PD6-07 AUGMENTED REALITY VIDEO SIMULATION FOR ROBOTIC PARTIAL NEPHRECTOMY SURGERY TRAINING – THE NEXT GENERATION

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You have accessJournal of UrologyTechnology & Instruments: Surgical Education & Skills Assessment I1 Apr 2014PD6-07 AUGMENTED REALITY VIDEO SIMULATION FOR ROBOTIC PARTIAL NEPHRECTOMY SURGERY TRAINING – THE NEXT GENERATION Andrew J. Hung, Daniel H. Shin, Wesley Yip, and Inderbir S. Gill Andrew J. HungAndrew J. Hung More articles by this author , Daniel H. ShinDaniel H. Shin More articles by this author , Wesley YipWesley Yip More articles by this author , and Inderbir S. GillInderbir S. Gill More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.515AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Mimic Technologies and USC Urology have jointly developed a prototype simulation interface featuring augmented video on the dV-Trainer. Users observe 3D video of robotic kidney surgeries and use virtual instruments to identify anatomy, demonstrate technical skills, and learn operation steps. Herein, we evaluate the face, content, and construct validity of the next generation simulation, which features expanded modules with special focus on anatomy. METHODS Participants were classified as “novice” (no prior robotic cases, n=28) or “expert” (≥30 cases, n=10) and prospectively assessed on 3 modules of a robotic partial nephrectomy: colon mobilization, duodenal Kocherization and hilar dissection. Questions were categorized as anatomy, technical, or steps, and metrics were analyzed with 2-sided t tests (construct validity). A post-study questionnaire assessed realism of simulation (face validity) and utility for training (content validity). RESULTS Novices and experts had performed a median of 0 and 150 (range 35-1000) robotic cases (p<0.001). Experts rated the modules as realistic (average 7/10) and helpful (8/10) in resident training. Overall, experts completed the exercises more accurately (p<0.001) and efficiently (p=0.02) than novices. Detailed analysis revealed that in Module 1, novices initially identified anatomy slower than experts (p=0.002), but with question repetition, their performance in the latter third of the module equaled the experts (p=0.16). CONCLUSIONS This next-generation augmented reality prototype simulation displays face and content validity, with expanded construct validity in teaching anatomy, retraction skills and steps of surgery. It is the first of its kind to statistically demonstrate the ability to teach surgical anatomy to novices so that their recognition ability nears that of experts. Contemporary surgical simulation requires vigorous step-wise validation throughout the development process. © 2014FiguresReferencesRelatedDetailsCited byHung A, Shah S, Dalag L, Shin D and Gill I (2018) Development and Validation of a Novel Robotic Procedure Specific Simulation Platform: Partial NephrectomyJournal of Urology, VOL. 194, NO. 2, (520-526), Online publication date: 1-Aug-2015. Volume 191Issue 4SApril 2014Page: e132-e133 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Andrew J. Hung More articles by this author Daniel H. Shin More articles by this author Wesley Yip More articles by this author Inderbir S. Gill More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...