Training the next generation: a blueprint for simulation-based microsurgical education in neurosurgery

Modern neurosurgical training is increasingly challenged by declining surgical caseloads and reduced hands-on opportunities. While haptic simulators offer safe and repetitive practice, their adoption remains limited due to high costs, suboptimal realism, and lack of standardization. This study introduces a highly realistic, low-cost, and fully replicable microsurgical simulator for repetitive training in complex cranial procedures, including sylvian fissure and white matter dissections, aneurysm clipping, and resection of anterior skull base, frontal, and temporal lobe tumors.

The simulator was developed using high-resolution anatomical reconstructions, additive manufacturing, and carefully selected materials to replicate the visual and tactile properties of living brain tissue. The entire process relied solely on freely available software, and a detailed blueprint is provided to allow easy replication. Three groups of participants (n = 22) with varying levels of surgical experience tested and evaluated the simulator. Pathology- and procedure-specific objective assessment tools were used to evaluate participants' technical skills and assess the simulator's educational efficacy and transferability.

The simulator was produced without specialized infrastructure and at minimal cost. Across all levels of experience, participants highly rated its realism, usability, and educational value (mean Likert score 4.9/5). Objective assessments demonstrated strong construct validity and significant improvements in technical performance, particularly among novice users, after short training intervals. Notably, the simulator allows direct comparison of different surgical approaches to the same pathology.

This study demonstrates the feasibility of creating an anatomically accurate, affordable simulator for advanced neurosurgical training using only freeware and accessible materials. The simulator enables realistic, hands-on practice across a wide range of procedures, including patient-specific simulations and comparison of surgical strategies. This simulator marks a significant step toward integrating physical simulation-based training into standardized neurosurgical curricula, offering a practical and scalable solution to current training limitations.