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Current Urology Reports

, 20:81 | Cite as

Novel Education and Simulation Tools in Urologic Training

  • Brandon S. Childs
  • Marc D. Manganiello
  • Ruslan KoretsEmail author
Education (G Badalato, Section Editor)
  • 43 Downloads
Part of the following topical collections:
  1. Topical Collection on Education

Abstract

Purpose of Review

Postgraduate medical training has evolved considerably from an emphasis on hands-on, autonomous learning to a paradigm where simulation technologies are used to introduce and augment certain skill sets. This review is intended to provide an update on surgical simulators and tools for urological trainee education.

Recent Findings

We provide an overview of simulation platforms for robotics, endoscopy, and laparoscopic practice and training. In general, these simulators provide face, content, and construct validity. Various educational and evaluation tools have been adopted.

Summary

Simulation platforms have been developed for technical and non-technical surgical skills, educational bootcamps, and tools for evaluation and feedback. While trainees find the opportunity to practice their skills beneficial, there may be difficulty with access due to cost and availability. Additionally, there is a need for more objective metrics demonstrating improvement in skill or patient outcome.

Keywords

Simulation Virtual reality Surgical skills training Surgical education Educational apps 

Notes

Compliance with Ethical Standards

Conflict of Interest

Brandon S. Childs, Marc D. Manganiello, and Ruslan Korets each declare no potential conflicts of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    • Abboudi H, Khan MS, Aboumarzouk O, Guru KA, Challacombe B, Dasgupta P, et al. Current status of validation for robotic surgery simulators–a systematic review. BJU Int. 2013;111(2):194–205.  https://doi.org/10.1111/j.1464-410X.2012.11270.x. Systematic review of validation within the field of robotic simulators. CrossRefPubMedGoogle Scholar
  2. 2.
    •• MacCraith E, Forde JC, Davis NF. Robotic simulation training for urological trainees: a comprehensive review on cost, merits and challenges. J Robot Surg. 2019;13(3):371–7.  https://doi.org/10.1007/s11701-019-00934-1 Complete review of all current available robotic simulators, their cost, and advantages/disadvantages. CrossRefPubMedGoogle Scholar
  3. 3.
    Hertz AM, George EI, Vaccaro CM, Brand TC. Head-to-head comparison of three virtual-reality robotic surgery simulators. JSLS. 2018;22(1):e2017.00081.  https://doi.org/10.4293/JSLS.2017.00081.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    • Hoogenes J, Wong N, Al-Harbi B, Kim KS, Vij S, Bolognone E, et al. A randomized comparison of 2 robotic virtual reality simulators and evaluation of trainees’ skills transfer to a simulated robotic urethrovesical anastomosis task. Urology. 2018;111:110–5.  https://doi.org/10.1016/j.urology.2017.09.023. dVSSS trainer led to higher GEARS and RACE scores vs. dV-T for performance of the urethrovesical anastomosis task in junior trainees but not seniors. CrossRefPubMedGoogle Scholar
  5. 5.
    McDonough P, Peterson A, Brand T. Initial validation of the ProMIS surgical simulator as an objective measure of robotic task performance. J Urol. 2010;183(4):e515.Google Scholar
  6. 6.
    Jonsson MN, Mahmood M, Askerud T, Hellborg H, Ramel S, Wiklund NP, et al. ProMIS™ can serve as a da Vinci® simulator—a construct validity study. J Endourol. 2011;25(2):345–50.  https://doi.org/10.1089/end.2010.0220.CrossRefPubMedGoogle Scholar
  7. 7.
    Gavazzi A, Bahsoun AN, Van Haute W, Ahmed K, Elhage O, Jaye P, et al. Face, content and construct validity of a virtual reality simulator for robotic surgery (SEP Robot). Ann R Coll Surg Engl. 2011;93(2):152–6.  https://doi.org/10.1308/003588411X12851639108358.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Seixas-Mikelus SA, Kesavadas T, Srimathveeravalli G, Chandrasekhar R, Wilding GE, Guru KA. Face validation of a novel robotic surgical simulator. Urology. 2010;76(2):357–60.  https://doi.org/10.1016/j.urology.2009.11.069.CrossRefPubMedGoogle Scholar
