Box trainers are ideal simulators, given they are inexpensive, accessible, and use appropriate fidelity.
Objective
The development and validation of an open-source, partial task simulator that teaches the fundamental skills necessary for endonasal skull-base neuro-endoscopic surgery.
Methods
We defined the Neuro-Endo-Trainer (NET) SkullBase-Task-GraspPickPlace with an activity area by analyzing the computed tomography scans of 15 adult patients with sellar suprasellar parasellar tumors. Four groups of participants (Group E, n = 4: expert neuroendoscopists; Group N, n =19: novice neurosurgeons; Group R, n = 11: neurosurgery residents with multiple iterations; and Group T, n = 27: neurosurgery residents with single iteration) performed grasp, pick, and place tasks using NET and were graded on task completion time and skills assessment scale score.
Results
Group E had lower task completion times and greater skills assessment scale scores than both Group N and R (P ≤ 0.03, 0.001). The performance of Groups N and R was found to be equivalent; in self-assessing neuro-endoscopic skill, the participants in these groups were found to have equally low pretraining scores (4/10) with significant improvement shown after NET simulation (6, 7 respectively). Angled scopes resulted in decreased scores with tilted plates compared with straight plates (30° P ≤ 0.04, 45° P ≤ 0.001). With tilted plates, decreased scores were observed when we compared the 0° with 45° endoscope (right, P ≤ 0.008; left, P ≤ 0.002).
Conclusions
The NET, a face and construct valid open-source partial task neuroendoscopic trainer, was designed. Presimulation novice neurosurgeons and neurosurgical residents were described as having insufficient skills and preparation to practice neuro-endoscopy. Plate tilt and endoscope angle were shown to be important factors in participant performance. The NET was found to be a useful partial-task trainer for skill building in neuro-endoscopy.
