A Neurosurgical Craniotomy Training System Based on Haptic Virtual Reality Simulation

Guobin Zhang, Keliang Li, Qiyuan Sun, Wenqi Wu, Shuai Li, Zhenzhong Liu*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Traditional neurosurgical training modes face challenges including high costs, limited resources, lengthy learning curves, and difficulties in personalized training. In this article, we developed an immersive neurosurgical craniotomy virtual training system (NeuroSimulator) that integrates haptic feedback, enabling comprehensive surgical skill learning through an operator-control interface. Specifically, we constructed the comprehensive neurosurgical craniotomy surgical procedural (CNCSP) dataset to guide operators in repetitive learning and personalized training of relevant surgical skills. To address surgical site model rendering complexity, we proposed an algorithm that integrates vertex curvature and edge-length cost calculation factors (VC&ECL-QEM), resolving the incompatibility between surgical area image rendering quality and efficiency. For intracranial soft tissue haptic deformation, we developed a hybrid soft tissue haptic deformation (HBD) model that combines mass-spring and volumetric elements, addressing the collapse and distortion issues of traditional models and achieving more realistic soft tissue haptic deformation. Experimental results demonstrate that VC&ECL-QEM can simplify nonsurgical area feature preservation while maintaining surgical site detail features, reflecting the effectiveness of model simplification. The HBD model focuses on improving soft tissue deformation realism and shows high consistency with finite element model deformation effects. A total of 83 participants highly recognized NeuroSimulator’s system performance in terms of operational compliance, rendering real-time performance, and deformation realism, achieving effective improvements in skill proficiency metrics including operation time, ineffective operations, guidance requests, and operation scores. NeuroSimulator provides an innovative, efficient, and practical solution for neurosurgical training and is expected to play an increasingly important role in medical education and clinical skill enhancement.

Original languageEnglish
Number of pages10
JournalIEEE Transactions on Human-Machine Systems
DOIs
Publication statusAccepted/In press - 2025
MoE publication typeA1 Journal article-refereed

Keywords

  • Human–machine interaction
  • neurosurgical craniotomy
  • simulator
  • training system
  • virtual reality (VR)

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