A High-Fidelity Artificial Urological System for the Quantitative Assessment of Endoscopic Skills

Author:

Kim Do Yeon,Tan Xiangzhou,Jeong MoonkwangORCID,Li Dandan,Miernik ArkadiuszORCID,Qiu TianORCID

Abstract

Minimally-invasive surgery is rapidly growing and has become a standard approach for many operations. However, it requires intensive practice to achieve competency. The current training often relies on animal organ models or physical organ phantoms, which do not offer realistic surgical scenes or useful real-time feedback for surgeons to improve their skills. Furthermore, the objective quantitative assessment of endoscopic skills is also lacking. Here, we report a high-fidelity artificial urological system that allows realistic simulation of endourological procedures and offers a quantitative assessment of the surgical performance. The physical organ model was fabricated by 3D printing and two-step polymer molding with the use of human CT data. The system resembles the human upper urinary tract with a high-resolution anatomical shape and vascular patterns. During surgical simulation, endoscopic videos are acquired and analyzed to quantitatively evaluate performance skills by a customized computer algorithm. Experimental results show significant differences in the performance between professional surgeons and trainees. The surgical simulator offers a unique chance to train endourological procedures in a realistic and safe environment, and it may also lead to a quantitative standard to evaluate endoscopic skills.

Funder

Cyber Valley Research Fund

Vector Foundation

University of Freiburg Medical Centre

Publisher

MDPI AG

Subject

Biomedical Engineering,Biomaterials

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Simulation training in urology;Current Opinion in Urology;2023-11-01

2. Recent Approaches in Laparoscopic Training Phantom Development—A Review;2023 IEEE 21st Jubilee International Symposium on Intelligent Systems and Informatics (SISY);2023-09-21

3. A sensorized modular training platform to reduce vascular damage in endovascular surgery;International Journal of Computer Assisted Radiology and Surgery;2023-05-17

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