Clinical trial · Observational
Artificial Intelligence-assisted Screening of Malignant Pigmented Tumors on the Ocular Surface
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Rare diseases generally refer to diseases whose prevalence rate is lower than 1 / 10 000 and the number of patients is less than 140000. Rare diseases are generally faced with the dilemma of a lack of qualified doctors, difficulty in large-scale screening, and a lack of rapid and effective channels for medical treatment. Studies have shown that 42% of patients say they have been misdiagnosed, and each patient with a rare disease needs to go through an average of eight doctors in seven years to see a corresponding rare disease specialist. More importantly, most rare diseases seriously affect the health and quality of life of patients. The ocular surface malignant tumor is a typical rare disease, and its incidence is less than 1 / 100000. The ocular surface not only affects the patient's appearance, but also damages the visual function, and the malignant tumor may even affect life. These uncommon malignant tumors are often hidden in the common black nevus on the eye surface, which is easy to be ignored and has great potential risks. With the improvement of people's living standards, people start to pay attention to rare diseases. In recent years, the rapid development of digital technology has also provided new opportunities for the prevention and treatment of rare diseases. Our team established the database of rare ophthalmopathy in China in the early stage, which provided a solid foundation for the digitization of precious clinical data. This study intends to develop an intelligent screening system for ocular surface malignant tumors, using the mobile phone for real-world verification and scale screening, and explore it to improve the ability of doctors to diagnose and treat rare diseases. This study is expected to improve the ability to screen malignant tumors on the ocular surface and provide a novel model for the universal screening of rare diseases.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Conjunctival Neoplasms | Conjunctival Neoplasm | ONTOLOGY_EXACT | 0.98 |
| Eye Neoplasms | Eye Neoplasm | ONTOLOGY_EXACT | 0.98 |
| Orbital Neoplasms | Orbital Neoplasm | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| screening system for ocular surface malignant tumors | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Eligible participants for smartphone-based ocular surface tumors diagnosis
- interventionNames
- Diagnostic Test: screening system for ocular surface malignant tumors
Primary outcomes (1)
- measure
- Area under the curve (AUC)
- timeFrame
- 2024.1
- description
- Measure of the ability of a binary classifier to distinguish between malignent and benign.
Secondary outcomes (4)
- measure
- Sensitivity, specificity and accuracy
- timeFrame
- 2024.1
- description
- The study will assess the sensitivity and specificity of the CaptureTumor (CaT) system under various conditions.
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * Dark-brown lesions on the ocular surface are found: i.e. ocular surface malignant melanoma, ocular basal cell carcinoma, conjunctival nevus, eyelid nevus, sclera pigmentation, benign eyelid keratosis Exclusion Criteria: * Non-pigmented ocular surface tumors: pterygium, corneal dermoid tumor, meibomian gland cyst, cataract, blepharitis, etc. * The image quality does not meet the clinical requirements.
References
Publications (1)
- DERIVEDWang R, Bi S, Lin D, Li M, Zhao L, Zhou Y, Jin L, Chen W, Li R, Shang Y, Yang H, Chen R, Xiao W, Ai S, Li J, Ling S, Wu X, Li Z, Liu G, Lu Y, Lin W, Rao H, Meng X, Yan H, Nie C, Zhu M, Ye H, Lin H. Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies: A Nonrandomized Clinical Trial. JAMA Ophthalmol. 2026 Jul 1;144(7):627-635. doi: 10.1001/jamaophthalmol.2026.1609. PMID 42240998