The space child neonatal trainer (SCNT)-A novel 3D-Printed simulator for neonatal laparoscopy

Neonatal laparoscopic surgery offers numerous advantages but remains challenging due to limited anatomical workspace and scarce training opportunities. Existing simulators often lack neonatal-specific anatomical realism. We developed and evaluated the Space Child Neonatal Trainer (SCNT), a low-cost (€10), fully 3D-printed neonatal laparoscopic simulator derived directly from patient-specific imaging data, designed to improve anatomical accuracy and training realism.

The SCNT was developed using anonymized CT scans of a one-month-old neonate. Anatomical segmentation was performed using 3D Slicer, with refinements in Blender and Fusion 360®, integrating realistic trocar entry points. Models were 3D-printed using thermoplastic polyurethane (TPU 87A) with infill density optimized by mechanical testing. Evaluation involved two phases: (1) a laparoscopic skills workshop with 21 pediatric surgery residents and three expert surgeons assessing realism and usability; (2) a comparative evaluation against the validated Pediatric Laparoscopic Simulator (PLS) with 22 first-year medical students, measuring task time, errors, and Objective Structured Assessment of Technical Skills (OSATS) scores.

Participants rated the SCNT highly for anatomical fidelity and usability (trocar placement: 4.0 ± 0.6; workspace adequacy: 4.2 ± 0.7). A comparative assessment revealed similar performance between SCNT and PLS across most metrics. Only tissue handling scores differed significantly, favoring PLS (p = 0.014). Mechanical analysis identified 15 % infill density as optimal for balancing flexibility and structural integrity, confirmed by expert surgeons for superior haptic realism.

The SCNT provides a realistic, cost-effective, anatomically precise neonatal laparoscopic trainer. Initial evaluations support its value in pediatric surgical education, though further validation in broader educational contexts is necessary.