IMR Press / EJGO / Volume 42 / Issue 3 / DOI: 10.31083/j.ejgo.2021.03.2295
Open Access Original Research
An innovative tissue model for robot-assisted radical hysterectomy and pelvic lymphadenectomy
Show Less
1 Department of Obstetrics and Gynecology Toyohashi Municipal Hospital, 441-8570 Toyohashi, Japan
Eur. J. Gynaecol. Oncol. 2021 , 42(3), 482–487;
Submitted: 2 October 2020 | Revised: 1 February 2021 | Accepted: 2 February 2021 | Published: 15 June 2021

Objective: The purpose of this study was to evaluate a new tissue model and to conduct a questionnaire survey to assess its feasibility for robot-assisted radical hysterectomy, colpotomy, and pelvic lymph node dissection training. Methods: Sixteen gynecologists (12 males, 4 females; mean age: 47.1 years; all attending doctors with an average experience of 9.3 robot-assisted surgeries) were trained in robot-assisted radical hysterectomy, colpotomy, and pelvic lymphadenectomy using a new uterine and pelvic lymph node model (mainly composed of PVA) from Fasotec Inc. The participants were trained by the author using a dual console. They performed all surgical procedures following the author’s instructions. The time required for completion of the surgeries was measured. The surgical skills of the participants were evaluated by the author using the operative performance rating scale recommended by the American College of Surgeons. After training, the participants answered a questionnaire for the assessment of the model and the training using a 5-point Likert scale. Results: We found that the mean time taken for radical hysterectomy, colpotomy, and pelvic lymphadenectomy was 57.3 minutes (range: 45–75 minutes), 12.2 minutes (range: 8–17 minutes), and 60.7 minutes (range: 45–70 minutes), respectively; the total time taken was 136.5 minutes (range: 98–162 minutes). The questionnaire survey revealed that this model followed pelvic anatomy and was practically trainable. Conclusion: This is the first report of a tissue model relevant to the uterus and the pelvic lymph nodes, and robot-assisted training using this model was considered effective.

Robotic training
Tissue model
Radical hysterectomy
Pelvic lymphadenectomy
Uterine cervical cancer
Fig. 1.
Back to top