An integrated fluid-dynamic and structural pipeline to assess atrial hemodynamics before and after left atrial

Benigno Marco Fanni1, Francesca Danielli2, Chiara Bonfanti1,3

  • 1BioCardioLab, Bioengineering Unit, Fondazione Monasterio, Massa, 54100, Italy.

Insights

This study introduces a computational workflow to assess left atrial appendage occlusion (LAAO) device placement and blood clot risk. It analyzes how patient anatomy and device fit impact outcomes for atrial fibrillation patients.

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Research
  • Computational Science

Background:

  • Atrial fibrillation (AF) carries a high risk of thromboembolic events.
  • Left atrial appendage occlusion (LAAO) is an alternative to anticoagulation for stroke prevention in AF patients.
  • Understanding biomechanical and hemodynamic factors is crucial for optimizing LAAO success.

Purpose of the Study:

  • To develop and validate a patient-informed computational workflow for assessing LAAO device deployment.
  • To investigate the influence of atrial wall stiffness on device placement and post-operative hemodynamics.
  • To evaluate the impact of different fabric reconstruction strategies on hemodynamic outcomes.

Main Methods:

  • Integration of pre-operative computational fluid dynamics (CFD) and finite element (FE) modeling.
  • FE analysis of LAAO device deployment considering varying atrial wall stiffness.
  • Post-operative CFD simulations incorporating FE-deformed configurations and fabric models.

Main Results:

  • Pre-implant CFD identified thrombotic risk regions in the left atrial appendage.
  • FE simulations showed atrial stiffness affects device positioning and interaction with anatomy.
  • Post-implant CFD revealed flow redirection and altered wall shear stress due to device configuration and fabric variability.

Conclusions:

  • The proposed multiphysics workflow enables comprehensive assessment of mechanical and hemodynamic outcomes for LAAO.
  • Anatomical and biomechanical factors significantly influence post-operative left atrial hemodynamics.
  • This approach advances patient-specific computational frameworks for LAAO device deployment and thrombogenic risk evaluation.

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