[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100657750":3},{"organization":4,"outcomesModule":7,"designInfo":19,"detailedDescription":25,"studyPopulation":18,"armGroups":26,"interventions":33,"overallOfficials":39,"centralContacts":43,"locations":52,"responsibleParty":70,"collaborators":74,"id":77,"slug":78,"hasResults":79,"nctId":80,"briefTitle":81,"officialTitle":81,"acronym":82,"eligibilityCriteria":83,"healthyVolunteers":84,"sex":85,"minAge":86,"maxAge":18,"enrollmentInfo":87,"targetDuration":18,"studyType":90,"phases":91,"briefSummary":92,"conditions":93,"keywords":98,"overallStatus":103,"whyStopped":18,"lastUpdateSubmitDate":104,"lastUpdatePostDateStruct":105,"startDateStruct":108,"completionDateStruct":110,"leadSponsor":112,"locationsCount":113},{"fullName":5,"class":6},"University of Pennsylvania","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":18},[9],{"measure":10,"description":11,"timeFrame":12},"Triage Classification","The primary endpoint is the accurate binary triage classification (distinguishing non-dysplasia from dysplasia\u002Fcancer) performed by the AI DUV-M platform, compared against the reference standard of histopathology.","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.",[14],{"measure":15,"description":16,"timeFrame":17},"Three-Class Diagnostic Discrimination","While the primary endpoint focuses on binary triage (non-dysplasia vs. dysplasia\u002Fcancer), the secondary analysis evaluates the AI framework's ability to discriminate samples across three distinct diagnostic categories: non-dysplasia, dysplasia, and invasive cancer.","From sample collection on Day 1 through completion of 3-class histopathological grading, assessed up to 14 days post-procedure.",null,{"allocation":20,"interventionModel":21,"interventionModelDescription":18,"primaryPurpose":22,"observationalModel":18,"timePerspective":18,"maskingInfo":23},"NA","SINGLE_GROUP","DIAGNOSTIC",{"masking":24,"maskingDescription":18,"whoMasked":18},"NONE","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.\n\nOptical 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.\n\nTransformer-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.",[27],{"label":28,"type":29,"description":30,"interventionNames":31},"AI-Enabled Deep UV Brush Cytology with Biopsy Validation","EXPERIMENTAL","Participants with suspicious oral lesions undergo a quick, non-invasive oral brush test analyzed in real time by the experimental Deep UV AI platform. Immediately after, participants receive the routine 5 mm tissue biopsy to confirm their diagnosis. The AI scan result is compared directly against the biopsy pathology to measure the AI's diagnostic accuracy.",[32],"Device: Deep UV-M and AI Cytology Triage",[34],{"type":35,"name":36,"description":37,"armGroupLabels":38,"otherNames":18},"DEVICE","Deep UV-M and AI Cytology Triage","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\u002Fcancer).",[28],[40],{"name":41,"affiliation":5,"role":42},"Anh D Le, DDS, PhD","PRINCIPAL_INVESTIGATOR",[44,49],{"name":45,"role":46,"phone":47,"phoneExt":18,"email":48},"Annachristine Hoover","CONTACT","310-560-7767","annachristine.hoover@pennmedicine.upenn.edu",{"name":41,"role":46,"phone":50,"phoneExt":18,"email":51},"215-662-6176","anh.le@pennmedicine.upenn.edu",[53],{"facility":54,"status":18,"city":55,"state":56,"zip":57,"country":58,"countryCode":59,"cosmosGeoPoint":60,"geoPoint":65,"contacts":66},"University of Pennsylvania, Department of Oral & Maxillofacial Surgery\u002FPharmacology","Philadelphia","Pennsylvania","19104","United States","US",{"type":61,"coordinates":62},"Point",[63,64],-75.16362,39.95238,{"lat":64,"lon":63},[67,68],{"name":45,"role":46,"phone":47,"phoneExt":18,"email":48},{"name":69,"role":46,"phone":50,"phoneExt":18,"email":51},"Anh Le, DDS, PhD",{"type":71,"investigatorFullName":72,"investigatorTitle":73,"investigatorAffiliation":5,"oldNameTitle":18,"oldOrganization":18},"SPONSOR_INVESTIGATOR","Anh Le","Norman Vine Endowed Professor and Department Chair",[75],{"name":76,"class":6},"University of Arizona","100657750","feasibility-and-validation-of-an-automated-ai-enabled-deep-ultraviolet-duv-cytology-platform-for-point-of-care-oral-cancer-triage-100657750",false,"NCT07842211","Feasibility and Validation of an Automated AI-Enabled Deep Ultraviolet (DUV) Cytology Platform for Point-of-Care Oral Cancer Triage","DEEP UV-M","Inclusion Criteria:\n\n* Suspicious Lesions Cohort: Adults with suspicious oral potentially malignant lesions (OPML), such as leukoplakia, erythroplakia, or speckled lesions), oral precancer (dysplasia), or suspected oral\u002Foropharyngeal squamous cell carcinoma (OSCC) who are scheduled for a diagnostic incisional or excisional tissue punch biopsy.\n* Healthy Volunteers Cohort: Clinically normal volunteers without suspicious oral mucosal lesions.\n\nExclusion Criteria:\n\n* Age: Individuals under 18 years of age.\n* Currently undergoing treatment for malignancy\n* Unwilling or unable to provide informed consent",true,"ALL","18 Years",{"count":88,"type":89},270,"ESTIMATED","INTERVENTIONAL",[20],"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).\n\nThe 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\u002Fcancer) without needing chemical stains, sample transport, or off-site laboratory processing.\n\nThe following occurs during a singular clinic visit for participants:\n\n1. Minimally Invasive Brush Test: A clinician gently rotates a soft brush over the mouth tissue to collect surface cells.\n2. 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.\n3. Standard Medical Care: Participants with suspicious spots receive a standard tissue biopsy to ensure a definitive, confirmed diagnosis regardless of the AI result.\n\nThis 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.",[94,95,96,97],"Oral Potentially Malignant Lesions","Oral Potentially Malignant Disorders","Oral Cancer , Oral Squamous Cell Carcinoma, Oral Cavity Cancer","Oral Cancer",[99,100,101,102],"oral cancer","oral squamous cell carcinoma","oral cavity cancer","oral potentially malignant lesions","NOT_YET_RECRUITING","2026-09-21",{"date":106,"type":107},"2026-09-25","ACTUAL",{"date":109,"type":89},"2026-12-01",{"date":111,"type":89},"2028-12",{"name":72,"class":6},1]