Overcoming Barriers in Neurosurgical Education: Introducing a Simulator for Insular Glioma Resection with Fluorescence Imaging (SIGMA)

Abstract

Background and Objectives: Realistic surgical simulation models are essential for neurosurgical training, particularly in glioma resection. We developed a patient-specific simulation model designed for fluorescence-guided glioma resection, providing an anatomically accurate and reusable platform for surgical education. While insular gliomas were used as an example, the model can be adapted to simulate gliomas in other brain regions, making it a versatile training tool. Methods: Using open-source 3D software, we created a digitally reconstructed skull, brain, and cerebral vessels, including a fluorescent insular glioma. The model was produced through additive manufacturing and designed with input from neurosurgeons to ensure a realistic and reusable representation of the Sylvian fissure and bone structures. The simulator’s educational effectiveness and usability were evaluated by two senior physicians, four assistant physicians, and six medical students using actual microsurgical instruments. Assessments were based on subjective and objective criteria. Results: Subjective evaluations, using a 5-point Likert scale, showed high face and content validity. Objective measures demonstrated strong construct validity, accurately reflecting the participant’s skills. Medical students and resident neurosurgeons showed marked improvement in their learning curve over three attempts, with progressive improvement in performance. Conclusions: This simulation model addresses advanced neurosurgical training needs by providing a highly realistic, cost- effective, and adaptable platform for fluorescence-guided glioma resection. Its effectiveness in enhancing surgical skills suggests significant potential for broader integration into neurosurgical training programs. Further studies are warranted to explore its applications in different glioma localizations and training settings.