Evidence map›Paper›PMID 38019844›Full record

ArticleSurgical innovation2024

Mixed Reality Surgical Navigation System; Positional Accuracy Based on Food and Drug Administration Standard.

Christopher T Morley, David M Arreola, Long Qian, Amy L Lynn, Zachary P Veigulis, Thomas F Osborne

Abstract read
In one paragraph

Article in Surgical innovation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
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  7. Augmented reality in brachytherapy: A narrative review.Journal of contemporary brachytherapy · 2024
    Review
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

6 authors.

Christopher T MorleyMedivis, Inc., New York, NY, USA.
David M ArreolaUS Department of Veterans Affairs, Palo Alto Healthcare System, Palo Alto, CA, USA.ORCID 0000-0002-2865-3797
Long QianMedivis, Inc., New York, NY, USA.
Amy L LynnMedivis, Inc., New York, NY, USA.
Zachary P VeigulisUS Department of Veterans Affairs, Palo Alto Healthcare System, Palo Alto, CA, USA.
Thomas F OsborneUS Department of Veterans Affairs, Palo Alto Healthcare System, Palo Alto, CA, USA.ORCID 0000-0002-8896-2487

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputer assisted surgical navigation systems are designed to improve outcomes by providing clinicians with procedural guidance information. The use of new technologies, such as mixed reality, offers the potential for more intuitive, efficient, and accurate procedural guidance. The goal of this study is to assess the positional accuracy and consistency of a clinical mixed reality system that utilizes commercially available wireless head-mounted displays (HMDs), custom software, and localization instruments.

methodsIndependent teams using the second-generation Microsoft HoloLens

resultsThe system demonstrated consistent results, with an average accuracy performance that was better than one millimeter (.75 ± SD .37 mm).

conclusionIndependently acquired positional tracking accuracies exceed conventional in-market surgical navigation tracking systems and FDA standards. Importantly, the performance was achieved at two different institutions, using an international testing standard, and with a system that included a commercially available off-the-shelf wireless head mounted display and software.

Indexed as

Augmented RealitySurgery, Computer-AssistedSoftwareSurgical Navigation SystemsUnited StatesUnited States Food and Drug AdministrationAugmented realitycomputer-assisted surgeryHoloLensmixed realitysurgical navigation

Identifiers

PMID38019844
PMCPMC10773158

What OpenQuestion holds

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LicenceCC BY-NC
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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.