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Holographic patient tracking after bed movement for augmented reality neuronavigation using a head-mounted display
T Fick1, J A M van Doormaal2, E W Hoving3,4
1Department of Neuro-oncology, Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584, CS, Utrecht, The Netherlands. t.fick-4@prinsesmaximacentrum.nl.
Acta Neurochirurgica
|January 30, 2021
Summary
This study introduces holographic neuronavigation, using an augmented reality head-mounted display (AR-HMD) for improved spatial understanding in neurosurgery. Patient tracking was achieved, though accuracy requires further optimization for clinical use.
Area of Science:
- Neurosurgery
- Medical Technology
- Augmented Reality
Background:
- Holographic neuronavigation offers potential advantages over conventional systems.
- This study reports the first holographic neuronavigation system with patient-to-image registration and tracking.
- Utilizes an augmented reality head-mounted display (AR-HMD).
Purpose of the Study:
- To demonstrate the feasibility of a holographic neuronavigation system for intracranial neurosurgery.
- To evaluate patient-to-image registration and patient tracking capabilities.
- To assess the system's potential for improving spatial anatomical understanding in surgeons.
Main Methods:
- Pilot study involving three patients undergoing intracranial neurosurgery.
- 3D segmentation of anatomy uploaded as a holographic scene.
- Point-based matching using anatomical landmarks for registration.
- Fiducial registration error (FRE) measured for accuracy.
- Custom reference array with QR codes for patient tracking post-movement.
Main Results:
- Six registrations performed with a mean FRE of 8.5 mm.
- Successful patient tracking demonstrated, maintaining registration integrity after bed movement.
- No visual difference observed in registration before and after patient repositioning.
Conclusions:
- Proof of principle for intraoperative patient tracking with a standalone holographic neuronavigation system.
- Navigation accuracy requires further optimization for clinical application.
- The technology shows promise for future neurosurgical workflows due to enhanced spatial understanding.
