Evidence map›Paper›PMID 42294425›Full record

ArticleFrontiers in surgery2026

Real-time augmented reality navigation in brain glioma resection: a pilot feasibility study.

Peihai Zhang, Kai Zhang, Huiting Liu, Xuejun Yang

Abstract read
In one paragraph

Article in Frontiers in surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Peihai ZhangBeijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
Kai ZhangBeijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
Huiting LiuPeking Union Medical College Hospital, Beijing, China.
Xuejun YangBeijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the clinical feasibility and technical performance of augmented reality (AR) navigation for brain glioma resection in a preliminary patient series. Methods: From April 2024 to May 2025, 6 patients with brain glioma were enrolled in this pilot study. Preoperative magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and magnetic resonance angiography (MRA) data were processed and imported into an AR head-mounted device. The 3D holographic models were reconstructed to enable preoperative surgical planning, simulation of resection pathways, and intraoperative AR navigation. The primary outcomes included AR registration time, target registration error (TRE) verified by an optical navigation system (StealthStation S7), extent of resection on postoperative MRI, and neurological function assessed by the Modified Rankin Scale (mRS) and detailed neurological examination at 3 months. Results: Gross total resection of the contrast-enhancing tumor was achieved in all patients. The mean AR registration time was 4.7 ± 0.7 min. The surface-matching registration yielded a TRE of 2.1 ± 0.4 mm compared to the StealthStation reference. Postoperative mRS scores improved significantly at 3 months ( Conclusion: This pilot study demonstrates that AR navigation is technically feasible for brain glioma resection. However, the small sample size limits conclusions about clinical efficacy.

Indexed as

augmented realitybrain gliomaHoloLens 2navigationsurgery

Identifiers

PMID42294425
PMCPMC13253691

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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.