPM) with respect to the atrial HDF, either simulated
or intracardially measured, and assumed correct if ¿1 Hz. The spatial distribution of the errors
between torso DFs and atrial HDFs were compared with atria driving mechanism locations. Torso
HDF regions, defined as portions of the maps with |DF ¿ HDFBSPM| ¿ 0.5 Hz were identified and
the percentage of the torso occuping these regions was compared between methods. The robustness
of both methods to white Gaussian noise, ventricular influence and harmonics, and to lower spatial
resolution BSPM lead layouts was analyzed: computer AF models (567 leads vs 256 leads down to
16 leads) and patient data (67 leads vs 32 and 16 leads). Main results: The proposed method
allowed an improvement in non-invasive estimation of the atria HDF. For the models the median
relative errors were 7.14% for the wavelet-based algorithm vs 60.00% for the Welch method; in
patients, the errors were 10.03% vs 12.66%, respectively. The wavelet method outperformed the
Welch approach in correct estimations of atrial HDFs in models (81.82% vs 45.45%, respectively)
and patients (66.67% vs 41.67%). A low positive BSPM-DF map correlation was seen between the
techniques (0.47 for models and 0.63 for patients), highlighting the overall differences in DF
distributions. The wavelet-based algorithm was more robust to white Gaussian noise, residual
ventricular activity and harmonics, and presented more consistent results in lead layouts with low
spatial resolution. Significance: Estimation of atrial HDFs using BSPM is improved by the proposed
wavelet-based algorithm, helping to increase the non-invasive diagnostic ability in AF.
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Thanks:
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This study was supported in part by grants from Sao Paulo Research Foundation (2017/19775-3), Instituto de Salud Carlos III FEDER (Fondo Europeo de Desarrollo Regional PI17/01106) and Generalitat Valenciana Grants (AICO/2018/267).[+]
This study was supported in part by grants from Sao Paulo Research Foundation (2017/19775-3), Instituto de Salud Carlos III FEDER (Fondo Europeo de Desarrollo Regional PI17/01106) and Generalitat Valenciana Grants (AICO/2018/267).
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