You have accessJournal of UrologySurgical Technology & Simulation: Training & Skills Assessment I (MP34)1 Apr 2020MP34-15 A DISSECTION GESTURE CLASSIFICATION AND INITIAL VALIDATION ON ROBOTIC RENAL HILUM PREPARATION Runzhuo Ma*, Erik Vanstrum, Shubham Bhatia, Ryan Lee, Jessica Nguyen, Andrew Chen, Jian Chen, and Andrew Hung Runzhuo Ma*Runzhuo Ma* More articles by this author , Erik VanstrumErik Vanstrum More articles by this author , Shubham BhatiaShubham Bhatia More articles by this author , Ryan LeeRyan Lee More articles by this author , Jessica NguyenJessica Nguyen More articles by this author , Andrew ChenAndrew Chen More articles by this author , Jian ChenJian Chen More articles by this author , and Andrew HungAndrew Hung More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000878.015AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The deconstruction of surgery into a semantic vocabulary yields an effective tool for surgical education. Herein, we disassemble tissue dissection into basic maneuvers, then utilize them to compare dissection between experts (E) and novices (N) during robotic renal hilum preparation. METHODS: Videos of robotic renal hilum dissection were manually reviewed. Only cases where the dominant hand uses monopolar scissors were included. Experts were defined by > 100 prior robotic cases, while novices ≤100 cases. 6 expert surgeons at our center arrived at a consensus for a dissection gestures classification system: blunt dissection (spread, peel/push, hook), sharp dissection (cold cut, energy cut and burn), and combination gestures (pediclize = multiple peels, hand over hand = both hands push) (Fig 1a). Continuous variables were compared by Mann-Whitney U test, and categorical variables by Chi-square test. RESULTS: 19 hilar dissections with 3,179 dissection maneuvers were analyzed, representing 11 cases from 6 expert surgeons (median 1750, range [150-3500] cases) and 8 cases from 6 novices (median 80 [5-100] cases). Patient baseline variables were comparable (p > 0.05). Compared to novices, experts were more efficient completing the artery preparation (E 32 vs N 83 gestures, p = 0.004) (Fig 1b). Experts needed less retraction adjustments (E 26 vs N 55 gestures, p = 0.047) and utilized more hand over hand gestures (5 vs 1 counts, p = 0.005). During artery preparation, they used more proportion of hook (E 15.7% vs N 6.4%, p<0.001) and burn (E 24.1% vs N 10.7%, p<0.001) (Fig 1c). Experts were more efficient with spread (E 2.71 vs N 2.96 s/gesture, p = 0.028) and hook (E 2.20 s vs N 2.50 s/gesture, p = 0.05), but spent more time with peel/push (E 1.73 vs N 1.44 s/gesture, p<0.001), energy cut (E 2.28 vs 1.50 s/gesture, p<0.001) and pediclize (E 4.05 vs 2.92 s/gesture, p<0.001). Overall, surgeons spent more time with peel/push (1.58 vs 1.41 s/gesture, p<0.001) and hook (2.79 vs 1.23 s/gesture, p<0.001) around the vein vs artery. CONCLUSIONS: This dissection gesture classification system can disassemble the renal hilum preparation. We found differences in dissection patterns of experts vs novices. This novel comprehensive classification may help streamline surgery education. Source of Funding: none © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e509-e509 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Runzhuo Ma* More articles by this author Erik Vanstrum More articles by this author Shubham Bhatia More articles by this author Ryan Lee More articles by this author Jessica Nguyen More articles by this author Andrew Chen More articles by this author Jian Chen More articles by this author Andrew Hung More articles by this author Expand All Advertisement PDF downloadLoading ...