Three Dimensional Printing Technology Used to Create a High-Fidelity Ureteroscopy Simulator: Development and Validity Assessment (Rein-3D-Print-UroCCR-39).

OBJECTIVE: To create and assess the validity of a high-fidelity, three dimensional (3D) printed, flexible ureteroscopy simulator resulting from a real case. METHODS: A patient's CT scan was segmented to obtain a 3D model in .stl format, including the urinary bladder, ureter and renal cavities. The file was printed and a kidney stone was introduced into the cavities. The simulated surgery consisted of monobloc stone extraction. Nineteen participants split into 3 groups according to their level (6 medical students, 7 residents and 6 urology fellows) performed the procedure twice at a 1-month interval. They were rated according to a global score and a task-specific score, based on an anonymized, timed video recording. RESULTS: Participants demonstrated a significant improvement between the 2 assessments, both on the global score (29.4 vs 21.9 points out of 35; P < .001) and the task-specific score (17.7 vs 14.7 points out of 20; P < .001) as well as procedure time (498.5 vs 700 seconds; P = .001). Medical students showed the greatest progress for the global score (+15.5 points (mean), P = .001) and the task-specific score (+6.5 points (mean), P < .001). 69.2% of participants considered the model as visually quite realistic or highly realistic and all of them judged it quite or extremely interesting for intern training purposes. CONCLUSION: Our 3D printed ureteroscopy simulator was able to enhance the progress of medical students who are new to endoscopy, whilst being valid and reasonably priced. It could become part of a training program in urology, in line with the latest recommendations for surgical education.

Waterpixels.

Many approaches for image segmentation rely on a first low-level segmentation step, where an image is partitioned into homogeneous regions with enforced regularity and adherence to object boundaries. Methods to generate these superpixels have gained substantial interest in the last few years, but only a few have made it into applications in practice, in particular because the requirements on the processing time are essential but are not met by most of them. Here, we propose waterpixels as a general strategy for generating superpixels which relies on the marker controlled watershed transformation. We introduce a spatially regularized gradient to achieve a tunable tradeoff between the superpixel regularity and the adherence to object boundaries. The complexity of the resulting methods is linear with respect to the number of image pixels. We quantitatively evaluate our approach on the Berkeley segmentation database and compare it against the state-of-the-art.