Abstract
Current biophysical atrial models for investigating atrial fibrillation (AF) mechanisms and treatment approaches use imaging data to define patient-specific anatomy. Electrophysiology of the models can be calibrated using invasive electrical data collected using electroanatomic mapping (EAM) systems. However, these EAM data are typically only available after the catheter ablation procedure has begun, which makes it challenging to use personalised biophysical simulations for informing procedures. In this study, we first aimed to derive a mapping between LGE-MRI intensity and EAM conduction velocity (CV) for calibrating patient-specific left atrial electrophysiology models. Second, we investigated the functional effects of this calibration on simulated arrhythmia properties. To achieve this, we used the Universal Atrial Coordinate (UAC) system to register LGE-MRI and EAM meshes for ten patients. We then post-processed these data to investigate the relationship between LGE-MRI intensities and EAM CV. Mean atrial CV decreased from 0.81 ± 0.31 m/s to 0.58 ± 0.18 m/s as LGE-MRI image intensity ratio (IIR) increased from IIR < 0.9 to 1.6 ≤ IIR. The relationship between IIR and CV was used to calibrate conductivity for a cohort of 50 patient-specific models constructed from LGE-MRI data. This calibration increased the mean number of phase singularities during simulated arrhythmia from 2.67 ± 0.94 to 5.15 ± 2.60.
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Acknowledgement
CR is funded by an MRC Skills Development Fellowship (MR/S015086/1). SN acknowledges support from the EPSRC (EP/M012492/1, NS/A000049/1, and EP/P01268X/1), the British Heart Foundation (PG/15/91/31812, PG/13/37/30280), and Kings Health Partners London National Institute for Health Research (NIHR) Biomedical Research Centre. SW acknowledges a British Heart Foundation Fellowship (FS 20/26/34952). This work was supported by the Wellcome/EPSRC Centre for Medical Engineering (WT 203148/Z/16/Z).
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Beach, M. et al. (2021). Using the Universal Atrial Coordinate System for MRI and Electroanatomic Data Registration in Patient-Specific Left Atrial Model Construction and Simulation. In: Ennis, D.B., Perotti, L.E., Wang, V.Y. (eds) Functional Imaging and Modeling of the Heart. FIMH 2021. Lecture Notes in Computer Science(), vol 12738. Springer, Cham. https://doi.org/10.1007/978-3-030-78710-3_60
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DOI: https://doi.org/10.1007/978-3-030-78710-3_60
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