Evidence map›Paper›PMID 39877694›Full record

ArticleFrontiers in digital health2024

Targeting accuracy of neuronavigation: a comparative evaluation of an innovative wearable AR platform vs. traditional EM navigation.

Marina Carbone, Nicola Montemurro, Nadia Cattari, Martina Autelitano, Fabrizio Cutolo, Vincenzo Ferrari, Emanuele Cigna, Sara Condino

Abstract read
In one paragraph

Article in Frontiers in digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. A real-time metric for quantifying registration stability in mixed reality neurosurgical navigation.International journal of computer assisted radiology and surgery · 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

8 authors.

Marina Carbone *Department of Information Engineering, University of Pisa, Pisa, Italy.
Nicola Montemurro *EndoCAS Interdipartimental Center, University of Pisa, Pisa, Italy.
Nadia CattariDepartment of Information Engineering, University of Pisa, Pisa, Italy.
Martina AutelitanoEndoCAS Interdipartimental Center, University of Pisa, Pisa, Italy.
Fabrizio CutoloDepartment of Information Engineering, University of Pisa, Pisa, Italy.
Vincenzo FerrariDepartment of Information Engineering, University of Pisa, Pisa, Italy.
Emanuele CignaEndoCAS Interdipartimental Center, University of Pisa, Pisa, Italy.
Sara CondinoDepartment of Information Engineering, University of Pisa, Pisa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable augmented reality in neurosurgery offers significant advantages by enabling the visualization of navigation information directly on the patient, seamlessly integrating virtual data with the real surgical field. This ergonomic approach can facilitate a more intuitive understanding of spatial relationships and guidance cues, potentially reducing cognitive load and enhancing the accuracy of surgical gestures by aligning critical information with the actual anatomy in real-time. This study evaluates the benefits of a novel AR platform, VOSTARS, by comparing its targeting accuracy to that of the gold-standard electromagnetic (EM) navigation system, Medtronic StealthStation

Indexed as

augmented reality navigationhead mounted displaysneuronavigationneurosurgerysurgical navigationtargeting accuracy

Identifiers

PMID39877694
PMCPMC11772343

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.