Skip to main content
Log in

Learning Tools and Simulation in Robotic Surgery: State of the Art

  • Published:
World Journal of Surgery Aims and scope Submit manuscript

Abstract

Robotic surgery has emerged as a new technology over the last decade and has brought with it new challenges, particularly in terms of teaching and training. To overcome these challenges, robotic courses, virtual simulation, and dual consoles have been successfully introduced. In fact, there are several simulators currently on the market that have proven to be a valid option for training, especially for the novice trainee. Robotic courses have also found success around the world, allowing participants to implement robotic programs at their institution, typically with the help of a proctor. More recently, the dual console has enabled two surgeons to be operating at the same time. Having one experienced surgeon and one trainee each at his or her own console has made it an obvious choice for training. Although these methods have been successfully introduced, the data remain relatively scarce concerning their role in training. The aim of this article was to review the various methods and tools involved in the training of surgeons in robotic surgery.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Buchs NC, Addeo P, Bianco FM et al (2012) Perioperative risk assessment in robotic general surgery: lessons learned from 884 cases at a single institution. Arch Surg 147:701–708

    Article  PubMed  Google Scholar 

  2. Buchs NC, Volonte F, Pugin F et al (2011) Robotic pancreatic resection: how far can we go? Minerva Chir 66:603–614

    PubMed  CAS  Google Scholar 

  3. Giulianotti PC, Addeo P, Buchs NC et al (2011) Robotic extended pancreatectomy with vascular resection for locally advanced pancreatic tumors. Pancreas 40:1264–1270

    Article  PubMed  Google Scholar 

  4. Giulianotti PC, Coratti A, Sbrana F et al (2011) Robotic liver surgery: results for 70 resections. Surgery 149:29–39

    Article  PubMed  Google Scholar 

  5. Buchs NC, Addeo P, Bianco FM et al (2010) Outcomes of robot-assisted pancreaticoduodenectomy in patients older than 70 years: a comparative study. World J Surg 34:2109–2114. doi:10.1007/s00268-010-0650-x

    Article  PubMed  Google Scholar 

  6. Buchs NC, Addeo P, Bianco FM et al (2011) Robotic versus open pancreaticoduodenectomy: a comparative study at a single institution. World J Surg 35:2739–2746. doi:10.1007/s00268-011-1276-3

    Article  PubMed  Google Scholar 

  7. Buchs NC (2012) Training in robotic general surgery: the next challenge. Adv Robot Autom 1:e104

    Article  Google Scholar 

  8. Kelly DC, Margules AC, Kundavaram CR et al (2012) Face, content, and construct validation of the Da Vinci Skills Simulator. Urology 79:1068–1072

    Article  PubMed  Google Scholar 

  9. Lallas CD, Members of the Society of Urologic Robotic Surgeons (2012) Robotic surgery training with commercially available simulation systems in 2011: a current review and practice pattern survey from the Society of Urologic Robotic Surgeons. J Endourol 26:283–293

    Article  PubMed  Google Scholar 

  10. Abboudi H, Khan MS, Aboumarzouk O et al (2012) Current status of validation for robotic surgery simulators: a systematic review. BJU Int 11:194–205

    Google Scholar 

  11. Schreuder HW, Wolswijk R, Zweemer RP et al (2012) Training and learning robotic surgery, time for a more structured approach: a systematic review. BJOG 119:137–149

    Article  PubMed  CAS  Google Scholar 

  12. Da Cruz JA, Sandy NS, Passerotti CC et al (2010) Does training laparoscopic skills in a virtual reality simulator improve surgical performance? J Endourol 24:1845–1849

    Article  PubMed  Google Scholar 

  13. Fairhurst K, Strickland A, Maddern G (2011) The LapSim virtual reality simulator: promising but not yet proven. Surg Endosc 25:343–355

    Article  PubMed  Google Scholar 

  14. Seymour NE, Gallagher AG, Roman SA et al (2002) Virtual reality training improves operating room performance: results of a randomized, double-blinded study. Ann Surg 236:458–463

