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Robotic dismembered pyeloplasty surgical simulation using a 3D-printed silicone-based model: development, face
Hersh H Bendre1, Archana Rajender1, Philip V Barbosa1
1Boston Medical Center, Boston University School of Medicine, 725 Albany St., Suite 3B, Boston, MA, 02118, USA.
Journal of Robotic Surgery
|April 3, 2020
Summary
This study introduces a 3D-printed silicone model for robotic pyeloplasty training, enhancing resident surgical skills and confidence. The simulation demonstrated improved depth perception and overall performance in ureteropelvic junction obstruction procedures.
Area of Science:
- Medical simulation
- Surgical training
- 3D printing technology
Background:
- Ureteropelvic junction obstruction (UPJO) presents unique challenges for surgical resident training.
- Robotic-assisted pyeloplasty is a key procedure requiring specialized skills.
- Objective assessment of surgical performance is crucial for effective training.
Purpose of the Study:
- To develop and validate a 3D-printed silicone model for robotic pyeloplasty simulation.
- To assess the face validity and learning outcomes of the simulation.
- To evaluate the effectiveness of crowdsourced scoring for performance assessment.
Main Methods:
- Development of a 3D-printed silicone model of UPJO using 3D modeling software.
- Robotic-assisted pyeloplasty simulations performed by residents and faculty in a box trainer.
- Face validity assessed using a 5-point Likert scale.
- Surgical performance scored using Crowd-Sourced Assessment of Technical Skills (C-SATS) and Global Evaluative Assessment of Robotic Skills (GEARS) criteria.
Main Results:
- Participants completed simulations with patent anastomoses, showing improved speed between trials.
- Significant improvement in depth perception (p=0.006) and overall GEARS scores observed.
- High face validity scores for model aesthetics, feel, usability, and suturability.
- Residents reported a significant increase in confidence (p=0.03).
Conclusions:
- 3D-printed silicone models provide a valid and effective platform for robotic pyeloplasty training.
- The simulation enhances surgical skill acquisition, particularly in depth perception.
- Crowdsourced assessment effectively measures performance improvements and resident confidence.
