Related Experiment Video
Updated: May 24, 2025

Simulator Training for Endovascular Neurosurgery
Published on: May 6, 2020
Impact of robotic assistance on the learning curve in endovascular interventions: exploring the role of operator
Tatjana Dell1, Marilia B Voigt2, Alexander Isaak2
1Department of Diagnostic and Interventional Radiology and Quantitative Imaging Lab Bonn (Qilab), University Hospital Bonn, Venusberg-Campus 1, Bonn, 53127, Germany. tatjana.dell@ukbonn.de.
Purpose:
This study investigates how endovascular interventionalists adapt to using a robotic platform, specifically the CorPath GRX Robotic System, and examines the influence of prior manual catheterization experience.
Materials And Methods:
An in-vitro trial was conducted to assess the adaptation to robot-assisted catheter-guided interventions in comparison to manual catheterization using a neurovascular phantom. Three interventional radiologists (beginner: no manual experience; intermediate: 3 years; expert: 10 years) with varying experience levels performed three corresponding robotic and manual guided superselective catherization tasks with three attempts per position with both approaches. Procedure time and total radiation dose was recorded.
Results:
For the beginner reduced intervention times were noted using the robot-assisted approach (mean: 123 s) in comparison to manual catheterization (mean: 257 s; p = 0.008), whilst no differences were seen in between procedure durations for the intermediate (mean: 71 s for manual versus 102 s for robotic; p = 0.388) and expert interventionalist (mean: 30 s for manual versus 42 s for robotic; p = 0.479). The beginner also benefited significantly from robot-assisted procedures with lower emitted total radiation doses (mean: 0.007 Gy for manual versus 0.003 Gy for robotic; p = 0.007), while no significant differences are observed for intermediate (mean: 0.002 Gy for manual versus 0.003 Gy for robotic; p = 0.137) and expert practitioners (mean: 0.0008 Gy for manual versus 0.001 Gy for robotic; p = 0.459).
Conclusion:
Robot-assisted platforms accelerate skill acquisition for beginners while maintaining efficiency for experienced practitioners. However, addressing costs and training requirements is essential for wider adoption and optimized outcomes.