    Article  PubMed  Google Scholar 

  15. Torkington J, Smith SG, Rees BI et al (2001) Skill transfer from virtual reality to a real laparoscopic task. Surg Endosc 15:1076–1079

    Article  PubMed  CAS  Google Scholar 

  16. Andreatta PB, Woodrum DT, Birkmeyer JD et al (2006) Laparoscopic skills are improved with LapMentor training: results of a randomized, double-blinded study. Ann Surg 243:854–860

    Article  PubMed  Google Scholar 

  17. Grantcharov TP, Kristiansen VB, Bendix J et al (2004) Randomized clinical trial of virtual reality simulation for laparoscopic skills training. Br J Surg 91:146–150

    Article  PubMed  CAS  Google Scholar 

  18. Fiedler MJ, Chen SJ, Judkins TN et al (2007) Virtual reality for robotic laparoscopic surgical training. Stud Health Technol Inform 125:127–129

    PubMed  Google Scholar 

  19. Finnegan KT, Meraney AM, Staff I et al (2012) da Vinci Skills Simulator construct validation study: correlation of prior robotic experience with overall score and time score simulator performance. Urology 80:330–335

    Article  PubMed  Google Scholar 

  20. Gavazzi A, Bahsoun AN, Van Haute W et al (2011) Face, content and construct validity of a virtual reality simulator for robotic surgery (SEP Robot). Ann R Coll Surg Engl 93:152–156

    Article  PubMed  Google Scholar 

  21. Guru KA, Baheti A, Kesavadas T et al (2009) In-vivo videos enhance cognitive skills for da Vinci Surgical System. J Urol 181(Suppl):823

    Article  Google Scholar 

  22. Hung AJ, Patil MB, Zehnder P et al (2012) Concurrent and predictive validation of a novel robotic surgery simulator: a prospective, randomized study. J Urol 187:630–637

    Article  PubMed  Google Scholar 

  23. Hung AJ, Zehnder P, Patil MB et al (2011) Face, content and construct validity of a novel robotic surgery simulator. J Urol 186:1019–1024

    Article  PubMed  Google Scholar 

  24. Kenney PA, Wszolek MF, Gould JJ et al (2009) Face, content, and construct validity of dV-trainer, a novel virtual reality simulator for robotic surgery. Urology 73:1288–1292

    Article  PubMed  Google Scholar 

  25. Kesavadas T, Kumar A, Srimathveeravalli G et al (2009) Efficacy of robotic surgery simulator (RoSS) for the daVinci surgical system. J Urol 181(Suppl):823

    Article  Google Scholar 

  26. Korets R, Graversen JA, Mues A et al (2011) Face and construct validity assessment of 2nd generation robotic surgery simulator. J Urol 185(Suppl):e488

    Article  Google Scholar 

  27. Korets R, Mues A, Graversen J et al (2011) Comparison of robotic surgery skill acquisition between DV-trainer and da Vinci Surgical System: a randomized controlled study. J Urol 185(Suppl):e593

    Article  Google Scholar 

  28. Lendvay TS, Casale P, Sweet R et al (2008) VR robotic surgery: randomized blinded study of the dV-Trainer robotic simulator. Stud Health Technol Inform 132:242–244

    PubMed  Google Scholar 

  29. Lendvay TS, Casale P, Sweet R et al (2008) Initial validation of a virtual-reality robotic simulator. J Robot Surg 2:145–149

    Article  Google Scholar 

  30. Lerner MA, Ayalew M, Peine WJ et al (2010) Does training on a virtual reality robotic simulator improve performance on the da Vinci surgical system? J Endourol 24:467–472

    Article  PubMed  Google Scholar 

  31. Liss MA, Abdelshehid C, Quach S et al (2012) Validation, correlation, and comparison of the da Vinci trainer and the da Vinci surgical skills simulator using the mimic software for urologic robotic surgical education. J Endourol 26:1629–1634

