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NCT Number: NCT06552247

Glaucoma Algorithm Validation Study in African Population - the MAGIC Study

Artificial Intelligence (AI) algorithms require validation in a variety of populations to ensure widespread clinical applicability. In Ophthalmology, AI algorithms are reaching maturity in diagnosis such as diabetic retinopathy and glaucoma. Higher-at-risk subjects of African descent are nevertheless usually under-represented in training datasets and therefore unclear about representativity.

A small scale validation study in consecutive patients in a large Eyesore unit in Mozambique will be performed to determine the diagnostic ability of these AI softwares in this population

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Key information

About this study

Artificial Intelligence (AI) algorithm's are the next frontier in medical management, usually meant to improve diagnostic capabilities and to optimize the existing resources. They are particularly relevant in settings where there is a lack of specialised Human Resources such as physicians.

Ensuring these algorithms can be used in a wide population is therefore crucial to clinical implementation. Validation studies in specific segments of populations are needed to ensure all patients are represented and the results are therefore reliable. Higher-at-risk subjects of African descent are nevertheless usually under-represented in training datasets and therefore unclear about representativity.

A pilot study for validation of an AI algorithm for Glaucoma and Diabetic Retinopathy will be done for the MONA G-RISK® and diabetic retinopathy. Consecutive patients from a large Eye Unit in Mozambique's capital will be screened using these AI algorithms and validated using clinical standard as ground truth.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • subjects age above 18 years old presenting at the Eye Unit
  • willingness to sign an informed consent for the screening process

Exclusion criteria

  • none
  • Poor quality in screening image will be included in the intention to treat analysis, but excluded from the diagnostic comparator outcome.
  • Patients with a known glaucoma diagnosis will not be excluded from the screening

Treatment and study plan

Fundus Picture AI testing

Diagnostic Test

G-Risk AI algorithm will assess the optic disc centered fundus picture and determine whether or not there is a need for referrable based on a pre-determined threshold (>=0.73)

Primary outcomes

  1. Diagnostic agreement between referring decision and reading center decision

    Time frame: Duration of the study - 3 weeks

    Level of agreement will be done between referring decision and the ground truth as assessed by the reading center (normal, glaucoma suspect; definitive glaucoma). All subjects from both centers (referred and non-referred) will be reviewed.

    For a primary outcome analysis, the middle category (glaucoma suspect) will be pooled together with the normal diagnosis

Secondary outcomes

  1. Level of agreement (in %) between AI-risk score and human-based assessment of disease severity

    Time frame: After the study - 6 months

    Reading center risk score of disease severity (ranked from 0 to 100) will be compared to the AI-based disease score. This will be done separately in each of the 3 categories (normal; glaucoma suspect; glaucoma). Analysis of this score would help refine clinical risk (high risk vs low risk patients) of each category. Exploratory analysis will be made to determine the added value of including this risk score in refining AI-based referral

Study contacts

Contact information is provided by the study sponsor or research team.

Luis Abegao Pinto, MD, PhD

CONTACT

[email protected]

+351 217 805 000

Quirina Tavares Ferreira, PhD

CONTACT

[email protected]

+351 217 805 000

Sponsors and collaborators

Lead sponsor

Centro Hospitalar Universitário Lisboa Norte

Other

Collaborators

  • Dr. Agarwal's Eye Hospital

Registry information

Official study title

Validation Study of an Artificial Algorithm for Glaucoma Detection in an African Population

Acronym: MAGIC

Important dates

Study start
2024
Primary completion
2024
Study completion
2024
First posted
Aug 13, 2024
Registry last updated
Aug 13, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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