First Prize: A Phantom Model as a Teaching Modality for Laparoscopic Partial Nephrectomy

Abstract

Purpose:

To evaluate a materials model for laparoscopic ultrasound identification and partial nephrectomy of kidney tumors.

Methods:

Five urology fellows performed laparoscopic ultrasonography (LUS) examination of the tumor model, and the time for identification was recorded. After identifying the tumor, they performed a laparoscopic partial nephrectomy using the target tumor with measurement of operative parameters. They completed a questionnaire and rated the quality of the renal tumor model on a 5-point Likert scale.

Results:

The participants were able to identify 49 tumors by LUS (98%). The mean time to identify the renal tumors by LUS was 1.12 minutes±0.93 standard deviation (SD). A partial nephrectomy was successfully completed on 49 tumor models (98%). The mean resection time was 7.69 minutes±3.8 SD. All of the participants considered that this model was helpful in the practice of LPN. The fellows would recommend this model as a teaching tool for residents/fellows to perform tumor imaging by LUS and for practicing LPN in a simulated environment.

Conclusion:

We have developed a unique model that simulates small kidney tumors that can be used for training surgeons in the clinical skills of laparoscopic partial nephrectomy.