Atrial Fibrillation Goes Beyond Arrhythmias: You Will Have Stroke If You Do Not Treat It. Let's Model It!

Oscar Camara
Universitat Pompeu Fabra


Abstract

Atrial fibrillation (AF) is catalogued as the most prevalent type of arrhythmia, its incidence and prevalence rates steadily rising globally. Among the several associated pathophysiological consequences in AF patients, stroke prevention is a cornerstone of the clinical management of atrial fibrillation. Structural and functional remodelling produce alterations in blood flow haemodynamics promoting blood stasis and then, stroke risk. The left atrial appendage (LAA) is the predominant site of thrombosis in AF patients. Oral anticoagulants (OACs) are the first-line treatment to reduce and prevent stroke risk. However, an increasing number of non-valvular AF patients have clinical contraindications OACs. Over the past decade, left atrial appendage closure using occluder devices (LAAO) has emanated as alternative to prevent and revert the thrombosis process. However, successful implantation of a LAAO device remains a challenging endeavour. Among the variability in LAA morphologies and the wide range of device settings to personalize (e.g., design, size, position), the learning curve to acquire excellence in LAAO device implantation becomes extensive, with interventional outcomes being dependent on the operator's experience. Computational fluid dynamics (CFD) is a powerful tool that can help to fill the gap in understanding LA and LAA morphology and complex haemodynamics characteristics. Nevertheless, despite the increasing number of LAAO interventions, only a limited number of in-silico studies explicitly incorporate LAAO devices in fluid simulations. In this talk I will present our most recent work analysing blood flow characteristics in relation with LA/LAA morphologies to better understand conditions that may lead to thrombus formation. A web-based platform, named VIDAA (Virtual Implantation of Devices for Left Atrial Appendage implantation) has been developed to support the clinical translation of the generated computational tools for the planning of the implantation of left atrial appendage occluder devices, which are used to cover the LAA in patients with atrial fibrillation.