  9. 9.
    Kamel M, Eltahawy EA, Warford R, Thrush CR, Noureldin YA. Simulation-based training in urology residency programmes in the USA: results of a nationwide survey. Arab J Urol. 2018;16(4):446–52.  https://doi.org/10.1016/j.aju.2018.06.003.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Van der Meijden OA, Schijven MP. The value of haptic feedback in conventional and robot-assisted minimal invasive surgery and virtual reality training: a current review. Surg Endosc. 2009;23(6):1180–90.  https://doi.org/10.1007/s00464-008-0298-x.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    • Moglia A, Ferrari V, Morelli L, Ferrari M, Mosca F, Cuschieri A. A systematic review of virtual reality simulators for robot-assisted surgery. Eur Urol. 2016;69(6):1065–80.  https://doi.org/10.1016/j.eururo.2015.09.021. Systematic review concluding that there is an urgent need for a large, multicenter, randomized controlled trial to assess the transferability of skills into the operating room. CrossRefPubMedGoogle Scholar
  12. 12.
    • Nagendran M, Toon CD, Davidson BR, Gurusamy KS. Laparoscopic surgical box model training for surgical trainees with no prior laparoscopic experience. Cochrane Database Syst Rev. 2014;(1):CD010479.  https://doi.org/10.1002/14651858.CD010479.pub2.
  13. 13.
    Aslam A, Nason GJ, Giri SK. Homemade laparoscopic surgical simulator: a cost-effective solution to the challenge of acquiring laparoscopic skills? Ir J Med Sci. 2016;185(4):791–6. Cochrane review concluded that laparoscopic box trainers (box, animal, and cadaveric models) appear to improve the overall skill of trainees with no prior experience. CrossRefGoogle Scholar
  14. 14.
    Makiyama K, Yamanaka H, Ueno D, Ohsaka K, Sano F, Nakaigawa N, et al. Validation of a patient-specific simulator for laparoscopic renal surgery. Int J Urol. 2015;22(6):572–6.  https://doi.org/10.1111/iju.12737.CrossRefPubMedGoogle Scholar
  15. 15.
    Inoue T, Okada S, Hamamoto S, Matsuda T. New advanced bench model for flexible ureteroscopic training: the smart simulator. J Endourol. 2018;32(1):22–7.CrossRefGoogle Scholar
  16. 16.
    de la Rosette JJ, Laguna MP, Rassweiler JJ, Conort P. Training in percutaneous nephrolithotomy—a critical review. Eur Urol. 2008;54(5):994–1001.  https://doi.org/10.1016/j.eururo.2008.03.052.CrossRefPubMedGoogle Scholar
  17. 17.
    • Ghazi A, Campbell T, Melnyk R, Feng C, Andrusco A, Stone J, et al. Validation of a full-immersion simulation platform for percutaneous nephrolithotomy using three-dimensional printing technology. J Endourol. 2017;31(12):1314–20.  https://doi.org/10.1089/end.2017.0366. Validated, 3-D print model for PCNL for full immersion simulation. CrossRefPubMedGoogle Scholar
  18. 18.
    Parkhomenko E, O'Leary M, Safiullah S, Walia S, Owyong M, Lin C, et al. Pilot assessment of immersive virtual reality renal models as an educational and preoperative planning tool for percutaneous nephrolithotomy. J Endourol. 2019;33(4):283–8.  https://doi.org/10.1089/end.2018.0626.CrossRefPubMedGoogle Scholar
  19. 19.
    •• Khan R, Aydin A, Khan MS, Dasgupta P, Ahmed K. Simulation-based training for prostate surgery. BJU Int. 2015;116(4):665–74.  https://doi.org/10.1111/bju.12721 Thorough review of all simulators available for prostate surgery. CrossRefPubMedGoogle Scholar
  20. 20.
    Hudak SJ, Landt CL, Hernandez J, Soderdahl DW. External validation of a virtual reality transurethral resection of the prostate simulator. J Urol. 2010;184(5):2018–22.  https://doi.org/10.1016/j.juro.2010.06.141.CrossRefPubMedGoogle Scholar
  21. 21.
    Aydin A, Muir GH, Khan MS, Dasgupta P, Ahmed K. Validation of the GreenLight Simulator and development of a training curriculum for GreenLight Laser Prostatectomy. Eur Urol Suppl. 2014;13(1):e874-b.CrossRefGoogle Scholar
  22. 22.
    Kuronen-Stewart C, Ahmed K, Aydin A, Cynk M, Miller P, Dasgupta P, et al. MP14-17 Assessment of face, construct and content validity of a novel virtual reality simulator for holmium laser enucleation of the prostate. Urology. 2015;86(3):639–46.  https://doi.org/10.1016/j.urology.2015.06.008.CrossRefPubMedGoogle Scholar
