Evidence map›Paper›PMID 41833977›Full record

ArticleInternational endodontic journal2026

Practitioners' Perceptions of Augmented and Virtual Reality in Endodontic Treatment Planning: A Pilot Study.

Marcel Reymus, Nils Werner, Falk Schwendicke, Ralf Krug

Abstract read
In one paragraph

Article in International endodontic journal, 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
–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

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

4 authors.

Marcel ReymusDepartment of Conservative Dentistry, Periodontology and Digital Dentistry, LMU University Hospital, LMU Munich, Munich, Germany.ORCID https://orcid.org/0000-0001-9040-5623
Nils WernerDepartment of Conservative Dentistry, Periodontology and Digital Dentistry, LMU University Hospital, LMU Munich, Munich, Germany.ORCID https://orcid.org/0000-0001-8498-0736
Falk SchwendickeDepartment of Conservative Dentistry, Periodontology and Digital Dentistry, LMU University Hospital, LMU Munich, Munich, Germany.ORCID https://orcid.org/0000-0003-1223-1669
Ralf KrugDepartment of Conservative Dentistry and Periodontology, University Hospital Würzburg, Würzburg, Germany.ORCID https://orcid.org/0000-0002-1412-726X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo develop a streamlined software workflow for converting cone-beam computed tomography (CBCT) data into augmented reality (AR) and virtual reality (VR) formats, and to evaluate dental practitioners' perceptions of these advanced visualisation modalities compared to conventional CBCT analysis for endodontic treatment planning. METHODOLOGY: A custom add-on for Blender (an open-source 3D modelling software), named VirtualEndo, was developed to automate the processing of AI-segmented CBCT scans into AR- and VR-compatible formats. Thirty dentists evaluated two diagnostically challenging cases using four methods: conventional CBCT analysis, AI-driven 3D segmentation, AR visualisation on iPad and VR visualisation with Meta Quest 3. The presentation order was randomised, and participants completed a standardised training protocol. Perceptions regarding diagnostic confidence, usability, information extraction, and clinical relevance were assessed using 4-point Likert scales. Statistical analysis employed Friedman tests with post hoc Wilcoxon signed-rank tests and Bonferroni correction.

resultsSignificant differences were found across all evaluated categories (p < 0.05). Conventional CBCT was rated significantly inferior to Segmentation, VR, and AR for information extraction (canal course: W = 0.68; canal number: W = 0.56) and usability (W = 0.40). No significant differences existed between the three advanced visualisation methods. Segmentation was most frequently selected as clinically most relevant (40%), followed by VR (20%). For canal detection, differences were small (W = 0.10) with no method demonstrating clear superiority.

conclusionsModern 3D visualisation technologies were perceived as significantly superior to conventional 2D CBCT slice analysis, primarily by presenting pre-integrated anatomical models that reduce the perceived cognitive burden of mental 3D reconstruction from 2D slices. Screen-based segmentation was favoured for pragmatic workflow integration, though immersive technologies showed promise if adoption barriers are addressed.

Indexed as

Attitude of Health PersonnelAugmented RealityDentistsEndodonticsPatient Care PlanningRoot Canal TherapyVirtual RealityCone-Beam Computed TomographyHumansImaging, Three-DimensionalPilot ProjectsSoftware

Identifiers

PMID41833977
PMCPMC13373033

What OpenQuestion holds

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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.