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Bayesian Optimization Based Preprocedural Planning For Robotic Left Atrial Appendage Occlusion.

Ran Hao1, Yuttana Itsarachaiyot1, M Cenk Çavuşoğlu1

  • 1Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH.

... International Symposium on Medical Robotics. International Symposium on Medical Robotics
|December 4, 2024
PubMed
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This study introduces a Bayesian Optimization approach for robotic left atrial appendage occlusion planning. It optimizes device implantation trajectories to reduce stroke risk in atrial fibrillation patients.

Area of Science:

  • Medical Robotics
  • Cardiovascular Interventions
  • Computational Optimization

Background:

  • Atrial fibrillation increases stroke risk via thromboembolism.
  • Left atrial appendage occlusion (LAAAO) is a key intervention to mitigate this risk.
  • Effective LAAAO requires precise preprocedural planning for optimal device implantation.

Purpose of the Study:

  • To propose a novel Bayesian Optimization (BO) based preprocedural planning approach for robotic LAAAO.
  • To enhance the efficiency and accuracy of identifying optimal transseptal puncture sites and occlusion trajectories.
  • To improve the success rate of LAAAO procedures through intelligent planning.

Main Methods:

  • Development of a BO-based planner for robotic LAAAO.
  • Sequential optimization of transseptal puncture locations over the fossa ovalis.

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  • Utilizing an iterative linear-quadratic-regulator for local trajectory optimization.
  • Evaluation in a simulation environment with a real cardiac anatomy model.

    • Main Results:

    • The BO planner efficiently sampled and optimized transseptal puncture positions.
    • Local optimization of occlusion trajectories was effectively performed.
    • The approach demonstrated feasibility in a simulated cardiac environment.

    Conclusions:

    • The proposed Bayesian Optimization approach offers an efficient method for preprocedural planning in robotic LAAAO.
    • This intelligent planning can enhance procedural success and patient safety.
    • Further validation in clinical settings is warranted.