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PMID: 30967786 Published · epublish English Journal Article

In silico Optimization of Left Atrial Appendage Occluder Implantation Using Interactive and Modeling Tools.

Frontiers in physiology ·Vol. 10 ·2019-00-00 ·页码 237

Aguado AM, Olivares AL, Yagüe C, Silva E, Nuñez-García M, Fernandez-Quilez Á, Mill J, Genua I, Arzamendi D, De Potter T, Freixa X, Camara O

Abstract

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 often 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 success dependent on clinician's experience. A sub-optimal LAAO implantation can generate thrombi outside the device, 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 select the most appropriate LAAO configurations (type of device, size, landing zone) for a given patient-specific LAA morphology. An initial LAAO configuration is proposed in VIDAA, automatically computed from LAA shape features (centreline, diameters). The most promising LAAO settings and LAA geometries were exported from VIDAA to build volumetric meshes and run Computational Fluid Dynamics (CFD) simulations to assess blood flow patterns after implantation. Risk of thrombus formation was estimated from the simulated hemodynamics with an index combining information from blood flow velocity and complexity. The combination of the VIDAA platform with in silico indices allowed to identify the LAAO configurations associated to a lower risk of thrombus formation; device positioning was key to the creation of regions with turbulent flows after implantation. Our results demonstrate the potential for optimizing LAAO therapy settings during pre-implant planning based on modeling tools and contribute to reduce the risk of thrombus formation after treatment.

Keywords
Computational Fluid Dynamics atrial fibrillation in silico optimization of therapies left atrial appendage occlusion web-based implantation platform
作者与单位
共 12 位作者,点击展开单位 / ORCID
Aguado Ainhoa M
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Olivares Andy L
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Yagüe Carlos
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Silva Etelvino
Division of Interventional Cardiology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.
Nuñez-García Marta
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Fernandez-Quilez Álvaro
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Mill Jordi
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Genua Ibai
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Arzamendi Dabit
Division of Interventional Cardiology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.
De Potter Tom
Arrhythmia Unit, Department of Cardiology, Cardiovascular Center, Aalst, Belgium.
Freixa Xavier
Department of Cardiology, Hospital Clínic de Barcelona, Universitat de Barcelona, Barcelona, Spain.
Camara Oscar
PhySense, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Article Info
Journal
Frontiers in physiology
Abbr.
Front Physiol
ISSN
1664-042X
Published
2019-00-00
电子出版
2019-00-22
页码
237
Language
English
Country/Region
Switzerland
NLM ID
101549006
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