Evidence map›Paper›PMID 42138623›Full record

ArticleTheScientificWorldJournal2026

Evaluation of Arch Dimensions and Bolton Ratio in Manual and Artificial Intelligence Tooth Segmentation.

Sara M Al-Mashhadany, Dheaa Al-Groosh, Ammar Sh Al-Ubaydi

Abstract read
In one paragraph

Article in TheScientificWorldJournal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

3 authors.

Sara M Al-MashhadanyOrthodontic Department, College of Dentistry, University of Baghdad, Baghdad, Iraq, uobaghdad.edu.iq.ORCID https://orcid.org/0000-0002-3219-399X
Dheaa Al-GrooshOrthodontic Department, College of Dentistry, University of Baghdad, Baghdad, Iraq, uobaghdad.edu.iq.ORCID https://orcid.org/0000-0003-0052-7286
Ammar Sh Al-UbaydiOrthodontic Department, Ministry of Health, Baghdad, Iraq, behdasht.gov.ir.ORCID https://orcid.org/0009-0002-6847-837X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveA 3D tooth model segmented with the use of deep learning (DL) method program (CephX) as well as MIMICS software (manual segmentation) will be evaluated for reliability in the presented work. In addition, the segmented model was compared with the intraoral scan (IOS)-generated 3D tooth model in terms of the Bolton ratio and arch dimensions. METHODS AND MATERIALS: A total of 30 patients attending the College of Dentistry/University of Baghdad with records of IOSs and CBCT scans were included. CBCT has been transformed into a 3D digital tooth model segmented with the use of MIMICS software and an AI-based program (CephX), and the Bolton ratio and arch dimensions (length and width) were measured utilizing Geomagic Control X software. Statistical analyses, including the mean and standard deviation, were performed, and a paired t-test was used to assess the systematic bias between the three methods. Bland-Altman plots and intraclass correlation (ICC) analysis were used to assess the agreement between the three methods.

resultsThe means of CephX, MIMICS, and IOS of all analyses were mostly similar, and the difference between them was greatest in the anterior Bolton ratio of IOS and CephX images. The systematic bias demonstrated no significant difference (p value > 0.05) between CephX and MIMICS, but CephX versus IOS and MIMICS versus IOS demonstrated significant differences (p value < 0.05) in several measurements, such as Bolton ratios and arch length. Agreement using ICC revealed good to excellent reliability overall, but moderate agreement in overall Bolton between MIMICS-IOS and between CephX-IOS, anterior Bolton and interpremolar distance between CephX-MIMICS, and poor agreement in anterior Bolton between MIMICS-IOS and between CephX-IOS was found. Bland-Altman plots showed that CephX and MIMICS were consistent, implying minimal systematic bias.

conclusionsDigital and AI-driven tooth segmentation (MIMICS and CephX), and IOS methods generally provide consistent and reliable measurements in terms of the Bolton ratio and arch dimensions. However, caution is advised when interpreting certain Bolton ratio values because discrepancies and lower agreement may occur.

Indexed as

Artificial IntelligenceDental ArchImaging, Three-DimensionalToothCone-Beam Computed TomographyHumansReproducibility of ResultsSoftwarearch dimensionartificial intelligenceBolton ratiosegmentation

Identifiers

PMID42138623
PMCPMC13178285

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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.