Abstract
Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by uncoordinated atrial activation with consequent deterioration of mechanical function. Personalized computational modeling provides a novel framework for integrating and interpreting the combined role of atrial electrophysiology and mechanics in AF development and sustenance. Coronary computed tomography angiography data were segmented using a threshold-based approach and the smoothed voxel representation was dis-cretized into a high-resolution tetrahedral finite element (FE) mesh. To estimate the complex left atrial fiber architecture, individual fiber fields were generated according to morphological data on the endo- and epicardial surfaces based on local solutions of Laplace's equation and trans-murally interpolated to all tetrahedral elements. Personalized geometrical models included the heterogeneous thickness distribution of the left atrial myocardium and subsequent discretization led to high-fidelity tetrahedral FE meshes. The novel algorithm for (automated) incorporation of the left atrial fiber architecture provided a realistic estimate of the atrial microstructure and was able to qualitatively capture all important fiber bundles. The established modeling pipeline provides a robust framework for the rapid development of personalized model cohorts and facilitates simulations of atrial electromechanics.
Original language | English |
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Title of host publication | Computing in Cardiology Conference, CinC 2016 |
Publisher | IEEE Computer Society |
Pages | 225-228 |
Number of pages | 4 |
Volume | 43 |
ISBN (Electronic) | 9781509008964 |
Publication status | Published - 1 Mar 2017 |
Event | 43rd Computing in Cardiology Conference, CinC 2016 - Vancouver, Canada Duration: 11 Sept 2016 → 14 Sept 2016 |
Conference
Conference | 43rd Computing in Cardiology Conference, CinC 2016 |
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Country/Territory | Canada |
City | Vancouver |
Period | 11/09/2016 → 14/09/2016 |