A Robotic System with Path Planning and Visual Guidance for Teleoperated Left Atrial Appendage Closure
Angela Peloso, Nadia D'Alessandro, Xiu Zhang, Arianna Menciassi, Elena De Momi
AI summary
Problem
Manual navigation for percutaneous left atrial appendage closure (LAAC) is highly challenging due to dynamic cardiac anatomy, sheath movement, and prolonged radiation exposure, with no existing robotic systems tailored for this procedure.
Approach
The authors designed a robotic teleoperation system featuring a custom steerable sheath and an RRT*-based planning framework that generates and dynamically updates collision-free paths within a patient-specific virtual anatomical model.
Key results
- First integrated robotic platform for teleoperated LAAC with real-time planning and replanning
- Custom steerable sheath with robotic steering module enabling precise coaxial alignment
- Navigation guidance reduced target position error by 2.03% (planner) and 2.85% (replanner) versus unassisted manual control
- Planning and replanning strategies significantly reduced collisions with cardiac structures in benchtop validation
Why it matters
Enhances safety and precision for a critical stroke-prevention procedure while reducing operator radiation exposure and standardizing catheter navigation.
Abstract
Percutaneous Left Atrial Appendage Closure (LAAC) is a minimally invasive procedure to prevent throm- boembolic events in atrial fibrillation patients. The procedure’s success relies on precise navigation and occluder deployment, which is challenged by sheath movement in the dynamic cardiac environment, procedural complexity, and prolonged radiation exposure. This study introduces a robotic-assisted navigation system for LAAC procedure, integrating a dedicated steerable sheath, custom planning algorithms, and an intuitive teleopera- tion interface. The path-planning framework generates collision- free routes based on patient-specific anatomy, adjusting for deviations in real-time. The teleoperation interface comprises a digital replica of the patient’s anatomy with real-time visual feedback to the user for precise and intuitive navigation. Bench- top validation demonstrated that navigation guidance reduced target position error by 2.03% with the planner and 2.85% with the replanner, compared to free navigation without planning assistance. Planning and replanning strategies also reduced collisions with cardiac structures, highlighting the platform’s potential to improve procedural precision and safety.