Evidence map›Paper›PMID 38764227›Full record

ArticleAsian spine journal2024

Feasibility of a novel augmented reality overlay for cervical screw placement in phantom spine models.

Joshua Olexa, Brian Shear, Nathan Han, Ashish Sharma, Annie Trang, Kevin Kim, Gary Schwartzbauer, Steven Ludwig, Charles Sansur

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Article in Asian spine journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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4 · The record

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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

9 authors.

Joshua OlexaDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Brian ShearDepartment of Orthopaedic Surgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Nathan HanDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Ashish SharmaDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Annie TrangDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Kevin KimDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Gary SchwartzbauerDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Steven LudwigDepartment of Orthopaedic Surgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Charles SansurDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

designFeasibility study. PURPOSE: A phantom model was used to evaluate the accuracy of a novel augmented reality (AR) system for cervical screw placement. OVERVIEW OF LITERATURE: The use of navigation systems is becoming increasingly common in spine procedures. However, numerous factors limit the feasibility of regular and widespread use of navigation tools during spine surgery. AR is a new technology that has already demonstrated utility as a navigation tool during spine surgery. However, advancements in AR technology are needed to increase its adoption by the medical community.

methodsAR technology that uses a fiducial-less registration system was tested in a preclinical cervical spine phantom model study for accuracy during spinal screw placement. A three-dimensional reconstruction of the spine along with trajectory lines was superimposed onto the phantom model using an AR headset. Participants used the AR system to guide screw placement, and post-instrumentation scans were compared for accuracy assessment.

resultsTwelve cervical screws were placed under AR guidance. All screws were placed in an acceptable anatomic position. The average distance error for the insertion point was 2.73±0.55 mm, whereas that for the endpoint was 2.71±0.69 mm. The average trajectory angle error for all insertions was 2.69°±0.59°.

conclusionsThis feasibility study describes a novel registration approach that superimposes spinal anatomy and trajectories onto the surgeon's real-world view of the spine. These results demonstrate reasonable accuracy in the preclinical model. The results of this study demonstrate that this technology can assist with accurate screw placement. Further investigation using cadaveric and clinical models is warranted.

Indexed as

Augmented realityCervicalMixed realityScrew fixation

Identifiers

PMID38764227
PMCPMC11222888

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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.