Artificial Intelligence-assisted Screening of Malignant Pigmented Tumors on the Ocular Surface

NCT ID: NCT05645341

Last Updated: 2024-08-05

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 535 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-12-05
• Study Completion Date: 2023-06-05

Brief Summary

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

Orbital Neoplasms; Conjunctival Neoplasms; Eye Neoplasms

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Eligible participants for smartphone-based ocular surface tumors diagnosis

screening system for ocular surface malignant tumors

Intervention Type: DIAGNOSTIC_TEST

Develop an intelligent screening system for ocular surface malignant tumors, apply it to the mobile terminal for real-world verification and large-scale general screening, and test its effect on assisting doctors in the diagnosis and treatment of rare diseases.

Interventions

screening system for ocular surface malignant tumors

Develop an intelligent screening system for ocular surface malignant tumors, apply it to the mobile terminal for real-world verification and large-scale general screening, and test its effect on assisting doctors in the diagnosis and treatment of rare diseases.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

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.

• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Sun Yat-sen University

OTHER

Sponsor Role: lead

Responsible Party

Haotian Lin

Clinical Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Zhognshan Ophthalmic Center, Sun Yat-sen University

Guangzhou, Guangdong, China

Countries

China

Other Identifiers

2022KYPJ067

Identifier Type: -

Identifier Source: org_study_id