Evidence map›Paper›PMID 41748575›Full record

ArticleScientific data2026

A dataset of midpalatal suture maturation stage in cone-beam computed tomography.

Zhigang Zuo, Bosha Jia, Yutong Xiao, Yi Hua, Yunlong Zhang, Jianing Li, Leyu Zhang, Zhengjian Guo, Shijie Zhang, Yue Wang

Abstract readDataset
In one paragraph

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

0numbers the graph read from it
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

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

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

10 authors.

Zhigang Zuo *Department of Orthodontics, Tianjin Medical University School and Hospital of Stomatological & Tianjin Key Laboratory of Oral Soft and Hard Tissues Restoration and Regeneration, No.12 Qixiangtai Road, Heping District, Tianjin, 300070, P. R. China.
Bosha Jia *Department of Orthodontics, Tianjin Medical University School and Hospital of Stomatological & Tianjin Key Laboratory of Oral Soft and Hard Tissues Restoration and Regeneration, No.12 Qixiangtai Road, Heping District, Tianjin, 300070, P. R. China.
Yutong Xiao *Department of Pharmacology and Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, P. R. China.
Yi HuaDepartment of Pharmacology and Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, P. R. China.
Yunlong ZhangTianjin Medical University Institute of Stomatology, No.12 Qixiangtai Road, Heping District, Tianjin, 300070, P. R. China.
Jianing LiDepartment of Orthodontics, Tianjin Medical University School and Hospital of Stomatological & Tianjin Key Laboratory of Oral Soft and Hard Tissues Restoration and Regeneration, No.12 Qixiangtai Road, Heping District, Tianjin, 300070, P. R. China.
Leyu ZhangDepartment of Orthodontics, Tianjin Medical University School and Hospital of Stomatological & Tianjin Key Laboratory of Oral Soft and Hard Tissues Restoration and Regeneration, No.12 Qixiangtai Road, Heping District, Tianjin, 300070, P. R. China.
Zhengjian GuoDepartment of Orthodontics, Tianjin Medical University School and Hospital of Stomatological & Tianjin Key Laboratory of Oral Soft and Hard Tissues Restoration and Regeneration, No.12 Qixiangtai Road, Heping District, Tianjin, 300070, P. R. China.
Shijie ZhangDepartment of Pharmacology and Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, P. R. China. shijie.zhang@tmu.edu.cn.
Yue WangDepartment of Orthodontics, Tianjin Medical University School and Hospital of Stomatological & Tianjin Key Laboratory of Oral Soft and Hard Tissues Restoration and Regeneration, No.12 Qixiangtai Road, Heping District, Tianjin, 300070, P. R. China. wangyue1@tmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the field of orthodontics, the degree of fusion of the midpalatal suture (MPS) is a crucial factor in determining the most appropriate maxillary expansion technique. This study analyzed 600 cone-beam computed tomography (CBCT) scans from patients aged 4 to 25, covering all MPS maturity stages (35 in stage A, 113 in stage B, 186 in stage C, 163 in stage D, and 103 in stage E). A custom model integrated 3D convolutional neural networks (3D CNNs) for processing image data and fully connected networks for handling tabular data to classify MPS stages. Key factors including gender, age, cervical vertebra staging, dental age, palatal morphology, and MPS bone density ratio were evaluated for their correlation with MPS fusion. Ethical approval was secured, and images were quality-assessed by orthodontists and a maxillofacial imaging physician. The model shows great performance in the diagnosis with AUC over 0.95. The model aids in selecting appropriate expanders, favoring traditional rapid palatal expansion (RME) for unclosed MPS and bone-anchored RME or surgery for fused cases.

Indexed as

Cone-Beam Computed TomographyCranial SuturesPalateChildChild, PreschoolConvolutional Neural NetworksFemaleHumansImaging, Three-DimensionalMalePalatal Expansion Technique

Identifiers

PMID41748575
PMCPMC13057253

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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.