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Not yet recruitingNCT07529769AID-OraLUpdated Apr 14, 2026

Artificial Intelligence for the Diagnosis of Oral Lesions

An observational study in Oral Potentially Malignant Disorders and Oral Cavity Squamous Cell Carcinoma, sponsored by Assistance Publique - Hôpitaux de Paris. Not yet recruiting. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-04-14.

Sponsored by Assistance Publique - Hôpitaux de Paris · Observational

Study type
Observational
Model
Cohort
Time perspective
Retrospective
Enrollment
5,000
Ages
18 Years and older
Sex
All
01

Study summary

Squamous cell carcinomas of the upper aerodigestive tract are among the most common cancers worldwide, with the oral cavity being the most frequent site. Oral cavity squamous cell carcinomas (OCSCC) represent a major cause of morbidity and mortality, mainly due to high rates of locoregional or metastatic recurrence and the frequent occurrence of second primary tumors. Unlike oropharyngeal squamous cell carcinomas, human papillomavirus (HPV) is not involved in the carcinogenesis of OCSCC.

In some cases, OCSCC develop from oral potentially malignant disorders (OPMDs), such as leukoplakia and erythroplakia, which have a worldwide incidence of 3-5%. The malignant transformation rate of OPMDs ranges from 3% to 50%, reflecting their marked heterogeneity. Although several clinical, histological, and molecular factors have been proposed to identify patients at high risk of malignant transformation, none have demonstrated sufficient clinical utility to date. In other cases, OCSCC arise from clinically normal oral mucosa in patients with OPMDs located at a distance and/or with established risk factors, particularly tobacco and alcohol use.

Currently, no chemopreventive or preventive strategy has been established as a standard of care to prevent malignant transformation of OPMDs. Improving the prognosis of OCSCC therefore requires the development of tools to better identify high-risk OPMDs and to enable the earliest possible diagnosis. Early detection of OPMDs is essential for secondary prevention of OCSCC. However, conventional oral examination based on visual inspection and palpation has limited sensitivity, and clinical recognition of OPMDs remains challenging. Consequently, there is a clear need for improved methods to enhance early detection and risk stratification of OPMDs.

Main objective:

To develop a tool to aid in the diagnosis of cancerous lesions in the oral cavity using Artificial Intelligence (AI). This tool appears promising in meeting the current needs of the oral cavity practitioner community.

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Conditions studied

  • Oral Potentially Malignant Disorders
  • Oral Cavity Squamous Cell Carcinoma

Keywords

  • Oral Potentially Malignant Disorders
  • Oral Cavity Squamous Cell Carcinoma
  • diagnosis
  • oral cancer
  • Artificial Intelligence
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In context

Squamous Cell Carcinoma of Head and Neck

1,680 studies on the registry are indexed under Squamous Cell Carcinoma of Head and Neck; 539 are open to participants now.

This study's planned enrollment of 5,000 is above the median of 100 across 179 observational studies indexed under Squamous Cell Carcinoma of Head and Neck.

Browse Squamous Cell Carcinoma of Head and Neck studies →

Lead sponsor

Assistance Publique - Hôpitaux de Paris is the lead sponsor of 3,505 studies on the registry; 1,006 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Patients followed in the Department of Oral Mucosal Pathology (Maxillofacial Surgery and Stomatology Department, Pitié-Salpêtrière Hospital, AP-HP, Paris) from January 1, 1970, to December 31, 2023, with a diagnosis of potentially malignant oral lesions and/or oral cavity cancer.

Inclusion criteria

  • Patient aged ≥ 18 years
  • Patients followed up in the Oral Mucosa Pathology Department (Maxillofacial Surgery and Stomatology Department, Pitié-Salpêtrière Hospital, AP-HP, Paris) between January 1, 1970, and December 31, 2023, with a diagnosis of potentially malignant oral lesion and/or oral cavity cancer.

Exclusion criteria

Exclusion Criteria:

  • Photograph of the lesion unavailable (in standard care)
05

Study design

Observational model
Cohort
Time perspective
Retrospective
Enrollment
5,000 participants (estimated)
Patient registry
No
06

What researchers measure

Primary outcomes

  1. Develop a tool to aid in the diagnosis of cancerous lesions in the oral cavity using Artificial Intelligence (AI)

    To develop a tool to aid in the diagnosis of cancerous lesions in theoral cavity using Artificial Intelligence (AI). This tool appears promisingin meeting the current needs of the oral cavity practitioner community. To achieve this objective, anonymized clinical photographs of oral lesions, along with relevant clinical data routinely recorded in medical charts, will be collected. All photographs will undergo retrospective review by experienced specialists in oral and maxillofacial surgery. The experts will independently assess the images and establish a reference diagnosis. In cases of disagreement, a consensus diagnosis will be reached. The complete dataset, including image data, associated clinical variables, and reference diagnoses, will be used to develop and internally validate a machine learning algorithm for the automated classification of oral lesions

    Time frame: Through study completion, an average of 9 months

07

Study locations

No study locations are listed for this record.

08

References and documents

Individual participant data

Plan to share: Yes

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Apr 14, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07529769
Lead sponsor
Assistance Publique - Hôpitaux de Paris
Collaborators
BPIfrance, Institut Universitaire de Cancérologie, Sorbonne University, Health Data Hub (France)
Responsible party
Sponsor
First posted
Apr 14, 2026
Start date
Apr 2026 (estimated)
Primary completion
Dec 2026 (estimated)
Completion
Dec 2026 (estimated)
Last update
Apr 14, 2026

Study contacts

Jebrane BOUAOUD, MD, PhD
Contact
jebrane.bouaoud@aphp.fr
33142161301
Jinmi BAEK
Contact
jinmi.baek@aphp.fr
331 42 16 11 32

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is not yet recruiting, as verified in Apr 2026. You cannot join it, but the record below documents what was studied.

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