Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Mar 13;22(4):26.
doi: 10.1007/s11934-021-01043-z.

Innovations in Urologic Surgical Training

Runzhuo Ma  1 , Sharath Reddy  1 , Erik B Vanstrum  1 , Andrew J Hung  2
Affiliations
Review

Innovations in Urologic Surgical Training

Runzhuo Ma et al. Curr Urol Rep. .

Abstract

Purpose of review: This review aims to summarize innovations in urologic surgical training in the past 5 years.

Recent findings: Many assessment tools have been developed to objectively evaluate surgical skills and provide structured feedback to urologic trainees. A variety of simulation modalities (i.e., virtual/augmented reality, dry-lab, animal, and cadaver) have been utilized to facilitate the acquisition of surgical skills outside the high-stakes operating room environment. Three-dimensional printing has been used to create high-fidelity, immersive dry-lab models at a reasonable cost. Non-technical skills such as teamwork and decision-making have gained more attention. Structured surgical video review has been shown to improve surgical skills not only for trainees but also for qualified surgeons. Research and development in urologic surgical training has been active in the past 5 years. Despite these advances, there is still an unfulfilled need for a standardized surgical training program covering both technical and non-technical skills.

Keywords: Assessment; Robotic surgery; Simulation; Surgical education; Surgical training; Urology.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest

Andrew J. Hung has financial disclosures with Quantgene, Inc. (consultant), Mimic Technologies, Inc. (consultant), and Johnson and Johnson, Inc. (consultant)

References

    1. Hung AJ, Chen J, Ghodoussipour S, Oh PJ, Liu Z, Nguyen J, et al. A deep-learning model using automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy. BJU Int 2019;124:487–95. doi:10.1111/bju.14735. - DOI - PMC - PubMed
    1. Goldenberg MG, Goldenberg L, Grantcharov TP. Surgeon Performance Predicts Early Continence After Robot-Assisted Radical Prostatectomy. J Endourol 2017;31:858–63. doi:10.1089/end.2017.0284. - DOI - PubMed
    1. Aydin A, Raison N, Khan MS, Dasgupta P, Ahmed K. Simulation-based training and assessment in urological surgery. Nat Rev Urol 2016;13:503–19. doi:10.1038/nrurol.2016.147. - DOI - PubMed

    2. •• A comprehensive review covering virtual/augmented reality, dry-lab, animal and cadaveric simulation models of urologic surgical training before 2016.

    1. McDougall EM. Validation of surgical simulators. J Endourol 2007;21:244–7. doi: 10.1089/end.2007.9985. - DOI - PubMed
    1. Goldenberg M, Lee JY. Surgical Education, Simulation, and Simulators-Updating the Concept of Validity. Curr Urol Rep 2018; 19: 52. doi:10.1007/s11934-018-0799-7 - DOI - PubMed

LinkOut - more resources