ArticleInternational journal of computer assisted radiology and surgery2026
VIVIE: Virtually Integrated Ventricular Intervention Environment and its effectiveness as a teaching and learning tool.
Article in International journal of computer assisted radiology and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeExternal ventricular drain (EVD) placement is a fundamental neurosurgical procedure for monitoring and relieving elevated intracranial pressure, yet catheter misplacement remains common, particularly during early training. Virtual reality (VR) simulation offers a scalable approach for procedural education. We present VIVIE, a standalone VR-based training system designed to support safe, repeatable practice of EVD placement.
methodsVIVIE simulates key steps of EVD placement, including anatomical landmark identification, entry point selection, burr hole creation, and catheter insertion. A pilot user study was conducted with 15 novice participants who completed a structured tutorial followed by progressively more challenging training levels. Objective performance metrics were recorded alongside subjective measures of workload and usability. Two expert neurosurgeons evaluated the system through hands-on use and provided qualitative feedback on realism, workflow fidelity, and educational relevance.
resultsNovice participants demonstrated improved targeting accuracy and lateral control across training levels despite increasing task difficulty, indicating a measurable learning effect. Subjective evaluations indicated low to moderate workload, good perceived usability, and high user engagement. Expert reviewers highlighted the system's realism and educational potential, while identifying limitations related to interaction fidelity, depth perception, and anatomical detail.
conclusionVIVIE demonstrates feasibility as a VR-based training system for EVD, particularly for early-stage learners. These findings support its potential role in simulation-based neurosurgical education, while expert feedback underscores the importance of high-fidelity interaction and anatomical representation for advanced training. Future work will focus on system refinement and larger-scale validation to assess learning transfer and clinical relevance.
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