Evaluation of Artificial Intelligence in Diagnosis and Risk Assessment of Oral Potentially Malignant Disorders

NCT07318922 | Not Yet Recruiting

• 1 other identifier: FDASU-Rec IM 112301
• Study Type: observational
• Target: 120
• Locations: 0 countries
• Sites: N/A

Brief Summary

Oral potentially malignant disorders (OPMDs) are mucosal lesions that carry a risk of malignant transformation into oral cancer. Unfortunately, a general lack of knowledge and awareness of OPMDs is common among general dental practitioners. While thorough clinical examinations coupled with biopsy can identify most OPMDs, the absence of reliable non-invasive diagnostic tools and standardized risk stratification often delays early diagnosis and treatment of oral squamous cell carcinoma (OSCC).Early detection of suspicious oral lesions is crucial for reducing OSCC-related mortality and improving patient outcomes. Histopathological assessment of biopsied tissue remains the gold standard for diagnosis. However, since biopsy is invasive and may be associated with patient discomfort; numerous noninvasive diagnostic technologies have emerged to enhance the detection and diagnosis of oral mucosal lesions.Toluidine blue (TB) staining is one such adjunctive tool, where the degree of color retention aids in lesion characterization. Dark blue staining is considered positive for lesions highly suspicious for malignancy; light blue retention is considered positive for premalignant lesions pending histopathological confirmation, while lesions showing no stain retention are classified as negative.Exfoliative cytology represents another non-invasive diagnostic approach, wherein cells obtained via brushing the oral mucosa are spread on a slide for cytological evaluation. This technique, widely accepted and increasingly utilized, has proven valuable for early cancer detection. Notably, confocal microscopy has demonstrated high sensitivity and specificity (93%) in detecting malignant cells in exfoliative cytology specimens. Currently, TB staining and confocal microscopy remain the most commonly utilized non-invasive screening techniques in clinical practice.In recent years, artificial intelligence (AI) applications have shown remarkable promise in oncology, achieving high diagnostic accuracy across various cancer types. Deep learning models, in particular, offer exceptional performance, suggesting that AI-based solutions may be feasible for widespread community screening programs following further validation. In many cases, AI models have produced diagnostic outcomes that match or surpass those of experienced pathologists. Moreover, the combined application of AI with expert human evaluation has been shown to reduce diagnostic errors and improve diagnostic precision, particularly for poorly differentiated tumors and rare cases.Several studies have been done using different AI Models and revealed a promising application of AI in diagnosing OPMDs and cancers in different body sites.

Conditions

Oral Lichen Planus; Oral Leukoplakia; Traumatic Ulcer of Oral Mucosa; Erythroleukoplakia of Mouth

Keywords

OPMDs; Artificial Intelligence; Toluidine blue stain; Confocal microscope; Exfoliative Cytology; Acridine orange stain; Tissue biopsy

Outcome Measures

Primary Outcomes (2)

• Comparing accuracy, sensitivity and specificity of the model with specialist's opinion for the same datasets.

  1 year

• Developing a machine learning model to identify, categorise, and evaluate the risk of oral potentially malignant disorders using datasets of personal criteria, clinical digital photographs and confocal microscopic images of exfoliative cytological smears

  1 year

Interventions

Toluidine blue staining of the lesion and cytological smears DIAGNOSTIC_TEST

Staining lesions with toluidine blue stain and Exfoliative cytological smears

Eligibility Criteria

• Age: 30 Years - 75 Years
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients with oral lesions has Potential Malignant transformation

You may qualify if:

• Patients have no signs of super infection of candida on the lesions. 2- A lesion with a provisional clinical diagnosis of (OLP, OLK, OEP, non-healing ulcers) at any site in the oral cavity (buccal mucosa, hard palate, labial mucosa, tongue, gingiva).

You may not qualify if:

• Any other mucosal lesions.

Sponsors & Collaborators

• Ain Shams University: lead

Biospecimen

Retention: SAMPLES WITHOUT DNA

Oral cytological smears on microscopic slides

MeSH Terms

Conditions

Lichen Planus, Oral; Leukoplakia, Oral

Condition Hierarchy (Ancestors)

Mouth Diseases; Stomatognathic Diseases; Lichen Planus; Lichenoid Eruptions; Skin Diseases, Papulosquamous; Skin Diseases; Skin and Connective Tissue Diseases; Mouth Neoplasms; Head and Neck Neoplasms; Neoplasms by Site; Neoplasms; Leukoplakia; Precancerous Conditions; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms

Study Officials

• Ali

  Ain Shams University

  STUDY CHAIR

Central Study Contacts

Aya Mostafa Ali, Bachelor of dentistry

CONTACT

+20 01140126541; ayamms1591997@gmail.com

Ola Mohammed Ezzatt, Doctoral in oral medicine

CONTACT

+20 12 87944769; Dr.ola@asfd.asu.edu.eg

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 20, 2025
• First Posted: January 6, 2026
• Study Start: December 16, 2025
• Primary Completion (Estimated): November 22, 2026
• Study Completion (Estimated): December 20, 2026
• Last Updated: January 6, 2026

Record last verified: 2025-11