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Artificial Intelligence for the Diagnosis of Oral Lesions

NCT07529769 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 5000

Last updated 2026-04-14

No results posted yet for this 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.

Conditions

  • Oral Potentially Malignant Disorders
  • Oral Cavity Squamous Cell Carcinoma

Sponsors & Collaborators

  • BPIfrance

    collaborator OTHER

  • Institut Universitaire de Cancérologie, Sorbonne University

    collaborator UNKNOWN

  • Health Data Hub (France)

    collaborator UNKNOWN

  • Assistance Publique - Hôpitaux de Paris

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-04-30
Primary Completion
2026-12-31
Completion
2026-12-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07529769 on ClinicalTrials.gov