1. Validation of a computational model aiming to optimize preprocedural planning in percutaneous left atrial appendage closure.
- Author
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Bavo AM, Wilkins BT, Garot P, De Bock S, Saw J, Søndergaard L, De Backer O, and Iannaccone F
- Subjects
- Aged, Aged, 80 and over, Atrial Appendage physiopathology, Atrial Fibrillation diagnostic imaging, Atrial Fibrillation physiopathology, British Columbia, Denmark, Equipment Design, Female, Humans, Male, Middle Aged, Models, Cardiovascular, Paris, Predictive Value of Tests, Reproducibility of Results, Retrospective Studies, Treatment Outcome, Atrial Appendage diagnostic imaging, Atrial Fibrillation therapy, Cardiac Catheterization adverse effects, Cardiac Catheterization instrumentation, Patient-Specific Modeling, Therapy, Computer-Assisted instrumentation, Tomography, X-Ray Computed
- Abstract
Background: Percutaneous left atrial appendage (LAA) closure can be optimised through diligent preprocedural planning. Cardiac computational tomography (CCT) is increasingly recognised as a valuable tool in this process. A CCT-based computational model (FEops HEARTguide™, Belgium) has been developed to simulate the deployment of the two most commonly used LAA closure devices into patient-specific LAA anatomies., Objective: The aim of this study was to validate this computational model based on real-life percutaneous LAA closure procedures and post-procedural CCT imaging., Methods: Thirty patients having undergone LAA closure (Amulet™ n = 15, Watchman™ n = 15) and having a pre- and post-procedural CCT-scan were selected for this validation study. Virtually implanted devices were directly compared to actual implants for device frame deformation and LAA wall apposition., Results: The coefficient of determination (R
2 ) and the difference in measurements between model and actual device (area, perimeter, minimum diameter, maximum diameter) were ≥0.91 and ≤ 5%, respectively. For both device types, the correlation coefficient between predicted and observed measurements was higher than 0.90. Furthermore, predicted device apposition correlated well with observed leaks based on post-procedural CCT., Conclusion: Computational modelling accurately predicts LAA closure device deformation and apposition and may therefore potentiate more accurate LAA closure device sizing and better preprocedural planning., (Copyright © 2020 Society of Cardiovascular Computed Tomography. All rights reserved.)- Published
- 2020
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