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PMID: 42616266 Published · aheadofprint English

An integrated fluid-dynamic and structural pipeline to assess atrial hemodynamics before and after left atrial appendage occluder deployment in a patient-specific anatomy.

Fanni BM, Danielli F, Bonfanti C, Verdirame I, Berti F, Gasparotti E, Berti S, Pennati G, Petrini L, Celi S

Abstract

Atrial fibrillation is associated with a high risk of thromboembolic events, often mitigated by left atrial appendage occlusion (LAAO) when anticoagulation is contraindicated. This study presents a patient-informed computational workflow integrating pre-operative computational fluid dynamics (CFD), finite element (FE) modeling of device deployment, and post-operative CFD informed by the FE-deformed configuration. A proof-of-concept case was analyzed considering three atrial wall stiffness values to explore biomechanical variability. Pre-implant CFD simulations identified regions of blood stasis within the left atrial appendage, highlighting areas of thrombotic risk. FE simulations of device deployment demonstrated that wall stiffness influenced device positioning, orientation, and contact with the atrial anatomy. Post-implant CFD analyses, incorporating both the FE-informed device configuration and two fabric reconstruction strategies (conformal vs. detached), revealed flow redirection and changes in wall shear stress consistent with effective occlusion and the impact of fabric variability. Overall, the proposed workflow enabled a coherent assessment of mechanical and hemodynamic outcomes, providing insights into how anatomical and biomechanical factors affect post-operative LA hemodynamics. This multiphysics approach offers a step toward a patient-informed computational framework for assessing device deployment and thrombogenic risk under complete occlusion conditions.

Keywords
Computational fluid dynamics Finite element analysis Hemodynamics Left atrial appendage occlusion Patient-specific modeling
Article Info
Journal
Medical & biological engineering & computing
Abbr.
Med Biol Eng Comput
ISSN
1741-0444
Published
2026-08-19
Language
English
Country/Region
United States
NLM ID
7704869
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