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Related Experiment Video

Updated: Sep 18, 2025

Simulator Training for Endovascular Neurosurgery
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A simulation environment for robot-assisted endovascular interventions.

Matteo Pescio1,2,3, Chenhao Li4, Dennis Kundrat4,5

  • 1Politecnico di Torino, Turin, Italy.

International Journal of Computer Assisted Radiology and Surgery
|June 24, 2025
PubMed
Summary
This summary is machine-generated.

This study developed a simulation environment for robotic endovascular procedures, improving catheter force and position accuracy. The findings enhance minimally invasive surgery by enabling greater precision in complex vascular interventions.

Keywords:
Digital twinEndovascular robotic surgeryModel-based force and shape sensingSurgical simulation

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Area of Science:

  • Medical Robotics
  • Computational Surgery
  • Biomechanical Engineering

Background:

  • Cardiovascular diseases are a leading global cause of death.
  • Endovascular procedures offer an alternative to open surgery.
  • Robotic platforms and navigation software enhance endovascular interventions.

Purpose of the Study:

  • Develop a model-based simulation environment for endovascular robotic procedures.
  • Enable shape and force sensing capabilities within the SOFA framework.
  • Improve accuracy and reliability in minimally invasive surgical applications.

Main Methods:

  • Modeled vascular catheters using beam theory.
  • Applied finite element method (FEM) for realistic catheter-vasculature interactions.
  • Validated simulation with experimental measurements of forces and displacements.

Main Results:

  • Simulated force and displacement measurements were experimentally validated.
  • Catheter contact force showed an absolute error of 0.0371 N (30.45%).
  • Elastic FEM model demonstrated best performance for anatomical deformation with varying errors.

Conclusions:

  • Advanced physical modeling and human-robot interactions improve MIS accuracy.
  • Enhanced computational capabilities support innovative solutions in endovascular interventions.
  • The developed simulation environment contributes to greater clinician accuracy and reliability.