[Methods for training of robot-assisted radical prostatectomy]

Area of Science:

• Minimally Invasive Surgery
• Surgical Oncology
• Medical Education

Background:

• Robot-assisted radical prostatectomy (RARP) is a prevalent surgical treatment for prostate cancer.
• Significant technical differences exist between RARP and traditional open or laparoscopic radical prostatectomy (LRP).
• Current physician training methods for RARP are varied and their effectiveness is debated.

Purpose of the Study:

• To analyze existing RARP training methodologies.
• To identify the most effective RARP training model and its associated benefits and drawbacks.
• To propose a standardized framework for RARP surgeon and team training and certification.

Main Methods:

• A comprehensive literature review was conducted using PubMed, Web of Science, and Scopus databases.
• Keywords included: robot-assisted radical prostatectomy, training, learning curve, and virtual reality simulators.
• Data on various training models and their outcomes were synthesized.

Main Results:

• Surgeons typically require 18-45 procedures to reach the RARP learning curve plateau.
• Parallel training, pre-operative warm-up, and virtual reality (VR) simulators can accelerate the learning curve.
• Multiple RARP training models are documented in the literature.

Conclusions:

• The lack of standardized learning curve evaluation criteria hinders its use as a measure of surgeon proficiency.
• New training methods are essential for effective RARP surgeon development.
• An optimal training program involves VR simulation, mentored real-world practice, and comprehensive surgical team education.