A-EYE: A Mixed Quantitative and Qualitative Study to Develop and Evaluate the Application of Artificial Intelligence (AI) Methods Using Retinal Imaging for the Identification of Adverse Retinal Changes Associated With Cancer Therapies.
NCT ID: NCT04901468
Last Updated: 2022-11-09
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
UNKNOWN
350 participants
OBSERVATIONAL
2021-06-18
2022-12-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
The purpose of this study is to gather data to help develop an AI algorithm to detect eye abnormalities specifically those related to certain cancer treatments.
At the end of the study interviews will be held with expert ophthalmologists to assess the acceptability of implementing AI into clinical practice.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Retinal Nerve Fiber Layer Thickness and Macular Thickness in Myopia, Hyperopia and Emmetropia : An OCT Study
NCT05486741
Real-world of AI in Diagnosing Retinal Diseases
NCT05981950
Retinal Imaging by Adaptive Optics in Healthy Eyes and During Retinal and General Diseases
NCT01546181
Motivations and Barriers to Participating in Ophthalmology Research Projects
NCT04404803
Artificial Intelligence (AI) - Assisted Visual Impairment Screening Model: Community-based Implementation and Evaluation of Performance, Feasibility and Costs.
NCT06877988
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Ahead of patients taking part in these trials there is often little planning done to manage potential side effects on the eye. Additionally, accessing the expertise of eye specialists is not always available and often referral to a specialist is only given when eye symptoms have become advanced. These delays in identifying side effects on the eye also delays treatment and follow-up management. Providing patients access to this expertise would help in the detection and management of treatment side effects, however, due to demands on resources this access is not always readily available.
The aim of this study is to create an artificial intelligence (AI) program that can detect changes to the eye related to disease, which, in the future, can be specifically used in cancer patient care. Additionally, developing an AI program to detect cancer related side effects to the eye will go a significant way in easing the burden on the health care system and improve side effects from new cancer treatments.
This study will involve the collection of eye scans and medical data from participants at the Manchester Royal Eye Hospital. These will then be used to develop AI methods to detect changes in the eye related to those seen by patients on cancer treatment. The AI will then be compared with the assessments of eye specialists to assess if they give similar results.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
OTHER
PROSPECTIVE
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
No Intervention
This is an observational study
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
2. Aged at least 18 years.
3. Fully registered patient attending the Manchester Royal Eye Hospital
4. Patients are having an optical diagnostic imaging as part of their standard of care.
Exclusion Criteria
1\. Patient who are deemed clinically unable to be scanned by healthcare professional.
18 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Institute of Cancer Research, United Kingdom
OTHER
University of Manchester
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Tariq Aslam
Professor Of Ophthalmology and Interface Technologies and Consultant Ophthalmologist
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Manchester Royal Eye Hospital
Manchester, , United Kingdom
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
NHS001768
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.