    Article  PubMed  Google Scholar 

  32. Seixas-Mikelus SA, Kesavadas T, Srimathveeravalli G et al (2010) Face validation of a novel robotic surgical simulator. Urology 76:357–360

    Article  PubMed  Google Scholar 

  33. Seixas-Mikelus SA, Stegemann AP, Kesavadas T et al (2011) Content validation of a novel robotic surgical simulator. BJU Int 107:1130–1135

    Article  PubMed  Google Scholar 

  34. Sethi AS, Peine WJ, Mohammadi Y et al (2009) Validation of a novel virtual reality robotic simulator. J Endourol 23:503–508

    Article  PubMed  Google Scholar 

  35. Perrenot C, Perez M, Tran N, Jehl JP et al (2012) The virtual reality simulator dV-Trainer® is a valid assessment tool for robotic surgical skills. Surg Endosc 26:2587–2593

    Article  PubMed  Google Scholar 

  36. Wass V, Van der Vleuten C, Shatzer J et al (2001) Assessment of clinical competence. Lancet 357:945–949

    Article  PubMed  CAS  Google Scholar 

  37. Ahmed K, Miskovic D, Darzi A et al (2011) Observational tools for assessment of procedural skills: a systematic review. Am J Surg 202:469–480

    Article  PubMed  Google Scholar 

  38. Ahmed K, Ashrafian H, Hanna GB et al (2009) Assessment of specialists in cardiovascular practice. Nat Rev Cardiol 6:659–667

    Article  PubMed  Google Scholar 

  39. Lee JY, Mucksavage P, Kerbl DC et al (2012) Validation study of a virtual reality robotic simulator—role as an assessment tool? J Urol 187:998–1002

    Article  PubMed  Google Scholar 

  40. Korets R, Mues AC, Graversen JA et al (2011) Validating the use of the Mimic dV-trainer for robotic surgery skill acquisition among urology residents. Urology 78:1326–1330

    Article  PubMed  Google Scholar 

  41. Katsavelis D, Siu KC, Brown-Clerk B et al (2009) Validated robotic laparoscopic surgical training in a virtual-reality environment. Surg Endosc 23:66–73

    Article  PubMed  Google Scholar 

  42. Kesavadas T, Stegemann A, Sathyaseelan G et al (2011) Validation of Robotic Surgery Simulator (RoSS). Stud Health Technol Inform 163:274–276

    PubMed  Google Scholar 

  43. Albani JM, Lee DI (2007) Virtual reality-assisted robotic surgery simulation. J Endourol 21:285–287

    Article  PubMed  Google Scholar 

  44. Van der Meijden OA, Broeders IA, Schijven MP (2010) The SEP “robot”: a valid virtual reality robotic simulator for the da Vinci surgical system? Surg Technol Int 19:51–58

    PubMed  Google Scholar 

  45. Balasundaram I, Aggarwal R, Darzi A (2008) Short-phase training on a virtual reality simulator improves technical performance in tele-robotic surgery. Int J Med Robot 4:139–145

    Article  PubMed  Google Scholar 

  46. Lin DW, Romanelli JR, Kuhn JN et al (2009) Computer-based laparoscopic and robotic surgical simulators: performance characteristics and perceptions of new users. Surg Endosc 23:209–214

    Article  PubMed  Google Scholar 

  47. Hanly EJ, Miller BE, Kumar R et al (2006) Mentoring console improves collaboration and teaching in surgical robotics. J Laparoendosc Adv Surg Tech A 16:445–451

    Article  PubMed  Google Scholar 

  48. Marengo F, Larrain D, Babilonti L et al (2012) Learning experience using the double-console da Vinci surgical system in gynecology: a prospective cohort study in a university hospital. Arch Gynecol Obstet 285:441–445

    Article  PubMed  Google Scholar 

  49. Smith AL, Krivak TC, Scott EM et al (2012) Dual-console robotic surgery compared to laparoscopic surgery with respect to surgical outcomes in a gynecologic oncology fellowship program. Gynecol Oncol 126:432–436

