Evidence map›Paper›PMID 42216194›Full record

ArticleBMC oral health2026

Comparison of linear and angular cephalometric measurements in CBCT using semi-automated software and artificial intelligence-generated cephalograms.

Kaan Orhan, Ismet Ersalıcı, Nora Saif, Seçil Aksoy, Maxim Gusarev, Matvey Ezhov, Alex Sanders

Abstract readComparative Study
In one paragraph

Article in BMC oral health, 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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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

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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

7 authors.

Kaan OrhanDepartment of Dentomaxillofacial Radiology, Faculty of Dentistry, Ankara University, Ankara, Turkey.
Ismet ErsalıcıDepartment of Orthodontics, Faculty of Dentistry, Near East University, Nicosia, Cyprus.
Nora SaifDepartment of Oral and Maxillofacial Radiology, Faculty of Dentistry, Cairo University, Cairo, Egypt. nora.taha@dentistry.cu.edu.eg.
Seçil AksoyDepartment of Dentomaxillofacial Radiology, Faculty of Dentistry, Near East University, Nicosia, Cyprus.
Maxim GusarevDiagnocat, Inc, San Francisco, USA.
Matvey EzhovDiagnocat, Inc, San Francisco, USA.
Alex SandersDiagnocat, Inc, San Francisco, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to assess the reliability of cephalometric measurements using CBCTs with two semi-automated software programs (InVivoDental and Romexis) and an artificial intelligence-based platform (Diagnocat).

methodsThis cross-sectional reliability study retrospectively analyzed a total of 29 CBCT scans (15 from Northern Cyprus and 14 from Egypt). Eleven measurements were included to assess vertical relationship, and anteroposterior relationship, using two software programs and an AI-based website.

resultsIntraobserver reliability, assessed through Bland-Altman plots, demonstrated high consistency. Interobserver agreement showed excellent reliability for most measurements, with ICC values exceeding 0.90 for both InVivoDental and Romexis software. Most measurements did not show significant differences between the two semi-automated programs and the AI-based algorithms. However, the AI system indicated lower measurements for Wits Appraisal and U1-SN angle compared to the two software systems.

conclusionIn conclusion, this study underscores the importance of evaluating the reliability of cephalometric measurements on CBCTs, particularly when utilizing semi-automated software programs and artificial intelligence-based platforms. Our analysis revealed consistent intra-observer repeatability across most measurements. However, it is noteworthy that certain metrics exhibited reduced repeatability when assessed using AI-generated cephalograms, suggesting potential areas for improvement in AI algorithms.

Indexed as

Artificial IntelligenceCephalometryCone-Beam Computed TomographySoftwareAlgorithmsCross-Sectional StudiesFemaleHumansImage Processing, Computer-AssistedIntelligent SystemsMaleObserver VariationReproducibility of ResultsRetrospective StudiesArtificial intelligenceCBCTCephalometric measurements

Identifiers

PMID42216194
PMCPMC13310432

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