Constructing bilayer and volumetric atrial models at scale.

To enable large in silico trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling in silico clinical trials at scale (https://github.com/pcmlab/atrialmtk)

P439Could regional electrogram desynchronization identified using mean phase coherence be potential ablation targets in persistent atrial fibrillation?

Background It remains controversial as to whether rotors detected using phase mapping during persistent atrial fibrillation (persAF) represent main drivers of the underlying mechanism as others found rotors to be located near line of conduction block. Regional electrogram desynchronization (RED) has been suggested as successful targets for persAF ablation, but automatic tools and quantitative measures are lacking. Purpose We aim to use mean phase coherence (MPC) to automatically identify RED regions during persAF. This method was compared with phase singularity density (PSD) maps. Methods Patients undergoing left atrial (LA) persAF ablation were enrolled (n = 10). 2048-channel virtual electrograms (VEGMs) were collected from each patient using non-contact mapping (St Jude Velocity System, Ensite Array) for 10 seconds. To remove far field ventricular activities, QRS onset and T wave end locations were detected from ECG lead I (Figure 1A) and only the VEGM segments from T end to QRS onset were included in the analysis. VEGMs were reconstructed using sinusoidal wavelets fitting and the phase of VEGMs determined using Hilbert transform. Phase singularities (PS) were detected using the topological charge method and repetitive PSD maps were generated. RED was defined as the average of MPC of each node against direct neighbouring nodes on the 3D mesh (Figure 1A-B). Linear regression analysis was used to compare the average MPC vs. PSD and vs. the standard deviation of MPC (MPC_SD). ResultsA total of 221,184 VEGM segments were analysed with mean duration of 364.2 milliseconds. MPC has shown the ability to quantify the level of synchronisation between VEGMs (Figure 1B). Inverse correlation was found between PSD and average MPC values for all 10 patients (p Conclusion We have proposed a method to quantify the level of synchronisation between VEGMs. Phase density mapping showed a considerable agreement with RED regions reflecting regional conducting delays, which supports the previous finding where rotors found at conduction block. Inverse correlation between local average MPC and MPC_SD suggests that conduction delays of the identified regions are not heterogenous, posing directional preferences. Rather than solely looking for rotational activities, this method could identify comprehensive RED regions, which may also explain the conflicting results from different studies targeting rotational activities, where incomplete subsets of RED regions could have been targeted. Atrial RED regions can easily be identified with simultaneously collected electrograms from multi-polar catheters and should be targeted in future persAF studies. </div