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Role of atrial wall thickness in wave-dynamics of atrial fibrillation.

ABSTRACT: Atrial anatomy and thickness may affect the electrical wave-dynamics of atrial fibrillation (AF). We explored the relationship between left atrial (LA) wall thickness (LAWT) or LA geometry and AF wave-dynamics.We included 15 patients with persistent AF (age, 62.3 ± 11.9 years) who underwent AF catheter ablation. We measured the LAWT, LA endocardial curvature, and SD-curvature (surface bumpiness) from preprocedural computed tomography images. We compared those anatomical characteristics with electrophysiologic parameters such as dominant frequency (DF), Shannon entropy (ShEn), or complex fractionated atrial electrogram (CFAE)-cycle length (CL), calculated from intracardiac bipolar electrograms (300-500 points, 5 s), acquired during ablation procedures.1. LAWT (excluding fat) varied widely among patients, locations, and types of AF. LAWT was inversely correlated with LA volume (r = -0.565, p = 0.028) and positively correlated with SD-curvature (r = 0.272, p < 0.001). 2. LAWT was positively correlated with ShEn (r = 0.233, p < 0.001) and negatively correlated with CFAE-CL (r = -0.107, p = 0.038). 3. In the multivariate linear regression analyses for AF wave-dynamics parameters, DF (β = -0.29 [95% CI -0.44--0.14], p < 0.001), ShEn (β = 0.19 [95% CI 0.12-0.25], p < 0.001), and CFAE-CL (β = 7.49 [95% CI 0.65-14.34], p = 0.032) were independently associated with LAWT.Regional LAWT is associated with LA structural features, and has significant correlations with the wave-dynamics parameters associated with electrical wavebreaks or rotors in patients with persistent AF.

SUBMITTER: Song JS

PROVIDER: S-EPMC5565105 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Project description:Introduction: Catheter ablation (CA) is a common treatment for atrial fibrillation (AF), but the knowledge of optimal ablation sites, and hence clinical outcomes, are suboptimal. Increasing evidence suggest that ablation strategies based on patient-specific substrates information, such as distributions of fibrosis and atrial wall thickness (AWT), may be used to improve therapy. We hypothesized that competing influences of large AWT gradients and fibrotic patches on conductive properties of atrial tissue can determine locations of re-entrant drivers (RDs) sustaining AF. Methods: Two sets of models were used: (1) a simple model of 3D atrial tissue slab with a step change in AWT and a synthetic fibrosis patch, and (2) 3D models based on patient-specific right atrial (RA) and left atrial (LA) geometries. The latter were obtained from four healthy volunteers and two AF patients, respectively, using magnetic resonance imaging (MRI). A synthetic fibrotic patch was added in the RA and fibrosis distributions in the LA were obtained from gadolinium-enhanced MRI of the same patients. In all models, 3D geometry was combined with the Fenton-Karma atrial cell model to simulate RDs. Results: In the slab, RDs drifted toward, and then along the AWT step. However, with additional fibrosis, the RDs were localized in regions between the step and fibrosis. In the RA, RDs drifted toward and anchored to a large AWT gradient between the crista terminalis (CT) region and the surrounding atrial wall. Without such a gradient, RDs drifted toward the superior vena cava (SVC) or the tricuspid valve (TSV). With additional fibrosis, RDs initiated away from the CT anchored to the fibrotic patch, whereas RDs initiated close to the CT region remained localized between the two structures. In the LA, AWT was more uniform and RDs drifted toward the pulmonary veins (PVs). However, with additional fibrotic patches, RDs either anchored to them or multiplied. Conclusion: In the RA, RD locations are determined by both fibrosis and AWT gradients at the CT region. In the LA, they are determined by fibrosis due to the absence of large AWT gradients. These results elucidate mechanisms behind the stabilization of RDs sustaining AF and can help guide ablation therapy.

Project description:The autonomic nervous system (ANS) is an important factor in cardiac arrhythmia, and information about ANS activity during atrial fibrillation (AF) may contribute to personalized treatment. In this study we aim to quantify respiratory modulation in the f-wave frequency trend from resting ECG. First, an f-wave signal is extracted from the ECG by QRST cancelation. Second, an f-wave model is fitted to the f-wave signal to obtain a high resolution f-wave frequency trend and an index for signal quality control ( S ). Third, respiratory modulation in the f-wave frequency trend is extracted by applying a narrow band-pass filter. The center frequency of the band-pass filter is determined by the respiration rate. Respiration rate is estimated from a surrogate respiration signal, obtained from the ECG using homomorphic filtering. Peak conditioned spectral averaging, where spectra of sufficient quality from different leads are averaged, is employed to obtain a robust estimate of the respiration rate. The envelope of the filtered f-wave frequency trend is used to quantify the magnitude of respiratory induced f-wave frequency modulation. The proposed methodology is evaluated using simulated f-wave signals obtained using a sinusoidal harmonic model. Results from simulated signals show that the magnitude of the respiratory modulation is accurately estimated, quantified by an error below 0.01 Hz, if the signal quality is sufficient ( S>0.5 ). The proposed method was applied to analyze ECG data from eight pacemaker patients with permanent AF recorded at baseline, during controlled respiration, and during controlled respiration after injection of atropine, respectively. The magnitude of the respiratory induce f-wave frequency modulation was 0.15 ± 0.01, 0.18 ± 0.02, and 0.17 ± 0.03 Hz during baseline, controlled respiration, and post-atropine, respectively. Our results suggest that parasympathetic regulation affects the magnitude of respiratory induced f-wave frequency modulation.

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Role of atrial wall thickness in wave-dynamics of atrial fibrillation.

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