Artificial Intelligence for the Diagnosis of Oral Lesions

NCT07529769 | Not Yet Recruiting

• 2 other identifiers: APHP251103CEth-SCOMFS 003/2025
• Study Type: observational
• Target: 5,000
• Locations: 0 countries
• Sites: N/A

Brief 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

Keywords

Oral Potentially Malignant Disorders; Oral Cavity Squamous Cell Carcinoma; diagnosis; oral cancer; Artificial Intelligence

Outcome Measures

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

  Through study completion, an average of 9 months

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• 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.

You may qualify if:

• 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.

You may not qualify if:

• Photograph of the lesion unavailable (in standard care)

Sponsors & Collaborators

• Health Data Hub (France): collaborator
• Assistance Publique - Hôpitaux de Paris: lead
• BPIfrance: collaborator
• Institut Universitaire de Cancérologie, Sorbonne University: collaborator

MeSH Terms

Conditions

Squamous Cell Carcinoma of Head and Neck; Disease; Mouth Neoplasms

Condition Hierarchy (Ancestors)

Carcinoma, Squamous Cell; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Head and Neck Neoplasms; Neoplasms by Site; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Mouth Diseases; Stomatognathic Diseases

Central Study Contacts

Jebrane BOUAOUD, MD, PhD

CONTACT

33142161301; jebrane.bouaoud@aphp.fr

Jinmi BAEK

CONTACT

331 42 16 11 32; jinmi.baek@aphp.fr

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 5, 2026
• First Posted: April 14, 2026
• Study Start: April 1, 2026
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: April 14, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will share