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Imaging and Predictive Modelling of Proliferative Vitreoretinopathy.
Sponsor: University College, London
Summary
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.
Official title: Identification of Imaging Biomarkers and Predictive Modelling of Proliferative Vitreoretinopathy Using Deep Learning.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
100
Start Date
2026-10-12
Completion Date
2027-10-15
Last Updated
2026-07-02
Healthy Volunteers
No
Conditions
Locations (1)
University College London
London, United Kingdom