Purpose Training in retrograde intrarenal surgery for the treatment of renal stone disease is a challenging task due to the unique complexity of the procedure. This study introduces a series of 3D printed models of upper urinary tract and stones designed to improve the training process. Methods Six different models of upper urinary tract were algorithmically isolated, digitally optimized and 3D printed from real-life cases. Soft and hard stones in different sizes were produced from 3D printed moulds. The models were fitted onto a commercially available part-task trainer and tested for retrograde intrarenal surgery. Results Each step of the procedure was simulated with extraordinary resemblance to real-life cases. The unique anatomical intricacy of each model and type of stones allowed us to reproduce surgeries of increasing difficulty. As the case-load required to achieve proficiency in retrograde intrarenal surgery is high, benchtop simulation could be integrated in training programs to reach good outcomes and low complication rates faster. Our models match incredible anatomical resemblance with low production cost and high reusability. Validation studies and objective skills assessment during simulations would allow comparison with other available benchtop trainers and the design of stepwise training programs. Conclusions 3D printing is gaining a significant importance in surgical training. Our 3D printed models of the upper urinary tract might represent a risk-free training option to hasten the achievement of proficiency in endourology.

Orecchia, L., Manfrin, D., Germani, S., Del Fabbro, D., Asimakopoulos, A.d., Finazzi Agrò, E., et al. (2021). Introducing 3D printed models of the upper urinary tract for high-fidelity simulation of retrograde intrarenal surgery. 3D PRINTING IN MEDICINE, 7(1), 15 [10.1186/s41205-021-00105-9].

Introducing 3D printed models of the upper urinary tract for high-fidelity simulation of retrograde intrarenal surgery

Finazzi Agrò, Enrico;Miano, Roberto
2021-06-07

Abstract

Purpose Training in retrograde intrarenal surgery for the treatment of renal stone disease is a challenging task due to the unique complexity of the procedure. This study introduces a series of 3D printed models of upper urinary tract and stones designed to improve the training process. Methods Six different models of upper urinary tract were algorithmically isolated, digitally optimized and 3D printed from real-life cases. Soft and hard stones in different sizes were produced from 3D printed moulds. The models were fitted onto a commercially available part-task trainer and tested for retrograde intrarenal surgery. Results Each step of the procedure was simulated with extraordinary resemblance to real-life cases. The unique anatomical intricacy of each model and type of stones allowed us to reproduce surgeries of increasing difficulty. As the case-load required to achieve proficiency in retrograde intrarenal surgery is high, benchtop simulation could be integrated in training programs to reach good outcomes and low complication rates faster. Our models match incredible anatomical resemblance with low production cost and high reusability. Validation studies and objective skills assessment during simulations would allow comparison with other available benchtop trainers and the design of stepwise training programs. Conclusions 3D printing is gaining a significant importance in surgical training. Our 3D printed models of the upper urinary tract might represent a risk-free training option to hasten the achievement of proficiency in endourology.
7-giu-2021
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore MED/24 - UROLOGIA
English
3D
Anatomy
Kidney
Lithotripsy
RIRS
Simulation
Training
Ureteroscopy
Urology
Orecchia, L., Manfrin, D., Germani, S., Del Fabbro, D., Asimakopoulos, A.d., Finazzi Agrò, E., et al. (2021). Introducing 3D printed models of the upper urinary tract for high-fidelity simulation of retrograde intrarenal surgery. 3D PRINTING IN MEDICINE, 7(1), 15 [10.1186/s41205-021-00105-9].
Orecchia, L; Manfrin, D; Germani, S; Del Fabbro, D; Asimakopoulos, Ad; Finazzi Agrò, E; Miano, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/286002
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