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NCT Number: NCT07842211

Feasibility and Validation of an Automated AI-Enabled Deep Ultraviolet (DUV) Cytology Platform for Point-of-Care Oral Cancer Triage

This research study evaluates an experimental, point-of-care tool that combines Deep Ultraviolet (DUV) light imaging with Artificial Intelligence (AI) to rapidly screen for oral cancer and pre-cancer (dysplasia).

The main goal is to determine if this automated tool can accurately deliver immediate, same-visit triage results (categorizing cells as either non-dysplasia or dysplasia/cancer) without needing chemical stains, sample transport, or off-site laboratory processing.

The following occurs during a singular clinic visit for participants:

1. Minimally Invasive Brush Test: A clinician gently rotates a soft brush over the mouth tissue to collect surface cells. 2. Stain-Free Imaging & AI Analysis: The DUV microscope scans the unstained cells in minutes, and the AI analyzes cell features (such as nucleus size and shape) in under 10 seconds. 3. Standard Medical Care: Participants with suspicious spots receive a standard tissue biopsy to ensure a definitive, confirmed diagnosis regardless of the AI result.

This is important given that the five-year survival rates for oral cancer exceed 80% when caught early but drop to under 20% if detected late. By delivering rapid results directly at the clinic, this technology aims to eliminate long waiting periods for lab results, accelerate specialist referrals, and improve access to early screening in community dental and medical clinics.

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Key information

Conditions

Oral Potentially Malignant Lesions Carcinoma Carcinoma, Squamous Cell Head and Neck Neoplasms Mouth Diseases Mouth Neoplasms Neoplasms Neoplasms by Histologic Type Neoplasms by Site Neoplasms, Glandular and Epithelial Oral Cancer Oral Cancer , Oral Squamous Cell Carcinoma, Oral Cavity Cancer Oral Potentially Malignant Disorders Squamous Cell Carcinoma of Head and Neck Stomatognathic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

University of Pennsylvania, Department of Oral & Maxillofacial Surgery/Pharmacology

Philadelphia, Pennsylvania, 19104, United States

About this study

This research project establishes a new diagnostic paradigm by transforming oral brush cytology from a centralized, laboratory-dependent procedure into an automated, AI-assisted point-of-care (POC) triage system. Traditional brush cytology relies on chemical staining, physical sample shipping, and off-site expert review, which can introduce diagnostic turnaround delays. By combining label-free optical imaging with automated hardware and deep learning, this system aims to deliver immediate, same-visit triage of suspicious oral lesions directly within primary dental and outpatient clinics.

Optical Physics & Optomechanical Engineering: The core imaging system utilizes Deep Ultraviolet (DUV) microscopy operating in the 200-280 nm spectral range. At these wavelengths, cellular nucleic acids and proteins exhibit strong intrinsic light absorption, enabling submicron-resolution, high-contrast visualization of nuclear architecture without chemical dyes or fluorescent stains.

Transformer-Based AI Framework (CellViT): Cellular analysis and classification are powered by an adapted CellViT deep learning framework, which replaces traditional object-detection architectures like YOLOv7.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Suspicious Lesions Cohort: Adults with suspicious oral potentially malignant lesions (OPML), such as leukoplakia, erythroplakia, or speckled lesions), oral precancer (dysplasia), or suspected oral/oropharyngeal squamous cell carcinoma (OSCC) who are scheduled for a diagnostic incisional or excisional tissue punch biopsy.
  • Healthy Volunteers Cohort: Clinically normal volunteers without suspicious oral mucosal lesions.

Exclusion criteria

  • Age: Individuals under 18 years of age.
  • Currently undergoing treatment for malignancy
  • Unwilling or unable to provide informed consent

Treatment and study plan

Deep UV-M and AI Cytology Triage

Device

Non-invasive oral brush cytology harvests full-thickness epithelial cells from suspicious lesions. Cells are smeared onto UV glass slides and fixed in 95% ethanol. Unstained slides are scanned on a point-of-care Deep UV Microscope (DUV-M). An adapted AI model performs per-cell instance segmentation, extracts nuclear morphometric features, and delivers a binary triage result (non-dysplasia vs. dysplasia/cancer).

Primary outcomes

  1. Triage Classification

    Time frame: From the time of oral brush cytology sampling on Day 1 through completion of the reference biopsy histopathology report, assessed up to 14 days post-procedure.

    The primary endpoint is the accurate binary triage classification (distinguishing non-dysplasia from dysplasia/cancer) performed by the AI DUV-M platform, compared against the reference standard of histopathology.

Secondary outcomes

  1. Three-Class Diagnostic Discrimination

    Time frame: From sample collection on Day 1 through completion of 3-class histopathological grading, assessed up to 14 days post-procedure.

    While the primary endpoint focuses on binary triage (non-dysplasia vs. dysplasia/cancer), the secondary analysis evaluates the AI framework's ability to discriminate samples across three distinct diagnostic categories: non-dysplasia, dysplasia, and invasive cancer.

Interested in participating?

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Sponsors and collaborators

Lead sponsor

Anh Le

Other

Collaborators

  • University of Arizona

Registry information

Acronym: DEEP UV-M

Important dates

Study start
2026
Primary completion
2028
Study completion
2028
First posted
Sep 25, 2026
Registry last updated
Sep 25, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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