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Clinical Trials/NCT05645341
NCT05645341
Completed
Not Applicable

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

Sun Yat-sen University1 site in 1 country535 target enrollmentDecember 5, 2022

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Orbital Neoplasms
Sponsor
Sun Yat-sen University
Enrollment
535
Locations
1
Primary Endpoint
Area under the curve (AUC)
Status
Completed
Last Updated
last year

Overview

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.

Registry
clinicaltrials.gov
Start Date
December 5, 2022
End Date
June 5, 2023
Last Updated
last year
Study Type
Observational
Sex
All

Investigators

Sponsor
Sun Yat-sen University
Responsible Party
Principal Investigator
Principal Investigator

Haotian Lin

Clinical Professor

Sun Yat-sen University

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.

Outcomes

Primary Outcomes

Area under the curve (AUC)

Time Frame: 2024.1

Measure of the ability of a binary classifier to distinguish between malignent and benign.

Secondary Outcomes

  • Screening coverage(2024.1)
  • Sensitivity, specificity and accuracy(2024.1)
  • Referral efficiency(2024.1)
  • Human-machine collaboration performance(2024.1)

Study Sites (1)

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