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Validation of a Simulation Tool to Support Robotic-Assisted Surgical Training

originally published in the Journal of Minimally Invasive Gynecology

Sabrina Whitehurst, MD; Ernest Lockrow, DO; Thomas S Lendvay, MD; Joseph M. Gobern, MD; Anthony Skinner, MD; J.L. Buller, MD

Study Objective:   To compare the efficacy of simulation-based training (MIMIC dV Trainer) with that of traditional training. Initially we established proficiency standards for four MIMIC dV-Trainer tasks and three robotic dry lab tasks based on mean performance scores for experienced robotic surgeons. We then conducted an external validation experiment comparing transfer of robotic surgical skills acquired using the MIMIC dV-Trainer to skills acquired using Fundamentals of Laparoscopic Surgery (FLS) dry lab tasks performed on the da Vinci Surgical System in a robotic surgery transfer task completed on an animal model.

Design:   We performed a prospective randomized study analyzing the performance of 20 robotics-naïve subjects. Subjects were enrolled and an on-line da Vinci Intuitive Surgical didactic training module followed by training on the use of the da Vinci standard surgical robot. Baseline Spatial Abilities Tests were performed. Subjects then trained on either the da Vinci or the dV-Trainer to proficiency. Subjects performed the a cystotomy closure criterion task. Tool path and video were recorded using SurgTrak™ and the subject’s hand motions were tracked using Accelegloves by Anthrotronix. Performance was assessed using objective tracking data and using the validated Global Evaluative Assessment of Robotic Surgery, structured assessment tool performed by a panel of experienced surgeons.

Setting:   A University teaching hospital.

Participants:   20 robotics-naïve subjects including residents, fellows and staff in surgical specialties. Measurement and Main Results: We validated that there was no difference in surgeon performance with training on the dV-trainer vs the da Vinci robot. A post-hoc power analysis of the study demonstrated that within a 95% confidence interval we were able to detect a difference of 1 pt in the likert grading scale of proficiency. Based again on a 95% confidence interval for the difference in means (-.803, .543) non-inferiority was also proven in that neither method was inferior to each other.

Conclusions:   In this study, curriculum on the dV-trainer is comparable to traditional da Vinci robot training. Therefore, training on virtual reality is feasible to adopt as a preparatory step for future robotic surgeons. Either surgical training curriculum also showed similar performance when transferred to an actual surgical procedure in a live swine model. Thus, future validation studies are warranted to show the decrease need for utilizing animal models for robotic training.

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