论文和技术资料

In this paper, we present a comprehensive study on the influence of anatomical shapes on the speed of blood flow in the left atrial appendage (LAA) using Computational Fluid Dynamics (CFD) Module in COMSOL Multiphysics®. The LAA itself can serve as a potential origin of blood clots, particularly during arrhythmias, ultimately leading to the risk of brain stroke. Understanding the factors that affect blood flow in the LAA is essential for developing new effective treatment strategies. To conduct the simulations, we employed a multi-step approach. Firstly, we utilized the Mimics and 3-matic software (Materialise, Belgium) to perform left heart segmentation from anonymized computed tomography (CT) images, enabling the extraction of accurate anatomical models. These models were then prepared for numerical simulations by creating a high-quality surface mesh, which was subsequently imported into the COMSOL Multiphysics® software. In COMSOL Multiphysics®, the mesh was carefully edited to ensure its integrity and eliminate any potential errors. By incorporating turbulent flow physics, specifically the Reynolds-Averaged Navier-Stokes (RANS) equations and the Shear Stress Transport (SST) turbulence model, along with transition modeling, we aim to enhance the accuracy and realism of our simulations. We defined the inlets as the four pulmonary veins, which are crucial for blood supply to the LAA. The inlets were configured with time-dependent pressure conditions, while the outlet was set to a time-dependent velocity condition, in order to accurately simulate the physiological behavior of blood flow throughout one cycle lasting 0.8 seconds. To evaluate the results of the simulations, we utilized LiveLink™ for MATLAB®, enabling data analysis and visualization. We performed in-depth analysis of the blood flow characteristics, including velocity profiles, pressure distributions, and turbulence patterns within the LAA as presented in Figure 1. Through our numerical simulations, we aimed to gain insights into the relationship between anatomical shapes and blood flow speed in the LAA. By the geometrical parameters variation of each patient LAA models, we were able to assess the impact of these factors on the flow dynamics. The findings from our study contribute to a deeper understanding of the complex hemodynamics within the LAA. Moreover, they provide valuable insights to identify potential risk factors associated with low blood flow and develop targeted interventions to mitigate the occurrence of blood strokes. In conclusion, this paper presents a comprehensive methodology for conducting blood flow numerical simulations in the LAA using CFD techniques (turbulent flow physics). By using the Mimics® and 3-matic® software for segmentation and mesh preparation, along with COMSOL Multiphysics®, and leveraging LiveLink™ for MATLAB® for result analysis, we successfully investigated the influence of anatomical shapes on blood flow speed. These findings advance knowledge of LAA hemodynamics and have potential implications for clinical practice and future research.