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. 2012 Sep 15;590(18):4515-35.
doi: 10.1113/jphysiol.2012.229062. Epub 2012 Jul 2.

The role of fine-scale anatomical structure in the dynamics of reentry in computational models of the rabbit ventricles

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The role of fine-scale anatomical structure in the dynamics of reentry in computational models of the rabbit ventricles

Martin J Bishop et al. J Physiol. .

Abstract

Fine-scale anatomical structures in the heart may play an important role in sustaining cardiac arrhythmias. However, the extent of this role and how it may differ between species are not fully understood. In this study we used computational modelling to assess the impact of anatomy upon arrhythmia maintenance in the rabbit ventricles. Specifically, we quantified the dynamics of excitation wavefronts during episodes of simulated tachyarrhythmias and fibrillatory arrhythmias, defined as being respectively characterised by relatively low and high spatio-temporal disorganisation.Two computational models were used: a highly anatomically detailed MR-derived rabbit ventricular model (representing vasculature, endocardial structures) and a simplified equivalent model, constructed from the same MR-data but lacking such fine-scale anatomical features. During tachyarrhythmias, anatomically complex and simplified models showed very similar dynamics; however, during fibrillatory arrhythmias, as activation wavelength decreased, the presence of fine-scale anatomical details appeared to marginally increase disorganisation of wavefronts during arrhythmias in the complex model. Although a small amount of clustering of reentrant rotor centres (filaments) around endocardial structures was witnessed in follow-up analysis (which slightly increased during fibrillation as rotor size decreased), this was significantly less than previously reported in large animals. Importantly, no anchoring of reentrant rotors was visibly identifiable in arrhythmia movies. These differences between tachy- and fibrillatory arrhythmias suggest that the relative size of reentrant rotors with respect to anatomical obstacles governs the influence of fine-scale anatomy in the maintenance of ventricular arrhythmias in the rabbit. In conclusion, our simulations suggest that fine-scale anatomical features play little apparent role in the maintenance of tachyarrhythmias in the rabbit ventricles and, contrary to experimental reports in larger animals, appear to play only a minor role in the maintenance of fibrillatory arrhythmias. These findings also have important implications in optimising the level of detail required in anatomical computational meshes frequently used in arrhythmia investigations.

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Figures

Figure 1
Figure 1. MR-derived rabbit ventricular models used
Complex model (left) containing fine-scale anatomical features such as blood vessels, papillary muscles and trabeculations, and simple model (right) with such fine-scale features removed. Also shown in simplified model is the square epicardial field-of-view (FOV) used to count wavefront numbers.
Figure 2
Figure 2. Wavefront dynamics during an arrhythmia episode (CI = 210 ms) in the anatomically complex (top) and simplified (bottom) models
Posterior (upper) and anterior (lower) epicardial views are shown, with clipping planes exposing intramural and endocardial activation in an inclined posterior view (centre).
Figure 3
Figure 3
Bipolar pseudo-ECG recordings from lead I during arrhythmia episode with CI = 185 ms for complex (red) and simple (blue) models.
Figure 4
Figure 4. Quantitative analysis of 3D complexity metrics
Top panels, total number of filaments for episode CI = 185 ms (A), epicardial surface phase singularities for episode CI = 185 ms (B), and surface wavefronts within selected FOV (shown in Fig. 1) for episode CI = 195 ms (C), plotted over entire arrhythmia duration for complex (red) and simple (blue) models. Bottom panels, mean (left) and max (right) numbers of above plotted quantities averaged over all 13 arrhythmia episodes.
Figure 5
Figure 5. Spatial distribution of mean nodal activation rate (activations s−1), averaged over all 13 arrhythmia episodes, within the entire volume of the ventricles
Plots are shown on anterior/posterior epicardial surfaces and posterior views where longitudinal/transverse clipping planes have been used to allow endocardial surfaces to be viewed.
Figure 6
Figure 6. Spatial distribution of the cumulative temporal filament count, within the entire volume of the ventricles, accumulated over all 13 arrhythmia episodes for complex (top) and simple (bottom) models
Plots are shown on anterior/posterior epicardial surfaces (right panel) and posterior views where longitudinal (top panel) and short-axis (bottom panel) clipping planes have been used to allow endocardial surfaces and intramural distributions to be viewed at different clipping locations through the ventricles.
Figure 7
Figure 7. Wavefront dynamics in the complex (top) and simplified (bottom) models during an arrhythmia episode (CI = 225 ms) with fibrillatory dynamics
Posterior (upper) and anterior (lower) epicardial views, with intramural and endocardial activation exposed in an inclined posterior view (centre).
Figure 8
Figure 8
Bipolar pseudo-ECG recordings from lead II during arrhythmia episode with CI = 200 ms for complex (red) and simple (blue) models.
Figure 9
Figure 9. Quantitative analysis of 3D complexity metrics during fibrillatory activity
Top panels, total number of filaments for episode CI = 225 ms (A), epicardial surface phase singularities for episode CI = 220 ms (B), and surface wavefronts within selected FOV (shown in Fig. 1) for episode CI = 225 ms (C) plotted over entire arrhythmia duration for complex (red) and simple (blue) models. Bottom panels, mean (left) and max (right) numbers of above plotted quantities averaged over all 13 arrhythmia episodes.
Figure 10
Figure 10
Spatial distribution of mean nodal activation rate (activations s−1), averaged over all 13 arrhythmia episodes, within the entire volume of the ventricles for fibrillatory activity with similar viewing angles to Fig. 5.
Figure 11
Figure 11
Spatial distribution of the cumulative temporal filament count, within the entire volume of the ventricles, accumulated over all 13 arrhythmia episodes for complex (top) and simple (bottom) models during fibrillatory activity with similar viewing angles as used in Fig. 6.

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