Effectiveness and Cost-Effectiveness Evaluations of AI-Assisted Diagnostic Software (VeriSee) for Ophthalmic Disease Screening

NCT06843499 | Recruiting DMC

• 1 other identifier: 202412086DINC
• Study Type: interventional
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to evaluate the effectiveness of an artificial intelligence (AI)-assisted screening system in ophthalmic diagnosis. Using AI-based fundus photography, the system will assist physicians in diagnosing three common eye diseases: age-related macular degeneration and diabetic retinopathy (DR). The AI system will analyze fundus images from participants and rapidly generate detection results for ophthalmologists' reference in making final diagnoses and clinical decisions. The study will assess the clinical benefits of the AI-assisted diagnostic system, providing scientific evidence to enhance the efficiency of ophthalmic disease diagnosis and treatment.

Conditions

Age-Related Macular Degeneration (AMD); Diabetic Retinopathy (DR)

Keywords

Artificial Intelligence; imaging analysis; disease diagnosis; macular degeneration; diabetic retinopathy

Outcome Measures

Primary Outcomes (3)

• Sensitivity

  The sensitivity of the index test (VeriSee) was calculated as the proportion of participants with reference standard-confirmed disease who were correctly identified as positive by the AI-assisted diagnostic software.

  From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month

• Specificity

  The specificity of the index test was calculated as the proportion of participants without the target condition, as determined by the reference standard, who were correctly classified as negative by the AI-assisted diagnostic tool.

  From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month

• Concordance

  Concordance between the AI-assisted diagnosis and the ophthalmologists' interpretation was assessed using the overall agreement rate (i.e., the percentage of cases with identical classification results).

  From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month

Secondary Outcomes (1)

• Total Cost Analysis (Including Direct and Indirect Costs)

  From enrollment to 12 months after screening

Study Arms (1)

AI Intervention

OTHER

Patients will undergo fundus photography screening using artificial intelligence-assisted diagnostic software (VeriSee). Ophthalmologists will independently interpret the same images, and the results will be compared with those generated by the AI.

Other: The VeriSee AI-assisted diagnostic system; Other: Data collection from the patient's clinical history

Interventions

The VeriSee AI-assisted diagnostic system OTHER

VeriSee AMD, VeriSee DR, and VeriSee GLC are AI-based medical software devices designed for screening age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma, respectively. These systems utilize advanced AI algorithms to analyze color fundus photography images for disease assessment. By installing the software on a computer, the system can evaluate image quality, predict disease conditions, and instantly provide results to clinical physicians, serving as a diagnostic aid.

AI Intervention

Data collection from the patient's clinical history OTHER

Data collection from the patient's clinical history was conducted because the VeriSee AI-assisted diagnostic system was not used.

AI Intervention

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• VeriSee AMD is used in non-retinal subspecialty ophthalmology clinics for adults aged 50 and above.
• VeriSee DR is used in non-retinal subspecialty clinics for diabetic patients aged 20 and above.

You may not qualify if:

• The patient does not agree to participate in the trial or is unable to provide informed consent.

Sponsors & Collaborators

• National Taiwan University Hospital: lead
• Fu Jen Catholic University Hospital: collaborator
• Min-Sheng General Hospital: collaborator
• Ministry of Health and Welfare, Taiwan: collaborator

Study Sites (1)

National Taiwan University Hospital

Taipei, Taiwan, 100225, Taiwan

RECRUITING

MeSH Terms

Conditions

Macular Degeneration; Diabetic Retinopathy

Condition Hierarchy (Ancestors)

Retinal Degeneration; Retinal Diseases; Eye Diseases; Diabetic Angiopathies; Vascular Diseases; Cardiovascular Diseases; Diabetes Complications; Diabetes Mellitus; Endocrine System Diseases

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: SCREENING
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: This trial is expected to use a diagnostic accuracy study to test the effectiveness of the VeriSee system in assisting ophthalmologists in diagnosis, and compare it with the traditional method of ophthalmologists making their own diagnosis through fundus photography to evaluate its sensitivity and specificity.

Study Record Dates

• First Submitted: February 20, 2025
• First Posted: February 25, 2025
• Study Start: June 2, 2025
• Primary Completion (Estimated): December 31, 2027
• Study Completion (Estimated): December 31, 2027
• Last Updated: June 22, 2025

Record last verified: 2025-06

Locations

TW (1)