    Article  PubMed  Google Scholar 

  50. Patel HR, Linares A, Joseph JV (2009) Robotic and laparoscopic surgery: cost and training. Surg Oncol 18:242–246

    Article  PubMed  Google Scholar 

  51. Corica FA, Boker JR, Chou DS et al (2006) Short-term impact of a laparoscopic “mini-residency” experience on postgraduate urologists’ practice patterns. J Am Coll Surg 203:692–698

    Article  PubMed  Google Scholar 

  52. Sim HG, Yip SK, Lau WK et al (2006) Team-based approach reduces learning curve in robot-assisted laparoscopic radical prostatectomy. Int J Urol 13:560–564

    Article  PubMed  Google Scholar 

  53. Hanly EJ, Marohn MR, Bachman SL et al (2004) Multiservice laparoscopic surgical training using the daVinci surgical system. Am J Surg 187:309–315

    Article  PubMed  Google Scholar 

  54. Hernandez JD, Bann SD, Munz Y et al (2004) Qualitative and quantitative analysis of the learning curve of a simulated surgical task on the da Vinci system. Surg Endosc 18:372–378

    Article  PubMed  CAS  Google Scholar 

  55. Ro CY, Toumpoulis IK, Ashton RC et al (2005) A novel drill set for the enhancement and assessment of robotic surgical performance. Stud Health Technol Inform 111:418–421

    PubMed  Google Scholar 

  56. Narazaki K, Oleynikov D, Stergiou N (2006) Robotic surgery training and performance: identifying objective variables for quantifying the extent of proficiency. Surg Endosc 20:96–103

    Article  PubMed  CAS  Google Scholar 

  57. Mehrabi A, Yetimoglu CL, Nickkholgh A et al (2006) Development and evaluation of a training module for the clinical introduction of the da Vinci robotic system in visceral and vascular surgery. Surg Endosc 20:1376–1382

    Article  PubMed  CAS  Google Scholar 

  58. Vlaovic PD, Sargent ER, Boker JR et al (2008) Immediate impact of an intensive one-week laparoscopy training program on laparoscopic skills among postgraduate urologists. JSLS 12:1–8

    PubMed  Google Scholar 

  59. Marecik SJ, Prasad LM, Park JJ et al (2008) A lifelike patient simulator for teaching robotic colorectal surgery: how to acquire skills for robotic rectal dissection. Surg Endosc 22:1876–1881

    Article  PubMed  CAS  Google Scholar 

  60. Moles JJ, Connelly PE, Sarti EE et al (2009) Establishing a training program for residents in robotic surgery. Laryngoscope 119:1927–1931

    Article  PubMed  Google Scholar 

  61. Chandra V, Nehra D, Parent R et al (2010) A comparison of laparoscopic and robotic assisted suturing performance by experts and novices. Surgery 147:830–839

    Article  PubMed  Google Scholar 

  62. Di Lorenzo N, Coscarella G, Faraci L et al (2005) Robotic systems and surgical education. JSLS 9:3–12

    PubMed  Google Scholar 

  63. Arain NA, Dulan G, Hogg DC et al (2012) Comprehensive proficiency-based inanimate training for robotic surgery: reliability, feasibility, and educational benefit. Surg Endosc 26:2740–2745

    Article  PubMed  Google Scholar 

  64. Hoekstra AV, Morgan JM, Lurain JR et al (2009) Robotic surgery in gynecologic oncology: impact on fellowship training. Gynecol Oncol 114:168–172

    Article  PubMed  Google Scholar 

  65. Lee PS, Bland A, Valea FA et al (2009) Robotic-assisted laparoscopic gynecologic procedures in a fellowship training program. JSLS 13:467–472

    Article  PubMed  Google Scholar 

  66. Mirheydar H, Jones M, Koeneman KS et al (2009) Robotic surgical education: a collaborative approach to training postgraduate urologists and endourology fellows. JSLS 13:287–292

