A novel ex vivo trainer for robotic vesicourethral anastomosis
Robotic surgical skill development is central to training in urology as well as other surgical disciplines. Vesicourethral anastomosis (VUA) in robotic prostatectomy is a challenging task for novices due to delicate tissue and difficult suturing angles. Commercially available, realistic training models are limited. Here, we describe the development and validation of a 3D-printed model of the VUA for ex vivo training using the da Vinci Surgical System. Models of the bladder and urethra were created using 3D-printing technology based on estimations of average in vivo anatomy. 10 surgical residents without prior robotics training were enrolled in the study: 5 residents received structured virtual reality (VR) training on the da Vinci Skills Simulator (“trained”), while the other 5 did not (“untrained”). 4 faculty robotic surgeons trained in robotic urologic oncology (“experts”) were also enrolled. Mean (range) completion percentage was 20% (10–30%), 54% (40–70%), and 96% (85–100%) by the untrained, trained, and expert groups, respectively. Anastomosis integrity was rated as excellent (as opposed to moderate or poor) in 40%, 60%, and 100% of untrained, trained, and expert groups, respectively. Face validity (realism) was rated as 8 of 10 on average by the expert surgeons, each of whom rated the model as a superior training tool to digital VR trainers. Content validity (usefulness) was rated as 10 of 10 by all participants. This is the first reported 3D-printed ex vivo trainer for VUA in robotic prostatectomy validated for use in robotic simulation. The addition of 3D-printed ex vivo training to existing digital simulation technologies may augment and improve robotic surgical education in the future.
KeywordsRobotic surgery Surgical education Simulation Surgical skills training Prostatectomy
This study was enabled by use of a da Vinci Skills Simulator (Intuitive, Sunnyvale, CA) provided to the authors’ institution via the “Intuitive Surgical Standalone Simulator program.”
Compliance with ethical standards
Conflict of interest
Authors Kevin Shee, Kevin Koo, Xiaotian Wu, Fady M. Ghali, Ryan J. Halter, and Elias S Hyams declare that they have no conflict of interest.
Ethics committee approval was received for this study from the ethics committee of the Institutional Review Board (IRB).
Written informed consent was obtained from patients who participated in this study.
- 2.Bekelman JE, Rumble RB, Chen RC, Pisansky TM, Finelli A, Feifer A, Nguyen PL, Loblaw DA, Tagawa ST, Gillessen S, Morgan TM, Liu G, Vapiwala N, Haluschak JJ, Stephenson A, Touijer K, Kungel T, Freedland SJ (2018) Clinically Localized Prostate Cancer: ASCO Clinical Practice Guideline Endorsement of an American Urological Association/American Society for Radiation Oncology/Society of Urologic Oncology Guideline. J Clin Oncol. https://doi.org/10.1200/JCO.18.00606 Google Scholar
- 4.Trinh QD, Sammon J, Sun M, Ravi P, Ghani KR, Bianchi M, Jeong W, Shariat SF, Hansen J, Schmitges J, Jeldres C, Rogers CG, Peabody JO, Montorsi F, Menon M, Karakiewicz PI (2012) Perioperative outcomes of robot-assisted radical prostatectomy compared with open radical prostatectomy: results from the nationwide inpatient sample. Eur Urol 61(4):679–685. https://doi.org/10.1016/j.eururo.2011.12.027 CrossRefGoogle Scholar
- 5.Sooriakumaran P, Srivastava A, Shariat SF, Stricker PD, Ahlering T, Eden CG, Wiklund PN, Sanchez-Salas R, Mottrie A, Lee D, Neal DE, Ghavamian R, Nyirady P, Nilsson A, Carlsson S, Xylinas E, Loidl W, Seitz C, Schramek P, Roehrborn C, Cathelineau X, Skarecky D, Shaw G, Warren A, Delprado WJ, Haynes AM, Steyerberg E, Roobol MJ, Tewari AK (2014) A multinational, multi-institutional study comparing positive surgical margin rates among 22393 open, laparoscopic, and robot-assisted radical prostatectomy patients. Eur Urol 66(3):450–456. https://doi.org/10.1016/j.eururo.2013.11.018 CrossRefGoogle Scholar
- 13.Yamada T, Osako M, Uchimuro T, Yoon R, Morikawa T, Sugimoto M, Suda H, Shimizu H (2017) Three-dimensional printing of life-like models for simulation and training of minimally invasive cardiac surgery. Innovations (Phila) 12(6):459–465. https://doi.org/10.1097/IMI.0000000000000423 CrossRefGoogle Scholar
- 15.Cheung CL, Looi T, Lendvay TS, Drake JM, Farhat WA (2014) Use of 3-dimensional printing technology and silicone modeling in surgical simulation: development and face validation in pediatric laparoscopic pyeloplasty. J Surg Educ 71(5):762–767. https://doi.org/10.1016/j.jsurg.2014.03.001 CrossRefGoogle Scholar
- 16.Hickling DR, Sun TT, Wu XR (2015) Anatomy and physiology of the urinary tract: relation to host defense and microbial infection. Microbiol Spectr. https://doi.org/10.1128/microbiolspec.UTI-0016-2012 Google Scholar
- 19.Kang SG, Cho S, Kang SH, Haidar AM, Samavedi S, Palmer KJ, Patel VR, Cheon J (2014) The Tube 3 module designed for practicing vesicourethral anastomosis in a virtual reality robotic simulator: determination of face, content, and construct validity. Urology 84(2):345–350. https://doi.org/10.1016/j.urology.2014.05.005 CrossRefGoogle Scholar
- 20.Chowriappa A, Raza SJ, Fazili A, Field E, Malito C, Samarasekera D, Shi Y, Ahmed K, Wilding G, Kaouk J, Eun DD, Ghazi A, Peabody JO, Kesavadas T, Mohler JL, Guru KA (2015) Augmented-reality-based skills training for robot-assisted urethrovesical anastomosis: a multi-institutional randomised controlled trial. BJU Int 115(2):336–345. https://doi.org/10.1111/bju.12704 CrossRefGoogle Scholar
- 23.Ahmed K, Khan R, Mottrie A, Lovegrove C, Abaza R, Ahlawat R, Ahlering T, Ahlgren G, Artibani W, Barret E, Cathelineau X, Challacombe B, Coloby P, Khan MS, Hubert J, Michel MS, Montorsi F, Murphy D, Palou J, Patel V, Piechaud PT, Van Poppel H, Rischmann P, Sanchez-Salas R, Siemer S, Stoeckle M, Stolzenburg JU, Terrier JE, Thuroff JW, Vaessen C, Van Der Poel HG, Van Cleynenbreugel B, Volpe A, Wagner C, Wiklund P, Wilson T, Wirth M, Witt J, Dasgupta P (2015) Development of a standardised training curriculum for robotic surgery: a consensus statement from an international multidisciplinary group of experts. BJU Int 116(1):93–101. https://doi.org/10.1111/bju.12974 CrossRefGoogle Scholar
- 30.Oishi M, Fukuda M, Yajima N, Yoshida K, Takahashi M, Hiraishi T, Takao T, Saito A, Fujii Y (2013) Interactive presurgical simulation applying advanced 3D imaging and modeling techniques for skull base and deep tumors. J Neurosurg 119(1):94–105. https://doi.org/10.3171/2013.3.JNS121109 CrossRefGoogle Scholar