Evidence map›Paper›PMID 42080888›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2026

Augmented reality assisted minimally invasive transforaminal lumbar interbody fusion: feasible and effective workflow with intraoperative video.

Iyan Younus, Rafael Garcia de Oliveira, Patricia Lipson, Aiyush Bansal, Philip Louie

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Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited 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

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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

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5 · Who and what money

Authors and funding

5 authors.

Iyan YounusDepartment of Neurosurgery, Vanderbilt University Medical Center, Nashville, USA. iyan.younus@gmail.com.
Rafael Garcia de OliveiraDepartment of Neurosurgery, Virginia Mason Medical Center, Seattle, USA.
Patricia LipsonDepartment of Neurosurgery, Virginia Mason Medical Center, Seattle, USA.
Aiyush BansalDepartment of Neurosurgery, Virginia Mason Medical Center, Seattle, USA.
Philip LouieDepartment of Neurosurgery, Virginia Mason Medical Center, Seattle, USA. louie.philip@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis article and accompanying video provide a comprehensive workflow for incorporating headset-mounted augmented reality (AR) navigation for minimally invasive transforaminal lumbar interbody fusion (MIS TLIF).

methodsConsecutive patients undergoing a single level MIS-TLIF with AR navigation for degenerative spondylolisthesis were analyzed between January 2023-2025. Demographic, intraoperative, and postoperative outcomes were collected. The AR workflow features a wireless headset with projection of intraoperative navigation in the surgical field. MIS pedicle screw placement, facetectomy, disc preparation, and contralateral arthrodesis are carried out percutaneously though single line of sight using navigated instruments.

resultA total of 138 consecutive patients underwent AR-assisted spinal fusion at our institution and 22 cases of single-level MIS TLIF met inclusion criteria. Mean age was 62.3 ± 15 years, 59% were females, mean BMI was 29.4±5.7 kg/m

conclusionHeadset-mounted AR navigation is a feasible and reproducible tool to provide visualization for MIS TLIF that can be successfully integrated into surgical workflow. In this initial case series, its use was associated with an acceptable early safety profile and consistent perioperative outcomes. However, given the limitations of this study, including its retrospective design and lack of a comparator cohort, further prospective and comparative studies are necessary to evaluate its impact on surgical efficiency, accuracy, and clinical outcomes.

Indexed as

Augmented realityLumbar interbody fusionMinimally invasiveWorkflow

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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.