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. (A-EYE)
This is a data collection study involving the gathering of clinical data and OCT (optical coherence tomography) scans from 350 patients.
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.
Aperçu de l'étude
Description détaillée
Many cancer patients will access new treatments through clinical trials. These treatments have often never been tested in humans and therefore, are likely to have unknown side effects. Some of these side effects include changes to the eye, such as blindness.
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.
Type d'étude
Inscription (Anticipé)
Contacts et emplacements
Coordonnées de l'étude
- Nom: Tariq Aslam
- Numéro de téléphone: 0161 276 1234
- E-mail: tariq.aslam@manchester.ac.uk
Lieux d'étude
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Manchester, Royaume-Uni
- Recrutement
- Manchester Royal Eye Hospital
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Contact:
- Tariq Aslam
- E-mail: tariq.aslam@manchester.ac.uk
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Critères de participation
Critère d'éligibilité
Âges éligibles pour étudier
Accepte les volontaires sains
Sexes éligibles pour l'étude
Méthode d'échantillonnage
Population étudiée
La description
Inclusion Criteria:
Patients are eligible for the study if all inclusion criteria are met:
- Voluntary informed consent.
- Aged at least 18 years.
- Fully registered patient attending the Manchester Royal Eye Hospital
- Patients are having an optical diagnostic imaging as part of their standard of care.
Exclusion Criteria:
Patients are excluded from the study if any of the following criteria apply:
1. Patient who are deemed clinically unable to be scanned by healthcare professional.
Plan d'étude
Comment l'étude est-elle conçue ?
Détails de conception
Que mesure l'étude ?
Principaux critères de jugement
Mesure des résultats |
Délai |
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Measure of the diagnostic accuracy of the AI algorithm against gold standard clinical assessment associated with cancer treatment.
Délai: 12 months
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12 months
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Mesures de résultats secondaires
Mesure des résultats |
Délai |
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Sensitivity of the AI in identifying clinically relevant lesions as defined by an ophthalmologist. Specificity of the AI in identifying clinically relevant lesions as defined by an ophthalmologist.
Délai: 12 months
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12 months
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Autres mesures de résultats
Mesure des résultats |
Délai |
|---|---|
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F1 score of the proposed algorithm compared against baseline algorithms.
Délai: 13 months
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13 months
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Recorded questionnaire/ interview with ophthalmologist and cancer specialists.
Délai: 9 months
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9 months
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Number of novel relationships identified
Délai: 12 months
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12 months
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Collaborateurs et enquêteurs
Parrainer
Collaborateurs
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude (Réel)
Achèvement primaire (Anticipé)
Achèvement de l'étude (Anticipé)
Dates d'inscription aux études
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première publication (Réel)
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Plus d'information
Termes liés à cette étude
Autres numéros d'identification d'étude
- NHS001768
Plan pour les données individuelles des participants (IPD)
Prévoyez-vous de partager les données individuelles des participants (DPI) ?
Informations sur les médicaments et les dispositifs, documents d'étude
Étudie un produit pharmaceutique réglementé par la FDA américaine
Étudie un produit d'appareil réglementé par la FDA américaine
Ces informations ont été extraites directement du site Web clinicaltrials.gov sans aucune modification. Si vous avez des demandes de modification, de suppression ou de mise à jour des détails de votre étude, veuillez contacter register@clinicaltrials.gov. Dès qu'un changement est mis en œuvre sur clinicaltrials.gov, il sera également mis à jour automatiquement sur notre site Web .