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OpenTrials
Enrolling by Invitation

NCT Number: NCT07682025

Imaging and Predictive Modelling of Proliferative Vitreoretinopathy.

Patients with retinal detachment are at risk of recurrence and failure of surgery requiring multiple surgeries due to a condition called proliferative vitreoretinopathy (PVR).

Study aims to help tailor patients' treatments and improve outcomes by:

[i] studying imaging biomarkers of PVR, and [ii] develop AI models for PVR detection.

Inclusion:

* Patients with 'complicated' retinal detachment with PVR recruited to a phase 1 dose-finding trial called MORPH-1. * Patients with 'simple' retinal detachment without PVR recruited to a PhD study.

Non -invasive multimodal imaging and anonymized imaging will be used to study imaging biomarkers of PVR and develop deep learning models to predict PVR in collaboration with an artificial intelligence (AI) expert team at UCL Institute of Ophthalmology.

Enrolling by Invitation

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Key information

Conditions

Proliferative Vitreoretinopathy Eye Diseases Retinal Diseases Vitreoretinopathy, Proliferative

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University College London

London, United Kingdom

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • MORPH-1 and Cohort-NHS study imaging

Exclusion criteria

  • Participants from above studies who have not consented for image analysis and AI related analysis.

Treatment and study plan

Primary outcomes

  1. To study multimodal imaging biomarkers of PVR.

    Time frame: Preoperative biomarkers of PVR on cases with established PVR Post-operative biomarkers of PVR on cases that develop PVR in the first 3 months.

    Use multimodal imaging namely widefield Optos, Widefield OCT, OCT macula, OCT disc, OCT EDI and OCTA to describe biomarkers of PVR.

Secondary outcomes

  1. To develop deep learning AI models for PVR detection in retinal detachment.

    Time frame: Post-operative 3 months

    Use widefield Optos imaging and OCT to:

    • Develop outputs for presence of PVR (binary), and
    • Develop output for prediction of PVR grade.

Sponsors and collaborators

Lead sponsor

University College, London

Other

Registry information

Official study title

Identification of Imaging Biomarkers and Predictive Modelling of Proliferative Vitreoretinopathy Using Deep Learning.

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Jul 2, 2026
Registry last updated
Jul 2, 2026

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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