Image-Based Flow Simulations of Pre- and Post-left Atrial Appendage Closure in the Left Atrium

Dongjie Jia1, Byunghwan Jeon2,3, Hyung-Bok Park3,4

  • 1Department of Mechanical, Aerospace & Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA.

Insights

This study introduces a computational fluid dynamic (CFD) framework to predict left atrial appendage (LAA) closure outcomes in atrial fibrillation patients. The simulation accurately predicted reduced thrombus formation risk, aiding procedural planning.

Area of Science:

  • Cardiovascular Imaging and Simulation
  • Medical Device Technology
  • Computational Fluid Dynamics

Background:

  • Atrial fibrillation (AF) patients are at high risk for stroke due to thrombus formation in the left atrial appendage (LAA).
  • Percutaneous LAA occlusion reduces stroke risk, but an 11% failure rate persists due to anatomical variabilities.
  • Accurate patient-specific assessment is crucial for effective LAA occlusion procedures.

Purpose of the Study:

  • To develop an image-based, patient-specific computational fluid dynamic (CFD) simulation framework.
  • To predict treatment outcomes for LAA closure procedures in atrial fibrillation patients.
  • To utilize automated image segmentation for reduced image processing time.

Main Methods:

  • A novel, fully-automated image segmentation procedure to identify left atrium (LA) and LAA geometries from CT scans.
  • Finite-element mesh generation to create a 3D volume mesh with defined boundary planes.
  • CFD simulations incorporating AF flow boundary conditions and analysis of pre- and post-LAA closure flow characteristics (velocity, streamlines, vortices).

Main Results:

  • CFD analysis on a patient with successful LAA closure showed a significant reduction in flow velocity (max factor 2.21).
  • Mitral outflow became more organized, and vortex size, number, intensity, and duration were dramatically reduced.
  • Predicted flow characteristics indicated a reduced risk of thrombus formation and stroke, consistent with the actual procedural outcome.

Conclusions:

  • The developed framework successfully predicted patient-specific LAA closure outcomes for an AF patient.
  • The framework holds potential as a tool for pre-procedural planning and patient selection.
  • Further validation with more patient data is required to establish broader clinical utility.
Abstract

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