Simulation has become central in flexible ureteroscopy training and research; however, the lack of standardized and reproducible models limits objective performance assessment. We aimed to evaluate the reliability and reproducibility of laser lithotripsy using morphology-specific artificial stones (AS) within a standardized ex vivo platform and to assess whether the model could detect operator-dependent differences in lithotripsy performance.
This study was conducted using AS derived from 3D-printed images of human kidney stones. Six stone volume categories (F1-F6; 250-1750 mm³) were reproduced using BegoStone® mixture with ratio of 15:4. Novice and expert surgeons performed in vitro laser lithotripsy under standardized settings. Performance metrics included ablation efficiency (AE) (mm³/J), energy consumption (J/mm³), lasing time consumption (s/mm³), and laser ablation rate (AR) (mm³/min). Results were compared with six matched in vivo reference cases. Adjusted linear models were used to evaluate the effect of operator experience.
In vivo lithotripsy showed a mean laser-on time of 44.9 ± 17.0 minutes, total energy delivery of 32.35 ± 12.2 kJ, AE of 0.03 ± 0.00 mm³/J, and laser AR of 21.9 ± 1.78 mm³/min, with complete stone clearance in all cases. AS experiments demonstrated shorter laser-on-time than in vivo procedures (37.4-38.3 vs 44.9 minutes, p < 0.01), lower energy delivery (26.9-27.9 vs 32.35 kJ, p < 0.01), higher AE (0.04 vs 0.03 mm³/J, p < 0.01), and higher laser AR (26.0-26.8 vs 21.9 mm³/min, p < 0.01). In unadjusted aggregated comparison, expert surgeons showed higher performances than novices, although the differences did not reach statistical significance (p > 0.05). Adjusted analysis showed that operator experience was significantly associated with both better AE and AR (p < 0.01).
The standardized ex vivo platform, combining a validated simulation model with 3D-printed morphology-specific AS, provides a reliable and reproducible environment for evaluating laser lithotripsy performance, supporting the objective metrics assessment.
Journal of endourology. 2026 Aug 01 [Epub ahead of print]
Federico Zorzi, Marie Chicaud, Quentin Jacquemin, Imade Koutiri, Carlos Gonzalez-Gonzalez, Pietro Scilipoti, Nicola Nannola, Corine Dupuy, Stessy Kutchukian, Stefano Moretto, Laurent Berthe, Cyrille Guillot-Tantay, Olivier Traxer, Steeve Doizi, Frederic Panthier
GRC20-Endolase lab, APHP Hôpital Tenon, Sorbonne University, Paris, France., UMR 8006 CNRS-Arts et Métiers ParisTech, PIMM, Paris, France., Service d'urologie et de transplantation rénale, Hôpital Foch, Suresnes, France.