Evidence map›Paper›PMID 39958371›Full record

ArticleNeurosurgery practice2023

Assessment of Accuracy of Mixed Reality Device for Neuronavigation: Proposed Methodology and Results.

Swati Jain, Tamara Tajsic, Tilak Das, Yujia Gao, Ngiam Kee Yuan, Tseng Tsai Yeo, Martin J Graves, Adel Helmy

Abstract read
In one paragraph

Article in Neurosurgery practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Swati JainDivison of Neurosurgery, University Surgical Cluster, National University Health System, Singapore.ORCID https://orcid.org/0000-0002-4359-7260
Tamara TajsicDivision of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Tilak DasDepartment of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Yujia GaoDivision of Hepatobiliary & Pancreatic Surgery, University Surgical Cluster, National University Health System (NUHS), Singapore.
Ngiam Kee YuanDivision of General Surgery (Thyroid & Endocrine Surgery), University Surgical Cluster, National University Health System (NUHS), Singapore.
Tseng Tsai YeoDivison of Neurosurgery, University Surgical Cluster, National University Health System, Singapore.
Martin J GravesDepartment of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Adel HelmyDivision of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-0531-0556

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intraoperative neuronavigation is currently an essential component of neurosurgical operations in several contexts. Recent progress in mixed reality (MR) technology has attempted to overcome the disadvantages of standard neuronavigation systems allowing the surgeon to superimpose a 3D rendered image onto the patient's anatomy. We present the first study in the literature to assess the surface matching accuracy of MR rendered image. For the purposes of this study, we used HoloLens 2 with virtual surgery intelligence providing the software capability for image rendering. To assess the accuracy of using mixed reality device for neuronavigation intraoperatively. This study seeks to assess the accuracy of rendered holographic images from a mixed reality device as a means for neuronavigation intraoperatively. We used the Realistic Operative Workstation for Educating Neurosurgical Apprentices to represent a patient's skull with intracranial components which underwent standardized computed tomography (CT) and MRI imaging. Eleven predefined points were used for purposes of assessing the accuracy of the rendered image, compared with the intraoperative gold standard neuronavigation. The mean HoloLens values against the ground truth were significantly higher when compared with Stealth using CT scan as the imaging modality. Using extracranial anatomic landmarks, the HoloLens error values continued to be significantly higher in magnitude when compared with Stealth across CT and MRI. This study provides a relatively easy and feasible method to assess accuracy of MR-based navigation without requiring any additions to the established imaging protocols. We failed to show the equivalence of MR-based navigation over the current neuronavigation systems.

Indexed as

HoloLens 2Mixed realityNeuronavigation

Identifiers

PMID39958371
PMCPMC11809955

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.