Evidence map›Paper›PMID 41920207›Full record

ArticleUnfallchirurgie (Heidelberg, Germany)2026

Virtual reality as classification aid for acetabular fractures : New possibilities for training and teaching.

Vincent K Schenk, Carolin Dieges, David Ackermann, Maximilian M Menger, Carolina Vogel, Tina Histing, Steven C Herath, Markus A Küper, Anna L Schiltenwolf, Christof K Audretsch

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In one paragraph

Article in Unfallchirurgie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Vincent K SchenkDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany. vincent.schenk@student.uni-tuebingen.de.
Carolin DiegesDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
David AckermannDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
Maximilian M MengerDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
Carolina VogelDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
Tina HistingDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
Steven C HerathDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
Markus A KüperDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
Anna L SchiltenwolfDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.
Christof K AudretschDepartment for Traumatology and Reconstructive Surgery, BG Trauma Center, University of Tübingen, Schnarrenbergstraße 95, 72076, Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incidence of acetabular fractures has increased, and classification according to Judet and Letournel remains challenging. While 3D CT improves accuracy, virtual reality (VR) may enhance training. This study assessed whether a VR simulator improves classification accuracy and understanding in inexperienced users. MATERIALS AND

methodsAn HTC VIVE Pro headset and an Alienware m15 R4 computer were utilized. Programming was done in Unity (2021.3.4f1 LTS), and segmentation in Slicer3D. In total, 83 ninth-semester medical students, divided into a VR group (n = 44) and a 3D control group (n = 39), took part. Participants had to classify 11 acetabular fractures, supported by pictograms if needed, followed by a user survey. Accuracy was compared.

resultsAll participants completed the study. Overall, 68% had no prior knowledge of the classification. The control group achieved a median of 27% (interquartile range [IQR]: 14-36%) correct classifications, while the VR group reached 45% (IQR: 36-64%), showing higher accuracy (p < 0.001). In general, essential fractures were classified significantly more accurately than associated fractures (p < 0.001). The VR system was rated as more intuitive than the 3D software (p = 0.025).

conclusionThe VR simulator significantly improved acetabular fracture classification among inexperienced users. It is intuitive, easy to use, and offers strong potential for future surgical training.

Indexed as

AcetabulumFractures, BoneVirtual RealityAdultClinical CompetenceFemaleHumansImaging, Three-DimensionalMaleOrthopedicsSoftwareStudents, MedicalTomography, X-Ray ComputedYoung AdultAcetabular surgeryFracture classificationMedical educationMedical simulationVirtual reality

Identifiers

PMID41920207
PMCPMC13328152

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LicenceCC BY
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Registered trials

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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.