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Evaluation of the accuracy of an automated algorithm for glaucoma detection from colour fundus photographs taken on a low- cost and a high-tech camera as compared to the gold standard clinical evaluation

Evaluation of the accuracy of an automated algorithm for glaucoma detection from colour fundus photographs taken on a low- cost slit lamp based Remidio fundus-on-phone camera and a high-tech Topcon camera as compared to the gold standard clinical evaluation - a prospective study.

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2021/07/034809
Enrollment
405
Registered
2021-07-13
Start date
Unknown
Completion date
Unknown
Last updated
2021-11-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: H400- Glaucoma suspect Health Condition 2: H401- Open-angle glaucoma Health Condition 3: H408- Other glaucoma Health Condition 4: H402- Primary angle-closure glaucoma

Interventions

Control Intervention1: NIL: NIL

Sponsors

Liverpool John Moores University and The Global Challenges Research Fund GCRF
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1.Glaucoma Group: Any case of glaucoma with typical glaucomatous disc changes, confirmed by clinical evaluation and/or visual field test (as defined below). 2.Normal Controls (including Ocular hypertension (OHT)) (as defined below) 3.Disc suspects (as defined below) 4.Reliable Visual field (false positive (FP), false negative (FN)

Exclusion criteria

Exclusion criteria: 1.Media opacity (corneal/lenticular/vitreous) preventing assessment of the optic disc 2.Co-existing retinal pathologies precluding view of disc 3.Unreliable visual fields 4.Shallow anterior chamber preventing dilation

Design outcomes

Primary

MeasureTime frame
To determine the sensitivity, specificity, positive and negative predictive value of the new AI tool to diagnose glaucoma (normal, glaucoma, suspect) on images collected from slitlamp based low- cost Remidio fundus-on-phone camera and high-tech Topcon camera, as compared to gold standard clinical evaluation.Timepoint: At 6 months (after completion of complete recruitment)—

Secondary

MeasureTime frame
1)Evaluate accuracy of AI tool with images collected from a slitlamp based Remidio Fundus on phone camera and a high-tech Topcon camera) as compared to manual grading of vertical cup to disc ratio (VCDR). 2) Refine the AI tool in in segmentation to increase its robustness. 3) Refine the AI tool in the deformation score to create personalised risk estimation of glaucoma. Timepoint: Single time point—

Countries

India

Contacts

Public ContactDr Swati Upadhyaya

Aravind Eye Hospital

swati.dr@aravind.org8489810704

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026