TY - JOUR

T1 - Validation of a computational model aiming to optimize preprocedural planning in percutaneous left atrial appendage closure

AU - Bavo, Alessandra M.

AU - Wilkins, Benjamin T.

AU - Garot, Philippe

AU - De Bock, Sander

AU - Saw, Jacqueline

AU - Søndergaard, Lars

AU - De Backer, Ole

AU - Iannaccone, Francesco

PY - 2020

Y1 - 2020

N2 - 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 (R2) 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.

AB - 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 (R2) 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.

KW - Atrial fibrillation

KW - CCT-based computational model

KW - Patient-specific anatomy

KW - Percutaneous left atrial appendage closure

KW - Pre-operative planning

U2 - 10.1016/j.jcct.2019.08.010

DO - 10.1016/j.jcct.2019.08.010

M3 - Journal article

C2 - 31445885

AN - SCOPUS:85070911139

VL - 14

SP - 149

EP - 154

JO - Journal of Cardiovascular Computed Tomography

JF - Journal of Cardiovascular Computed Tomography

SN - 1934-5925

IS - 2

ER -