In silico Optimization of Left Atrial Appendage Occluder Implantation Using Interactive and Modeling Tools - Aguado, Ainhoa M.; Olivares, Andy L.; Yagüe, Carlos; Silva, Etelvino; Nuñez-García, Marta; Fernandez-Quilez, Álvaro; Mill, Jordi; Genua, Ibai; Arzamendi, Dabit; De Potter, Tom; Freixa, Xavier; Camara, Oscar (Frontiers in Physiology, 2019)
According to clinical studies, around one-third of patients with atrial fibrillation (AF) will suffer a stroke during their lifetime. Between 70% and 90% of these strokes are caused by thrombus formed in the left atrial appendage. In patients with contraindications to oral anticoagulants, a left atrial appendage occluder (LAAO) is implanted to prevent blood flow entering in the LAA. A limited range of LAAO devices is available, with different designs and sizes. Together with the heterogeneity of LAA morphology, these factors make LAAO-based therapy success strongly dependent on the clinician’s experience. A sub-optimal LAAO implantation can generate thrombi outside the LAA, eventually leading to stroke if not treated. The aim of this study was to develop clinician-friendly tools based on biophysical models to optimize LAAO device therapies. A web-based 3D interactive virtual implantation platform, so-called VIDAA, was created to allow clinicians to select the most appropriate LAAO configurations (the type of device, size, landing zone) for a patient-specific LAA morphology. A default LAAO configuration is initially displayed in VIDAA, which is based on automatically computed LAA shape features (centreline, diameters). Computational Fluid Dynamics (CFD) simulations were then run for different LAAO settings from VIDAA to assess the corresponding blood flow patterns after implantation and estimate their risk of thrombus formation. The initial LAAO configuration proposed in VIDAA was the one associated with a lower risk of thrombus formation, according to the estimated in silico parameters from CFD simulations. Our results demonstrate that the optimization of LAAO therapy settings during pre-implant planning based on modelling tools can contribute to reduce the risk of thrombus formation after treatment.