Left atrial appendage occlusion: On the need of a numerical model to simulate the implant procedure.

Left atrial appendage occlusion (LAAO) is a percutaneous procedure to prevent thromboembolism in patients affected by atrial fibrillation. Despite its demonstrated efficacy, the LAA morphological complexity hinders the procedure, resulting in postprocedural drawbacks (device-related thrombus and peri-device leakage). Local anatomical features may cause difficulties in the device's positioning and affect the effectiveness of the device's implant. The current work proposes a detailed FE model of the LAAO useful to investigate implant scenarios and derive clinical indications. A high-fidelity model of the Watchman FLX device and simplified parametric conduits mimicking the zone of the LAA where the device is deployed were developed. Device-conduit interactions were evaluated by looking at clinical indicators such as device-wall gap, possible cause of leakage, and device protrusion. As expected, the positioning of the crimped device before the deployment was found to significantly affect the implant outcomes: clinician's choices can be improved if FE models are used to optimize the pre-operative planning. Remarkably, also the wall mechanical stiffness plays an important role. However, this parameter value is unknown for a specific LAA, a crucial point that must be correctly defined for developing an accurate FE model. Finally, numerical simulations outlined how the device's configuration on which the clinician relies to assess the implant success (i.e., the deployed configuration with the device still attached to the catheter) may differ from the actual final device's configuration, relevant for achieving a safe intervention.

3D Printed Model-Guided Neonatal Transcatheter Closure of Left Main Coronary Artery-to-Right Ventricle Fistula.

We report on a 2-week-old infant with huge left main coronary artery-to-right ventricular outflow tract fistula causing myocardial ischemia due to global coronary steal who was successfully submitted to percutaneous closure guided by a 3-dimensional-printed model using a duct-occluder vascular plug. (Level of Difficulty: Advanced.).

Uncertainty Quantification in the In Vivo Image-Based Estimation of Local Elastic Properties of Vascular Walls.

INTRODUCTION: Patient-specific computational models are a powerful tool for planning cardiovascular interventions. However, the in vivo patient-specific mechanical properties of vessels represent a major source of uncertainty. In this study, we investigated the effect of uncertainty in the elastic module (E) on a Fluid-Structure Interaction (FSI) model of a patient-specific aorta. METHODS: The image-based χ-method was used to compute the initial E value of the vascular wall. The uncertainty quantification was carried out using the generalized Polynomial Chaos (gPC) expansion technique. The stochastic analysis was based on four deterministic simulations considering four quadrature points. A deviation of about ±20% on the estimation of the E value was assumed. RESULTS: The influence of the uncertain E parameter was evaluated along the cardiac cycle on area and flow variations extracted from five cross-sections of the aortic FSI model. Results of stochastic analysis showed the impact of E in the ascending aorta while an insignificant effect was observed in the descending tract. CONCLUSIONS: This study demonstrated the importance of the image-based methodology for inferring E, highlighting the feasibility of retrieving useful additional data and enhancing the reliability of in silico models in clinical practice.

Effects of Uncertainty of Outlet Boundary Conditions in a Patient-Specific Case of Aortic Coarctation.

Computational Fluid Dynamics (CFD) simulations of blood flow are widely used to compute a variety of hemodynamic indicators such as velocity, time-varying wall shear stress, pressure drop, and energy losses. One of the major advances of this approach is that it is non-invasive. The accuracy of the cardiovascular simulations depends directly on the level of certainty on input parameters due to the modelling assumptions or computational settings. Physiologically suitable boundary conditions at the inlet and outlet of the computational domain are needed to perform a patient-specific CFD analysis. These conditions are often affected by uncertainties, whose impact can be quantified through a stochastic approach. A methodology based on a full propagation of the uncertainty from clinical data to model results is proposed here. It was possible to estimate the confidence associated with model predictions, differently than by deterministic simulations. We evaluated the effect of using three-element Windkessel models as the outflow boundary conditions of a patient-specific aortic coarctation model. A parameter was introduced to calibrate the resistances of the Windkessel model at the outlets. The generalized Polynomial Chaos method was adopted to perform the stochastic analysis, starting from a few deterministic simulations. Our results show that the uncertainty of the input parameter gave a remarkable variability on the volume flow rate waveform at the systolic peak simulating the conditions before the treatment. The same uncertain parameter had a slighter effect on other quantities of interest, such as the pressure gradient. Furthermore, the results highlight that the fine-tuning of Windkessel resistances is not necessary to simulate the post-stenting scenario.

A novel formulation for the study of the ascending aortic fluid dynamics with in vivo data.

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by applying a rigid wall simplification, on the other side the FSI simulation requires a lot of assumptions for the material properties definition and high computational costs. The aim of this study is to investigate the feasibility of a new strategy, based on Radial Basis Functions (RBF) mesh morphing technique and transient simulations, able to introduce the patient-specific changes in aortic geometry during the cardiac cycle. Starting from medical images, aorta models at different phases of cardiac cycle were reconstructed and a transient shape deformation was obtained by proper activating incremental RBF solutions during the simulation process. The results, in terms of main hemodynamic parameters, were compared with two performed CFD simulations for the aortic model at minimum and maximum volume. Our implemented strategy copes the actual arterial variation during cardiac cycle with high accuracy, capturing the impact of geometrical variations on fluid dynamics, overcoming the complexity of a standard FSI approach.

Left atrial appendage occlusion device: Development and validation of a finite element model.

Atrial Fibrillation (AF) is a common disease that significantly increases the risk of strokes. Oral anticoagulants represent the standard preventive treatment, but they involve severe drawbacks, including intracerebral bleedings. Since in patients affected by nonvalvular AF, the Left Atrial Appendage (LAA) is the primary source of thromboembolism, percutaneous closure of the LAA is a viable option for people unsuitable for long-term anticoagulant therapy. However, the complexities related to the implant procedure, occlusion devices and the anatomical variability hinder the pre-operative planning, resulting in unexpected outcomes. In this context, in-silico models may represent a powerful support tool providing clinicians with more detailed information. Nevertheless, few works focusing on numerical modeling of LAA occlusion devices have been presented so far, and a detailed process to assess the model credibility, verifying that different sources of uncertainty did not affect the prediction, is missing. This work aims to illustrate a process that allows to build and validate the numerical model of a commercial occlusion device starting from only one sample available and without data provided by the manufacturer. To better identify potential uncertainties, the validation followed a step-by-step process that led from individual device behavior assessment to interaction with deformable conduit evaluation.