Evidence map›Paper›PMID 42213384›Full record

ArticleProgress in orthodontics2026

Evaluation of artificial intelligence-based cephalometric analysis compared to the manual method.

Alfonso Alvarado-Lorenzo, Laura Criado-Pérez, Daniele Garcovich, Sabina Romero, Giuseppe Scuzzo, Giacomo Scuzzo, Adrián Curto

Abstract readComparative Study
In one paragraph

Article in Progress in orthodontics, 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

7 authors.

Alfonso Alvarado-LorenzoDepartment of Oral Surgery, University of Salamanca, Salamanca, Spain.
Laura Criado-PérezDepartment of Oral Surgery, University of Salamanca, Salamanca, Spain. lauracriado@usal.es.
Daniele GarcovichDepartment of Dentistry, European University of Valencia, Valencia, Spain.
Sabina RomeroDepartment of Oral Surgery, University of Salamanca, Salamanca, Spain.
Giuseppe ScuzzoDepartment of Orthodontics, Università Cattolica del Sacro Cuore, Rome, Italy.
Giacomo ScuzzoEline Clinic, Rome, Italy.
Adrián CurtoDepartment of Oral Surgery, University of Salamanca, Salamanca, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe application of artificial intelligence (AI) to cephalometry has aroused growing interest due to its potential to optimize clinical workflows and improve efficiency. This study aimed to compare the differences and reproducibility of cephalometric measurements obtained using three methods: manual, WebCeph™ and AngelAligner™. METHODOLOGY: 30 patients were analysed, evaluating 9 measurements generated by the three methods at two different timepoints (T1 and T2).

resultsWebCeph™ presented significant differences as compared to the manual method in 7 of the 9 measurements (SNA, SNB, ANB, U1-APg, L1-APg, GoGn-SN, U1-L1), while AngelAligner™ displayed significant differences with the manual method in 4 measurements (SNA, U1-APg, L1-APg and U1-L1). Significant differences were found between the two AI-based systems in 7 of the 9 measurements. Reproducibility was high at all angles with the manual method, except for U1-L1, NLA, and LFH. The ICC was 1 for all measurements for both AI-based systems, indicating optimal reproducibility. When grouping by malocclusions, however, WebCeph™ presented greater differences with the manual method than AngelAligner™.

conclusionAI-based methods offered greater reproducibility than the manual method, but still require human supervision.

Indexed as

Artificial IntelligenceCephalometryAdolescentFemaleHumansMaleMalocclusionMandibleReproducibility of ResultsArtificial intelligenceCephalometricsDigitalManual tracing

Identifiers

PMID42213384
PMCPMC13221533

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