  23. 23.
    de Vries AH, van Genugten HG, Hendrikx AJ, Koldewijn EL, Schout BM, Tjiam IM, et al. The Simbla TURBT simulator in urological residency training: from needs analysis to validation. J Endourol. 2016;30(5):580–7.  https://doi.org/10.1089/end.2015.0723.CrossRefPubMedGoogle Scholar
  24. 24.
    Fiard G, Selmi SY, Promayon E, Vadcard L, Descotes JL, Troccaz J. Initial validation of a virtual-reality learning environment for prostate biopsies: realism matters! J Endourol. 2014;28(4):453–8.  https://doi.org/10.1089/end.2013.0454.CrossRefPubMedGoogle Scholar
  25. 25.
    • Rowley K, Pruthi D, Al-Bayati O, Basler J, Liss MA. Novel use of household items in open and robotic surgical skills resident education. Adv Urol. 2019;2019:5794957.  https://doi.org/10.1155/2019/5794957. Low-fidelity, inexpensive, surgical simulators which are easily reproducible at home have been shown to improve open surgical skills. CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Singal A, Halverson A, Rooney DM, Davis LM, Kielb SJ. A validated low-cost training model for suprapubic catheter insertion. Urology. 2015;85(1):23–6.  https://doi.org/10.1016/j.urology.2014.08.024.CrossRefPubMedGoogle Scholar
  27. 27.
    Lentz AC, Rodríguez D, Davis LG, Apoj M, Kerfoot BP, Perito P, et al. Simulation training in penile implant surgery: assessment of surgical confidence and knowledge with cadaveric laboratory training. Sex Med. 2018;6(4):332–8.  https://doi.org/10.1016/j.esxm.2018.09.001.CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Bertolo R, Garisto J, Dagenais J, Sagalovich D, Kaouk JH. Single session of robotic human cadaver training: the immediate impact on urology residents in a teaching hospital. J Laparoendosc Adv Surg Tech A. 2018;28(10):1157–62.  https://doi.org/10.1089/lap.2018.0109.CrossRefPubMedGoogle Scholar
  29. 29.
    Lin C, Gao J, Zheng H, Zhao J, Yang H, Zheng Y, et al. When to introduce three-dimensional visualization technology into surgical residency: a randomized controlled trial. J Med Syst. 2019;43(3):71.  https://doi.org/10.1007/s10916-019-1157-0.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Porpiglia F, Bertolo R, Checcucci E, Amparore D, Autorino R, Dasgupta P, et al. Development and validation of 3D printed virtual models for robot-assisted radical prostatectomy and partial nephrectomy: urologists’ and patients’ perception. World J Urol. 2018;36(2):201–7.  https://doi.org/10.1007/s00345-017-2126-1.CrossRefPubMedGoogle Scholar
  31. 31.
    Shee K, Koo K, Wu X, Ghali FM, Halter RJ, Hyams ES. A novel ex vivo trainer for robotic vesicourethral anastomosis. J Robot Surg. 2019:1–7.  https://doi.org/10.1007/s11701-019-00926-1.
  32. 32.
    • Rodgers A, Trinchieri A, Ather MH, Buchholz N. Vision for the future on urolithiasis: research, management, education and training—some personal views. Urolithiasis. 2018:1–3.  https://doi.org/10.1007/s00240-018-1086-2. Discusses the benefits of augmented reality in the urological field, in particular to its benefits related to percutaneous nephrolithotomy. CrossRefGoogle Scholar
  33. 33.
    • Bertolo R, Hung A, Porpiglia F, Bove P, Schleicher M, Dasgupta P. Systematic review of augmented reality in urological interventions: the evidences of an impact on surgical outcomes are yet to come. World J Urol. 2019.  https://doi.org/10.1007/s00345-019-02711-z. Limited benefits of augmented reality currently in comparison with conventional surgery.
  34. 34.
    • Brook NR, Dell’Oglio P, Barod R, Collins J, Mottrie A. Comprehensive training in robotic surgery. Curr Opin Urol. 2019;29(1):1–9.  https://doi.org/10.1097/MOU.0000000000000566. Discusses the establishment of robotic cirricula for training of novice surgeons. CrossRefPubMedGoogle Scholar
  35. 35.
    Volpe A, Ahmed K, Dasgupta P, Ficarra V, Novara G, van der Poel H, et al. Pilot validation study of the European Association of Urology robotic training curriculum. Eur Urol. 2015;68(2):292–9.  https://doi.org/10.1016/j.eururo.2014.10.025.CrossRefPubMedGoogle Scholar
