Needs Analysis for Developing a Virtual Reality NOTES Simulator
Identifieur interne : 001A20 ( Pmc/Corpus ); précédent : 001A19; suivant : 001A21Needs Analysis for Developing a Virtual Reality NOTES Simulator
Auteurs : Ganesh Sankaranarayanan ; Kai Matthes ; Arun Nemani ; Woojin Ahn ; Masayuki Kato ; Daniel B. Jones ; Steven Schwaitzberg ; Suvranu DeSource :
- Surgical endoscopy [ 0930-2794 ] ; 2012.
Abstract
Natural orifice translumenal endoscopic surgery (NOTES) is an emerging surgical technique that requires a cautious adoption approach to ensure patient safety. High fidelity virtual reality-based simulators allow development of new surgical procedures and tools and train medical personnel without risk to human patients. As part of a project funded by the National Institutes of Health, we are developing a Virtual Transluminal Endoscopic Surgery Trainer (VTEST™) for this purpose. The objective of this study is to conduct a structured needs analysis to identify the design parameters for such a virtual reality-based simulator for NOTES.
A 30-point questionnaire was distributed at the 2011 NOSCAR meeting to get responses from the experts. Ordinal logistic regression and the Wilcoxon rank sum test were used for analysis.
A total of 22 NOTES experts participated in the study. Cholecystectomy (CE, 68%) followed by appendectomy (AE, 63%) (CE vs AE, p=0.0521) was selected as the first choice for simulation. Flexible (FL, 47%) and hybrid (HY, 47%) approaches were equally favorable compared to rigid (RI, 6%) with p<0.001 for both FL vs RI and HY vs RI. The transvaginal approach was preferred 3 to 1 to the transgastric. Most participants preferred two channel (2C) scopes (65%) compared to single (1C) or three (3C) or more channels with p<0.001 for both 2C vs 1C and 2C vs 3C. The importance of force feedback and the utility of a virtual NOTES simulator in training and testing new tools for NOTES were rated very high by the participants.
Our study reinforced the importance of developing a virtual NOTES simulator and clearly presented expert preferences. The results of this analysis will direct our initial development of the VTESTTM platform.
Url:
DOI: 10.1007/s00464-012-2637-1
PubMed: 23247736
PubMed Central: 3618859
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