Evidence map›Paper›PMID 37893439›Full record

ReviewMedicina (Kaunas, Lithuania)2023

Augmented Reality in Neurosurgery: A New Paradigm for Training.

Grace Hey, Michael Guyot, Ashley Carter, Brandon Lucke-Wold

Open access · goldAbstract readReview
In one paragraph

Review in Medicina (Kaunas, Lithuania), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
20.6field-weighted citation impact, top 1% of its field
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

37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 65 citations in OpenAlex.

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  6. Advanced imaging integration in robotic neurosurgery.Annals of medicine and surgery (2012) · 2026
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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

4 authors at 2 institutions in 1 country.

Grace HeyCollege of Medicine, University of Florida, Gainesville, FL 32610, USA.
Michael GuyotCollege of Medicine, University of Florida, Gainesville, FL 32610, USA.ORCID 0009-0000-0664-7516
Ashley CarterEastern Virginia Medical School, Norfolk, VA 23507, USA.
Brandon Lucke-WoldDepartment of Neurosurgery, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-6577-4080
University of Florida · USEastern Virginia Medical School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Augmented reality (AR) involves the overlay of computer-generated images onto the user's real-world visual field to modify or enhance the user's visual experience. With respect to neurosurgery, AR integrates preoperative and intraoperative imaging data to create an enriched surgical experience that has been shown to improve surgical planning, refine neuronavigation, and reduce operation time. In addition, AR has the potential to serve as a valuable training tool for neurosurgeons in a way that minimizes patient risk while facilitating comprehensive training opportunities. The increased use of AR in neurosurgery over the past decade has led to innovative research endeavors aiming to develop novel, more efficient AR systems while also improving and refining present ones. In this review, we provide a concise overview of AR, detail current and emerging uses of AR in neurosurgery and neurosurgical training, discuss the limitations of AR, and provide future research directions. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 386 articles were initially identified. Two independent reviewers (GH and AC) assessed article eligibility for inclusion, and 31 articles are included in this review. The literature search included original (retrospective and prospective) articles and case reports published in English between 2013 and 2023. AR assistance has shown promise within neuro-oncology, spinal neurosurgery, neurovascular surgery, skull-base surgery, and pediatric neurosurgery. Intraoperative use of AR was found to primarily assist with surgical planning and neuronavigation. Similarly, AR assistance for neurosurgical training focused primarily on surgical planning and neuronavigation. However, studies included in this review utilize small sample sizes and remain largely in the preliminary phase. Thus, future research must be conducted to further refine AR systems before widespread intraoperative and educational use.

Indexed as

Augmented RealityNeurosurgerySurgery, Computer-AssistedChildHumansProspective StudiesRetrospective Studiesaugmented realitycranial neurosurgerymachine learningneuro-oncologyneurosurgeryneurosurgical trainingneurovascular surgeryspine surgery

Identifiers

PMID37893439
PMCPMC10608758
OpenAlexW4387047039

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.