Left atrial appendage occlusion devices (LAAO) are a feasible alternative for non-valvular atrial fibrillation (AF) patients at high risk of thromboembolic stroke and contraindication to antithrombotic therapies. However, optimal LAAO device configurations (i.e., size, type, location) remain unstandardized due to the large anatomical variability of the left atrial appendage (LAA) morphology, leading to a 4-6% incidence of device-related thrombus (DRT). In-silico simulations have the potential to assess DRT risk and identify the key factors, such as suboptimal device positioning. This work presents fluid simulation results computed on 20 patient-specific left atrial geometries, analysing different commercially available LAAO occluders, including plug-type and pacifier-type devices. In addition, we explored two distinct device positions: 1) the real post-LAAO intervention configuration derived from follow-up imaging; and 2) one covering the pulmonary ridge if it was not achieved during the implantation (13 out of 20). In total, 33 different configurations were analysed. In-silico indices indicating high risk of DRT (e.g., low blood flow velocities and flow complexity around the device) were combined with particle deposition analysis based on a discrete phase model. The obtained results revealed that covering the pulmonary ridge with the LAAO device may be one of the key factors to prevent DRT, resulting in higher velocities and reduced flow recirculations (e.g., mean velocities of 0.183 ± 0.12 m/s and 0.236 ± 0.16 m/s for uncovered versus covered positions in DRT patients). Moreover, disk-based devices exhibited enhanced adaptability to various LAA morphologies and, generally, demonstrated a lower risk of abnormal events after LAAO implantation.

MOTIVATION: Biological mechanisms contributing to atherogenesis are multiple and complex. The early stage of atherosclerosis (AS) is characterized by the accumulation of low-density lipoprotein (LDL) droplets, leading to the creation of foam cells (FC). To address the difficulty to explore the dynamics of interactions that controls this process, this study aimed to develop a model of agents and infer on the most influential cell- and molecule-related parameters. RESULTS: FC started to accumulate after six to eight months of simulated hypercholesterolemia. A sensitivity analysis revealed the strong influence of LDL oxidation rate on the risk of FC creation, which was exploited to model the antioxidant effect of statins. Combined with an empirical simulation of the drug ability to decrease the level of LDL, the virtual statins treatment led to reductions of oxidized LDL levels similar to reductions measured in vivo. AVAILABILITY AND IMPLEMENTATION: An Open source software was used to develop the agent-based model of early AS. Two different concentrations of LDL agents were imposed in the intima layer to simulate healthy and hypercholesterolemia groups of 'virtual patients'. The interactions programmed between molecules and cells were based on experiments and models reported in the literature. A factorial sensitivity analysis explored the respective effects of the less documented model parameters as (i) agent migration speed, (ii) LDL oxidation rate and (iii) concentration of autoantibody agents. Finally, the response of the model to known perturbations was assessed by introducing statins agents, able to reduce the oxidation rate of LDL agents and the LDL boundary concentrations. CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.