  36. 36.
    Hanchanale V, Kailavasan M, Rajpal S, Koenig P, Yiasemidou M, Palit V, et al. Impact of urology simulation boot camp in improving endoscopic instrument knowledge. BMJ Simulation and Technology Enhanced Learning. 2018:bmjstel-2018.Google Scholar
  37. 37.
    Kailavasan M, Hanchanale V, Rajpal S, Morley R, Mcllhenny C, Somani B, et al. A method to evaluate trainee progression during simulation training at the Urology Simulation Boot Camp (USBC) course. J Surg Educ. 2019;76(1):215–22.  https://doi.org/10.1016/j.jsurg.2018.06.020.CrossRefPubMedGoogle Scholar
  38. 38.
    Ahmed K, Aydin A, Dasgupta P, Khan MS, McCabe JE. A novel cadaveric simulation program in urology. J Surg Educ. 2015;72(4):556–65.  https://doi.org/10.1016/j.jsurg.2015.01.005.CrossRefPubMedGoogle Scholar
  39. 39.
    Somasundram K, Spence H, Colquhoun AJ, Mcilhenny C, Biyani CS, Jain S. Simulation in urology to train non-technical skills in ward rounds. BJU Int. 2018;122(4):705–12.  https://doi.org/10.1111/bju.14402.CrossRefPubMedGoogle Scholar
  40. 40.
    Goh AC, Goldfarb DW, Sander JC, Miles BJ, Dunkin BJ. Global evaluative assessment of robotic skills: validation of a clinical assessment tool to measure robotic surgical skills. J Urol. 2012;187(1):247–52.  https://doi.org/10.1016/j.juro.2011.09.032.CrossRefPubMedGoogle Scholar
  41. 41.
    Van Hove PD, Tuijthof GJ, Verdaasdonk EG, Stassen LP, Dankelman J. Objective assessment of technical surgical skills. Br J Surg. 2010;97(7):972–87.CrossRefGoogle Scholar
  42. 42.
    Martin JA, Regehr G, Reznick R, Macrae H, Murnaghan J, Hutchison C, et al. Objective structured assessment of technical skill (OSATS) for surgical residents. Br J Surg. 1997;84(2):273–8.CrossRefGoogle Scholar
  43. 43.
    Handelman A, Schnaider S, Schwartz-Ossad A, Barkan R, Tepper R. Computerized model for objectively evaluating cutting performance using a laparoscopic box trainer simulator. Surg Endosc. 2019;33(9):2941–50.  https://doi.org/10.1007/s00464-018-6598-x.CrossRefPubMedGoogle Scholar
  44. 44.
    • Hung AJ, Chen J, Jarc A, Hatcher D, Djaladat H, Gill IS. Development and validation of objective performance metrics for robot-assisted radical prostatectomy: a pilot study. J Urol. 2018;199(1):296–304.  https://doi.org/10.1016/j.juro.2017.07.081. The establishment of automated performance metrics within the field of urology and specifically radical robotic-assisted prostatectomy. CrossRefPubMedGoogle Scholar
  45. 45.
    Chen J, Oh PJ, Cheng N, Shah A, Montez J, Jarc A, et al. Use of automated performance metrics to measure surgeon performance during robotic vesicourethral anastomosis and methodical development of a training tutorial. J Urol. 2018;200(4):895–902.  https://doi.org/10.1016/j.juro.2018.05.080.CrossRefPubMedGoogle Scholar
  46. 46.
    Kim SS, Blankstein U, Ordon M, Pace KT, Honey RJ, Lee JY, et al. Evaluation of optimal timing of expert feedback in a simulated flexible ureteroscopy course. J Endourol. 2019;33(6):463–7.  https://doi.org/10.1089/end.2018.0732.CrossRefPubMedGoogle Scholar
  47. 47.
    •• Sweet R. Taskforce Update: PGY-1 Curriculum Education Tools. [online] Sauweb.org. 2019. https://sauweb.org/docs/taskforces/pgy-1-curriculum-education-tools.aspx. Accessed 12 Jun 2019. A taskforce was created by the Society of Academic Urologists in order to aid in the establishment of a standardized curriculum for urology residents.
  48. 48.
    Manganiello M, Haleblian G, Canes D, Chang P, Wagner A, Korets R. Multi-institutional pilot evaluation of an online feedback platform for surgical skill acquisition. New England Section of American Urological Association Annual Meeting. Montreal CA 2017.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Brandon S. Childs
    • 1
  • Marc D. Manganiello
    • 1
  • Ruslan Korets
    • 2
    Email author
  1. 1.Department of UrologyLahey Hospital and Medical CenterBurlingtonUSA
  2. 2.Division of Urology, Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonUSA

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