Evidence map›Paper›PMID 42134189›Full record

ArticleInternational dental journal2026

Non-Invasive Screening of AI-Assisted DNA Aneuploidy Cytology by Image Cytometry for the Early Diagnosis of Malignant Transformation of OPMDs.

Ya-Qin Tan, Feng Wang, Xu-Ya Chen, Xin-Xin Huang, Xin-Yi Wei, Rui Lu, Xiao-Jie Chen, Ge-Fei Du, Fang Wang, Ming-Jing He and 2 more

Abstract read
In one paragraph

Article in International dental journal, 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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1 · What the graph read from it

What it found

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2 · The registry

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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

12 authors.

Ya-Qin TanState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China.
Feng WangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Xu-Ya ChenState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Xin-Xin HuangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Xin-Yi WeiState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Rui LuState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China.
Xiao-Jie ChenState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China.
Ge-Fei DuState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China.
Fang WangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China.
Ming-Jing HeState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China.
Jing ZhangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China. Electronic address: zhangjing.ss@whu.edu.cn.
Gang ZhouState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China; Department of Oral Medicine, School and Hospital of Stomatology, Wuhan University, China. Electronic address: zhougang@whu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

INTRODUCTION AND

aimsOral exfoliative DNA aneuploidy cytology by image cytometry (DNA-ICM) has been introduced for the early diagnosis of malignant transformation. This study aimed to investigate the optimal cut-off values of DNA content and assess the diagnostic accuracy of artificial intelligence (AI)-assisted DNA-ICM for detecting the risk of malignant transformation in oral potentially malignant disorders (OPMDs).

methodsA total of 6,874 consecutive patients with clinical lesions of OPMDs were subjected to AI-assisted DNA-ICM analysis. In this study, both oral exfoliative cytobrushing and surgical biopsy samples were obtained from 415 patients with OPMDs and then allocated by AI-assisted DNA-ICM and histopathological examination, respectively. The diagnostic efficiency and accuracy of AI-assisted DNA-ICM analysis were evaluated in this OPMDs cohort. Fisher's exact test was applied to evaluate differences in qualitative variables. Logistic regression analysis was used to estimate the odds ratio (OR) and the associations among confounding variables.

resultsFor the optimal cut-off values of at least 1 aneuploid cell with DNA content ≥4.86c, the area under the curve (AUC) was 0.840 (sensitivity, 76.19%; specificity, 74.40%) for the discrimination of dysplasia from OPMDs. For the DNA content ≥6.2c, the AUC was 0.766 (sensitivity, 80.52%; specificity, 64.38%) for detecting carcinoma from OPMDs. Notably, OR analysis by logistic regression suggested that ages ≥60 years and the areca nut chewing habit were significantly associated with dysplasia or worse in OPMDs. In addition, DNA aneuploidy criteria and their diagnostic accuracy vary among different subtypes of OPMDs.

conclusionThis diagnostic study optimised the criteria of DNA aneuploidy cytology for detecting malignant transformation of OPMDs. AI-assisted DNA-ICM may be an efficient noninvasive diagnostic tool for screening different high-risk OPMDs and early-stage oral cancers. CLINICAL RELEVANCE: This clinicopathological diagnostic study establishes a methodological foundation for future broader screening applications of oral exfoliative AI-assisted DNA-ICM.

Indexed as

AneuploidyArtificial IntelligenceCell Transformation, NeoplasticEarly Detection of CancerImage CytometryMouth NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedSensitivity and SpecificityArtificial intelligence DNA aneuploidy cytology Image cytometry Oral potentially malignant disorders Malignant transformation

Identifiers

PMID42134189
PMCPMC13196354

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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.