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

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.

Patient-Specific Computer Simulation of Transcatheter Aortic Valve Replacement in Bicuspid Aortic Valve Morphology.

BACKGROUND: A patient-specific computer simulation of transcatheter aortic valve replacement (TAVR) in tricuspid aortic valve has been developed, which can predict paravalvular regurgitation and conduction disturbance. We wished to validate a patient-specific computer simulation of TAVR in bicuspid aortic valve and to determine whether patient-specific transcatheter heart valve (THV) sizing and positioning might improve clinical outcomes. METHODS: A retrospective study was performed on TAVR in bicuspid aortic valve patients that had both pre- and postprocedural computed tomography imaging. Preprocedural computed tomography imaging was used to create finite element models of the aortic root. Finite element analysis and computational fluid dynamics was performed. The simulation output was compared with postprocedural computed tomography imaging, cineangiography, echocardiography, and electrocardiograms. For each patient, multiple simulations were performed, to identify an optimal THV size and position for the patient's specific anatomic characteristics. RESULTS: A total of 37 patients were included in the study. The simulations accurately predicted the THV frame deformation (minimum-diameter intraclass correlation coefficient, 0.84; maximum-diameter intraclass correlation coefficient, 0.88; perimeter intraclass correlation coefficient, 0.91; area intraclass correlation coefficient, 0.91), more than mild paravalvular regurgitation (area under the receiver operating characteristic curve, 0.86) and major conduction abnormalities (new left bundle branch block or high-degree atrioventricular block; area under the receiver operating characteristic curve, 0.88). When compared with the implanted THV size and implant depth, optimal patient-specific THV sizing and positioning reduced simulation-predicted paravalvular regurgitation and markers of conduction disturbance. CONCLUSIONS: Patient-specific computer simulation of TAVR in bicuspid aortic valve may predict the development of important clinical outcomes, such as paravalvular regurgitation and conduction abnormalities. Patient-specific THV sizing and positioning may improve clinical outcomes of TAVR in bicuspid aortic valve.

Fluid-Structure Interaction Simulation of Prosthetic Aortic Valves: Comparison between Immersed Boundary and Arbitrary Lagrangian-Eulerian Techniques for the Mesh Representation.

In recent years the role of FSI (fluid-structure interaction) simulations in the analysis of the fluid-mechanics of heart valves is becoming more and more important, being able to capture the interaction between the blood and both the surrounding biological tissues and the valve itself. When setting up an FSI simulation, several choices have to be made to select the most suitable approach for the case of interest: in particular, to simulate flexible leaflet cardiac valves, the type of discretization of the fluid domain is crucial, which can be described with an ALE (Arbitrary Lagrangian-Eulerian) or an Eulerian formulation. The majority of the reported 3D heart valve FSI simulations are performed with the Eulerian formulation, allowing for large deformations of the domains without compromising the quality of the fluid grid. Nevertheless, it is known that the ALE-FSI approach guarantees more accurate results at the interface between the solid and the fluid. The goal of this paper is to describe the same aortic valve model in the two cases, comparing the performances of an ALE-based FSI solution and an Eulerian-based FSI approach. After a first simplified 2D case, the aortic geometry was considered in a full 3D set-up. The model was kept as similar as possible in the two settings, to better compare the simulations' outcomes. Although for the 2D case the differences were unsubstantial, in our experience the performance of a full 3D ALE-FSI simulation was significantly limited by the technical problems and requirements inherent to the ALE formulation, mainly related to the mesh motion and deformation of the fluid domain. As a secondary outcome of this work, it is important to point out that the choice of the solver also influenced the reliability of the final results.