    PubMed  Google Scholar 

  67. Davis JW, Kamat A, Munsell M et al (2010) Initial experience of teaching robot-assisted radical prostatectomy to surgeons-in-training: can training be evaluated and standardized? BJU Int 105:1148–1154

    Article  PubMed  Google Scholar 

  68. Schachner T, Bonaros N, Wiedemann D et al (2009) Training surgeons to perform robotically assisted totally endoscopic coronary surgery. Ann Thorac Surg 88:523–527

    Article  PubMed  Google Scholar 

  69. Dulan G, Rege RV, Hogg DC et al (2012) Developing a comprehensive, proficiency-based training program for robotic surgery. Surgery 152:477–488

    Article  PubMed  Google Scholar 

  70. Badani KK, Hemal AK, Peabody JO et al (2006) Robotic radical prostatectomy: the Vattikuti Urology Institute training experience. World J Urol 24:148–151

    Article  PubMed  Google Scholar 

  71. Rashid HH, Leung YY, Rashid MJ et al (2006) Robotic surgical education: a systematic approach to training urology residents to perform robotic-assisted laparoscopic radical prostatectomy. Urology 68:75–79

    Article  PubMed  Google Scholar 

  72. Schroeck FR, de Sousa CA, Kalman RA et al (2008) Trainees do not negatively impact the institutional learning curve for robotic prostatectomy as characterized by operative time, estimated blood loss, and positive surgical margin rate. Urology 71:597–601

    Article  PubMed  Google Scholar 

  73. Thiel DD, Francis P, Heckman MG et al (2008) Prospective evaluation of factors affecting operating time in a residency/fellowship training program incorporating robot-assisted laparoscopic prostatectomy. J Endourol 22:1331–1338

    Article  PubMed  Google Scholar 

  74. Link BA, Nelson R, Josephson DY et al (2009) Training of urologic oncology fellows does not adversely impact outcomes of robot-assisted laparoscopic prostatectomy. J Endourol 23:301–305

    Article  PubMed  Google Scholar 

  75. Buchs NC, Pugin F, Bucher P et al (2012) Learning curve for robot-assisted Roux-en-Y gastric bypass. Surg Endosc 26:1116–1121

    Article  PubMed  Google Scholar 

  76. Buchs NC, Pugin F, Volonte F, et al (2013) Impact of robotic general surgery course on participants’ surgical practice. Surg Endosc Jan 5. [Epub ahead of print]

  77. Lucas SM, Gilley DA, Joshi SS et al (2011) Robotics training program: evaluation of the satisfaction and the factors that influence success of skills training in a resident robotics curriculum. J Endourol 25:1669–1674

    Article  PubMed  Google Scholar 

  78. Altunrende F, Autorino R, Haber GP, et al (2011) Immediate impact of a robotic kidney surgery course on attendees practice patterns. Int J Med Robot Feb 25. doi: 10.1002/rcs.384

  79. Gamboa AJ, Santos RT, Sargent ER et al (2009) Long-term impact of a robot assisted laparoscopic prostatectomy mini fellowship training program on postgraduate urological practice patterns. J Urol 181:778–782

    Article  PubMed  Google Scholar 

  80. Zorn KC, Gautam G, Shalhav AL et al (2009) Training, credentialing, proctoring and medicolegal risks of robotic urological surgery: recommendations of the Society of Urologic Robotic Surgeons. J Urol 182:1126–1132

    Article  PubMed  Google Scholar 

  81. Halvorsen FH, Elle OJ, Dalinin VV et al (2006) Virtual reality simulator training equals mechanical robotic training in improving robot-assisted basic suturing skills. Surg Endosc 20:1565–1569

    Article  PubMed  CAS  Google Scholar 

  82. Steinberg PL, Merguerian PA, Bihrle W et al (2008) The cost of learning robotic-assisted prostatectomy. Urology 72:1068–1072

