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Publication Detail
Computational Fluid Dynamic Analysis of the Left Atrial Appendage to Predict Thrombosis Risk.
  • Publication Type:
    Conference presentation
  • Publication Sub Type:
    Presentation
  • Authors:
    Bosi G, Cook A, Rai R, Menezes L, Schievano S, Torii R, Burriesci G
  • Date:
    08/09/2017
  • Name of Conference:
    7th International Conference on Computational Bioengineering
  • Conference place:
    Compiègne, France
  • Conference start date:
    06/09/2017
  • Conference finish date:
    08/09/2017
Abstract
Thromboembolic events, mainly caused by atrial fibrillation (AF), affect 1-2% of the population. More than 90% of the left atrial thrombi responsible for these originate in the left atrial appendage (LAA), a trabeculated finger-like projection about 2-4 cm long departing from the main body of the left atrium (LA). Current treatment to prevent thromboembolic event is oral anticoagulation, surgical LAA exclusion or percutaneous LAA occlusion. However, the role played by the appendage morphology in the clotting mechanism is still poorly understood. This sac can vary substantially from patient to patient, in terms of structure and number of lobes, and is typically classified into four groups, characterised based on their shape: “chicken wing”, “cactus”, “windsock” and “cauliflower”. The aim of this work is to analyse the hemodynamic behaviour in all four LAA morphologies, to identify potential relationships between the different shapes and the risk of thrombotic events. Computerized tomography (CT) images from four healthy subjects were acquired at University College London Hospital (London, UK) and segmented to derive the 3D anatomical shape of LAA and LA. The 3D structures were meshed in Ansys-ICEM (ANSYS, Inc.), with 10 prism layers in proximity of the walls and tetra elements elsewhere (average size ~ 0.3 mm). Computational Fluid Dynamic (CFD) analyses based on patient-specific anatomies were implemented in Ansys CFX (ANSYS, Inc.) for all four cases. An opening boundary condition was set at the mitral valve outlet, where a velocity profile derived from the flow measured by Rabbah et al. was imposed. Transient simulations were carried out to perform four cardiac cycles, to allow the flow to fully develop. The time step was set to 5×10-4. A turbulence model was used and blood was considered as non-Newtonian, using a Casson model. Residence time in the different LAA regions was estimated introducing a virtual contrast agent in the computational models; the remaining contrast agent normalised volume in the LAA at the end of every cardiac cycle was monitored throughout the simulation. CFD results indicate that both velocity and shear strain rate decrease along the LAA, from the orifice to the extremities, at each instant in the cardiac cycle, thus making the LAA edge regions more prone to fluid stagnation, and therefore to thrombosis formation. Moreover, CFD analyses allowed to identify the different flow dynamics produced by the four LAA shapes. The largest normalised volume of contrast agent (Fig. 1) was obtained for the cauliflower shape (4.7%), and the smallest for the chicken wing LAA (2.1%). This suggests that the latter is expected to be associated with a lower risk of thrombosis, confirming the reports in the literature. These computational models could be translated into clinical practice to support clinicians in the stratification of patients under high risk of thrombus formation, towards personalised patient care.
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