Evidence map›Paper›PMID 41758431›Full record

ArticleProgress in orthodontics2026

Reliability of AI-driven cephalometric analysis on CBCT: comparison with manual 2D cephalometry.

Natalia Kazimierczak, Natalia Chwarścianek, Nora Sultani, Joanna Janiszewska-Olszowska, Tomasz Jankowski, Anita Nowicka, Zbigniew Serafin, Wojciech Kazimierczak

Abstract readComparative Study
PubMed Full text at PMC Publisher
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Article in Progress in orthodontics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Natalia KazimierczakKazimierczak Clinic, Bydgoszcz, Poland.
Natalia ChwarścianekLudwik Rydygier Provincial Hospital, Torun, Poland.
Nora SultaniFaculty of Medicine, Collegium Medicum, Nicolaus Copernicus University, Toruń, Poland.
Joanna Janiszewska-OlszowskaDepartment of Interdisciplinary Dentistry, Pomeranian Medical University, Szczecin, Poland.
Tomasz JankowskiPrivate Dental Practice Jankowscy Clinic, Zary, Poland.
Anita NowickaKazimierczak Clinic, Bydgoszcz, Poland.
Zbigniew SerafinFaculty of Medicine, Bydgoszcz University of Science and Technology, Bydgoszcz, Poland.
Wojciech KazimierczakDepartment of Radiology and Diagnostic Imaging, Collegium Medicum, Nicolaus Copernicus University, Toruń, Poland. w.kazimierczak@cm.umk.pl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is increasingly utilized in orthodontics to automate cephalometric analysis. Despite promising results for AI-based landmark detection on 2D cephalograms, the reliability of AI analyses performed on 3D CBCT data by commercial systems remains unclear. The aim of this study was to evaluate the interchangeability between the results of AI-driven cephalometric analyses using two commercial software platforms (CephX and Invivo) on CBCT datasets and reference 2D cephalometric analysis following manual landmark identification. MATERIALS AND

methodsThis retrospective study included 135 patients (mean age: 26.8 ± 10.1 years) who underwent concurrent CBCT and lateral cephalometric imaging. Analyses (Steiner and Ricketts methods) based on manual landmark identification served as the reference standard. For each variable, the mean difference (AI - reference) with 95% confidence intervals (CIs) and Bland-Altman plots were calculated. The intrareader repeatability of the manual reference was assessed with the ICC (3). For clinical interpretability, commonly accepted bands (angles ± 1-2°, linear ± 2 mm) were used.

resultsBoth AI systems showed systematic bias for key skeletal and dental measures. For CephX, SNA differed by + 3.40° (95% CI + 1.66 to + 5.14), SNB by + 5.88° (+ 4.33 to + 7.43), and ANB by - 2.48° (- 4.38 to - 0.58). For Invivo, SNA was + 5.07° (+ 2.40 to + 7.74), the SNB was + 4.40° (+ 2.64 to + 6.16), and the ANB was + 5.55° (+ 0.77 to + 10.33). Many parameters also had wide limits of agreement, indicating poor precision for individual patients. Several variables suggested proportional bias (greater discrepancy at larger values). The intrareader ICCs for the manual reference were 0.91-0.95. Overall, the 95% CIs for sentinel angles commonly exceed ± 2°, which argues against clinical interchangeability.

conclusionsIn their current form, the evaluated AI CBCT cephalometry tools do not match manual 2D cephalometry closely enough for standalone clinical use. Differences of 3-6° in the core sagittal angles are large enough to change the diagnosis and treatment plans. AI outputs should be reviewed and, when necessary, corrected by clinicians.

Indexed as

Artificial IntelligenceCephalometryCone-Beam Computed TomographyAdolescentAdultAnatomic LandmarksFemaleHumansImaging, Three-DimensionalIntelligent SystemsMaleReproducibility of ResultsRetrospective StudiesSoftwareYoung AdultArtificial intelligenceCBCTCephalometric analysisCephXIntraclass correlation coefficientInvivoOrthodontic diagnosis

Identifiers

PMID41758431
PMCPMC12949154

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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.