    Article  PubMed  Google Scholar 

  83. Sarle R, Tewari A, Shrivastava A et al (2004) Surgical robotics and laparoscopic training drills. J Endourol 18:63–66

    Article  PubMed  Google Scholar 

  84. Shane MD, Pettitt BJ, Morgenthal CB et al (2008) Should surgical novices trade their retractors for joysticks? Videogame experience decreases the time needed to acquire surgical skills. Surg Endosc 22:1294–1297

    Article  PubMed  Google Scholar 

  85. Harper JD, Kaiser S, Ebrahimi K et al (2007) Prior video game exposure does not enhance robotic surgical performance. J Endourol 21:1207–1210

    Article  PubMed  Google Scholar 

  86. Hagen ME, Wagner OJ, Inan I et al (2009) Impact of IQ, computer-gaming skills, general dexterity, and laparoscopic experience on performance with the da Vinci surgical system. Int J Med Robot 5:327–331

    Article  PubMed  Google Scholar 

  87. Lynch J, Aughwane P, Hammond TM (2010) Video games and surgical ability: a literature review. J Surg Educ 67:184–189

    Article  PubMed  Google Scholar 

  88. Dulan G, Rege RV, Hogg DC et al (2012) Content and face validity of a comprehensive robotic skills training program for general surgery, urology, and gynecology. Am J Surg 203:535–539

    Article  PubMed  Google Scholar 

  89. Stefanidis D, Hope WW, Scott DJ (2011) Robotic suturing on the FLS model possesses construct validity, is less physically demanding, and is favored by more surgeons compared with laparoscopy. Surg Endosc 25:2141–2146

    Article  PubMed  Google Scholar 

  90. Judkins TN, Oleynikov D, Stergiou N (2009) Objective evaluation of expert and novice performance during robotic surgical training tasks. Surg Endosc 23:590–597

    Article  PubMed  Google Scholar 

  91. Dulan G, Rege RV, Hogg DC et al (2012) Proficiency-based training for robotic surgery: construct validity, workload, and expert levels for nine inanimate exercises. Surg Endosc 26:1516–1521

    Article  PubMed  Google Scholar 

  92. Derossis AM, Fried GM, Abrahamowicz M et al (1998) Development of a model for training and evaluation of laparoscopic skills. Am J Surg 175:482–487

    Article  PubMed  CAS  Google Scholar 

  93. Xeroulis G, Dubrowski A, Leslie K (2009) Simulation in laparoscopic surgery: a concurrent validity study for FLS. Surg Endosc 23:161–165

    Article  PubMed  Google Scholar 

  94. Lee JY, Mucksavage P, Sundaram CP et al (2011) Best practices for robotic surgery training and credentialing. J Urol 185:1191–1197

    Article  PubMed  Google Scholar 

  95. Do AT, Cabbad MF, Kerr A et al (2006) A warm-up laparoscopic exercise improves the subsequent laparoscopic performance of Ob-Gyn residents: a low-cost laparoscopic trainer. JSLS 10:297–301

    PubMed  Google Scholar 

  96. Kahol K, Satava RM, Ferrara J et al (2009) Effect of short-term pretrial practice on surgical proficiency in simulated environments: a randomized trial of the “preoperative warm-up” effect. J Am Coll Surg 208:255–268

    Article  PubMed  Google Scholar 

  97. Calatayud D, Arora S, Aggarwal R et al (2010) Warm-up in a virtual reality environment improves performance in the operating room. Ann Surg 251:1181–1185

    Article  PubMed  Google Scholar 

Download references

Conflict of interest

The authors have no financial disclosures to make.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nicolas C. Buchs.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Buchs, N.C., Pugin, F., Volonté, F. et al. Learning Tools and Simulation in Robotic Surgery: State of the Art. World J Surg 37, 2812–2819 (2013). https://doi.org/10.1007/s00268-013-2065-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00268-013-2065-y

Keywords

Navigation