OBJECTIVES: The objective of the study was to determine whether the metrics from a left-sided laparoscopic colectomy (LC) simulator could distinguish between the objectively scored performance of minimally invasive colorectal expert and novice surgeons. We report our results from the first virtual reality-based laparoscopic colorectal training course for experienced laparoscopic surgeons. METHODS: Eleven surgeons, experienced but novice in LC, constituted the novice group, and three experienced laparoscopic colorectal surgeons (>300 LCs) served as our experts. Novice subjects received didactic educational sessions and instruction in practice of LC from the experts. All subjects received instruction, demonstration, and supervision on the surgical technique to perform a LC on the simulator. All subjects then performed a laparoscopic colectomy on the simulator. Experts performed the same case as the novices. Outcomes measured by the simulator were time to perform the procedure, instrument path length, and smoothness of the trajectory of the instruments. Anatomy trays from the simulator were objectively scored for explicitly predefined intraoperative errors after each procedure. RESULTS: Expert surgeons performed significantly better then the novice colorectal surgeons with regard to instrument path length, instrument smoothness, and time taken to complete the procedure. Of the 13 predetermined errors, experts made significantly fewer errors in total then the novices (mean score 2.67 versus 4.7, p=0.03), and performed better in 8 out of 13 errors. CONCLUSION: The parameters assessed by the ProMIS VR simulator for laparoscopic colorectal training distinguished between novice and expert colorectal surgeons, despite using otherwise experienced novices who had extensive training before the procedure and expert mentoring during it. Experts performed the simulated procedure significantly faster with more efficient use of their instruments, and made fewer intraoperative errors. Thus the simulator demonstrated construct validity.
OBJECTIVES: The objective of the study was to determine whether the metrics from a left-sided laparoscopic colectomy (LC) simulator could distinguish between the objectively scored performance of minimally invasive colorectal expert and novice surgeons. We report our results from the first virtual reality-based laparoscopic colorectal training course for experienced laparoscopic surgeons. METHODS: Eleven surgeons, experienced but novice in LC, constituted the novice group, and three experienced laparoscopic colorectal surgeons (>300 LCs) served as our experts. Novice subjects received didactic educational sessions and instruction in practice of LC from the experts. All subjects received instruction, demonstration, and supervision on the surgical technique to perform a LC on the simulator. All subjects then performed a laparoscopic colectomy on the simulator. Experts performed the same case as the novices. Outcomes measured by the simulator were time to perform the procedure, instrument path length, and smoothness of the trajectory of the instruments. Anatomy trays from the simulator were objectively scored for explicitly predefined intraoperative errors after each procedure. RESULTS: Expert surgeons performed significantly better then the novice colorectal surgeons with regard to instrument path length, instrument smoothness, and time taken to complete the procedure. Of the 13 predetermined errors, experts made significantly fewer errors in total then the novices (mean score 2.67 versus 4.7, p=0.03), and performed better in 8 out of 13 errors. CONCLUSION: The parameters assessed by the ProMIS VR simulator for laparoscopic colorectal training distinguished between novice and expert colorectal surgeons, despite using otherwise experienced novices who had extensive training before the procedure and expert mentoring during it. Experts performed the simulated procedure significantly faster with more efficient use of their instruments, and made fewer intraoperative errors. Thus the simulator demonstrated construct validity.
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