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See It and Hear It: Multimodal Guidance in MR-Based Neurosurgical Simulation for Skill Retention

  • Pasquale Cascarano*
  • , Andrea Loretti
  • , Luca Zanuttini
  • , Daniele Giunchi
  • , Riccardo Bovo
  • , Shirin Hajahmadi
  • , Giacomo Vallasciani
  • , Matteo Martinoni
  • , Gustavo Marfia
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

External Ventricular Drain (EVD) placement is a complex neurosurgical task that requires identifying a target point within the brain and accurately positioning a catheter at the appropriate angle. While Mixed Reality (MR) technologies have seen limited adoption in the operating room, they offer significant potential for developing training systems that enhance skill acquisition and retention in unaided conditions. A current gap in research concerns the effectiveness of multimodal guidance systems that incorporate both visual and audio-based MR cues. In this paper, we present an MR-based simulator for EVD placement training and evaluate the impact of three MR-guided training modalities: (1) a baseline condition using only 2D CT scans and a 2D catheter projection; (2) a visual guidance modality incorporating a 3D trajectory overlay; and (3) an embodied-audio guidance modality featuring a virtual agent delivering spoken instructions and feedback. Participants underwent a digital training phase using one of the three modalities, followed by an unaided EVD placement on a physical phantom with a real catheter to evaluate skill transfer and retention. Results indicate that both advanced MR modalities significantly improve procedural accuracy, execution speed and receive higher scores in usability and technology acceptance compared to the baseline. Notably, training with 3D visual trajectory guidance led to significantly higher unaided placement accuracy, indicating stronger skill retention. However, multimodal guidance demonstrated equivalent execution speed, while showing a trend toward lower overall cognitive load.
Original languageEnglish
Title of host publicationVRST '25
Subtitle of host publicationProceedings of the 2025 31st ACM Symposium on Virtual Reality Software and Technology
EditorsAnil Batmaz, Mayra Barrera Machuca, Francisco Ortega, Daniel Zielasko, Kangsoo Kim, Rick Skarbez, Lucas Plabst, Amy Banić, Mine Stroppa
PublisherAssociation for Computing Machinery
Number of pages11
ISBN (Print)9798400721182
DOIs
Publication statusPublished - 4 Dec 2025

Publication series

NameVRST: Virtual Reality Software and Technology

Keywords

  • Mixed Reality
  • Neurosurgical Training
  • External Ventricular Drainage
  • Catherer Placement
  • Visual Guidance
  • Audio Guidance
  • Multimodal Guidance
  • Skill Retention

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