Literature DB >> 24122244

Can we become better robot surgeons through simulator practice?

Ankit Patel, Meghna Patel, Nathaniel Lytle, Juan P Toro, Rachel L Medbery, Sheryl Bluestein, Sebastian D Perez, John F Sweeney, S Scott Davis, Edward Lin.   

Abstract

INTRODUCTION: There is significant growth in the use of the robotic surgery platform in the general surgery community. Current pre-requisites for robot surgery training include performing basic tasks on a simulator and achieving a minimum overall score for each task. However, there is limited information about these tasks related to performance and time required to become proficient. We focused on critical tasks that have the highest potential for preventing inadvertent injuries, and constructed models to predict how many attempts would be needed to master the tasks depending on the user's initial attempt. METHODS AND PROCEDURES: This study was conducted using de-identified data collected over 12 months from the dV-Trainers® simulator at our institution. We analyzed tasks used in institutional surgical robot credentialing that focused on camera manipulation and energy use. Data were extracted from the Camera Targeting, Energy Dissection, and Energy Switching exercises focusing on individual metrics such as Time to Complete Exercise, Economy of Motion, Misapplied Energy Time, and Blood Volume Loss. Mixed linear models looking at sequential attempts and specific performance metrics were constructed using IBM SPSS Statistics version 20.
RESULTS: Over 26,000 overall minutes of recorded use was logged in our simulator by more than 30 unique users across all exercises. An average of 15 users performed each of the analyzed exercises, with an average of eight attempts per exercise. Based on our models, on average most users would need four to five attempts to achieve 80 % proficiency for any given metric.
CONCLUSION: Virtual reality robotic simulators such as the dv-Trainer® can be used by general surgeons to become better robotic surgeons. Our data suggests that it can be used by a surgeon to predict how much time and effort one would need to spend on the simulator in order to become proficient with the robot, especially in critical metrics such as camera manipulation and energy application. Surgeons who require more attempts to successfully complete tasks may want to consider additional training methods, such as proctoring or hands-on laboratories, to improve robot surgery proficiency.

Entities:  

Mesh:

Year:  2014        PMID: 24122244     DOI: 10.1007/s00464-013-3231-x

Source DB:  PubMed          Journal:  Surg Endosc        ISSN: 0930-2794            Impact factor:   4.584


  11 in total

1.  Virtual reality training improves operating room performance: results of a randomized, double-blinded study.

Authors:  Neal E Seymour; Anthony G Gallagher; Sanziana A Roman; Michael K O'Brien; Vipin K Bansal; Dana K Andersen; Richard M Satava
Journal:  Ann Surg       Date:  2002-10       Impact factor: 12.969

2.  Concurrent and predictive validation of a novel robotic surgery simulator: a prospective, randomized study.

Authors:  Andrew J Hung; Mukul B Patil; Pascal Zehnder; Jie Cai; Casey K Ng; Monish Aron; Inderbir S Gill; Mihir M Desai
Journal:  J Urol       Date:  2011-12-15       Impact factor: 7.450

3.  Validation study of a virtual reality robotic simulator--role as an assessment tool?

Authors:  Jason Y Lee; Phillip Mucksavage; David C Kerbl; Victor B Huynh; Mohamed Etafy; Elspeth M McDougall
Journal:  J Urol       Date:  2012-01-20       Impact factor: 7.450

4.  The virtual reality simulator dV-Trainer(®) is a valid assessment tool for robotic surgical skills.

Authors:  Cyril Perrenot; Manuela Perez; Nguyen Tran; Jean-Philippe Jehl; Jacques Felblinger; Laurent Bresler; Jacques Hubert
Journal:  Surg Endosc       Date:  2012-04-05       Impact factor: 4.584

5.  A study on the learning curve of the robotic virtual reality simulator.

Authors:  Sung Gu Kang; Kyung Sook Yang; Young Hwii Ko; Seok Ho Kang; Hong Seok Park; Jeong Gu Lee; Je Jong Kim; Jun Cheon
Journal:  J Laparoendosc Adv Surg Tech A       Date:  2012-03-08       Impact factor: 1.878

6.  Does training on a virtual reality robotic simulator improve performance on the da Vinci surgical system?

Authors:  Michelle A Lerner; Mikias Ayalew; William J Peine; Chandru P Sundaram
Journal:  J Endourol       Date:  2010-03       Impact factor: 2.942

7.  Proficiency-based virtual reality training significantly reduces the error rate for residents during their first 10 laparoscopic cholecystectomies.

Authors:  Gunnar Ahlberg; Lars Enochsson; Anthony G Gallagher; Leif Hedman; Christian Hogman; David A McClusky; Stig Ramel; C Daniel Smith; Dag Arvidsson
Journal:  Am J Surg       Date:  2007-06       Impact factor: 2.565

Review 8.  Systematic review of randomized controlled trials on the effectiveness of virtual reality training for laparoscopic surgery.

Authors:  K Gurusamy; R Aggarwal; L Palanivelu; B R Davidson
Journal:  Br J Surg       Date:  2008-09       Impact factor: 6.939

9.  da Vinci skills simulator for assessing learning curve and criterion-based training of robotic basic skills.

Authors:  Willem M Brinkman; Jan-Maarten Luursema; Bas Kengen; Barbara M A Schout; J Alfred Witjes; Ruud L Bekkers
Journal:  Urology       Date:  2013-01-04       Impact factor: 2.649

10.  Randomized clinical trial of virtual reality simulation for laparoscopic skills training.

Authors:  T P Grantcharov; V B Kristiansen; J Bendix; L Bardram; J Rosenberg; P Funch-Jensen
Journal:  Br J Surg       Date:  2004-02       Impact factor: 6.939

View more
  7 in total

1.  Development of a virtual reality robotic surgical curriculum using the da Vinci Si surgical system.

Authors:  Pedro Pablo Gomez; Ross E Willis; Kent R Van Sickle
Journal:  Surg Endosc       Date:  2014-11-01       Impact factor: 4.584

Review 2.  Review of robotics in foregut and bariatric surgery.

Authors:  Juan P Toro; Edward Lin; Ankit D Patel
Journal:  Surg Endosc       Date:  2014-06-28       Impact factor: 4.584

Review 3.  SAGES guidelines for the introduction of new technology and techniques.

Authors:  Dimitrios Stefanidis; Robert D Fanelli; Ray Price; William Richardson
Journal:  Surg Endosc       Date:  2014-06-18       Impact factor: 4.584

4.  "Alarm-corrected" ergonomic armrest use could improve learning curves of novices on robotic simulator.

Authors:  Kun Yang; Manuela Perez; Gabriela Hossu; Nicolas Hubert; Cyril Perrenot; Jacques Hubert
Journal:  Surg Endosc       Date:  2016-05-17       Impact factor: 4.584

5.  The effect of different training exercises on the performance outcome on the da Vinci Skills Simulator.

Authors:  U Walliczek-Dworschak; M Schmitt; P Dworschak; I Diogo; A Ecke; M Mandapathil; A Teymoortash; C Güldner
Journal:  Surg Endosc       Date:  2016-09-20       Impact factor: 4.584

6.  Peer Review and Surgical Innovation: Robotic Surgery and Its Hurdles.

Authors:  Dinesh Vyas; Sean Cronin
Journal:  Am J Robot Surg       Date:  2015-12-01

7.  Current status of simulation-based training and assessment in urological robot-assisted surgery.

Authors:  Phil Hyun Song
Journal:  Investig Clin Urol       Date:  2016-11-07
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.