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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)

2022年11月8日 更新者:Tariq Aslam、University of Manchester

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.

研究概览

地位

招聘中

条件

详细说明

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.

研究类型

观察性的

注册 (预期的)

350

联系人和位置

本节提供了进行研究的人员的详细联系信息,以及有关进行该研究的地点的信息。

学习联系方式

学习地点

参与标准

研究人员寻找符合特定描述的人,称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。

资格标准

适合学习的年龄

18年 及以上 (成人、年长者)

接受健康志愿者

不

有资格学习的性别

全部

取样方法

概率样本

研究人群

Participants will be patients at the Manchester Royal Eye Hospital who meet the eligibility criteria.

描述

Inclusion Criteria:

Patients are eligible for the study if all inclusion criteria are met:

  1. Voluntary informed consent.
  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:

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.

学习计划

本节提供研究计划的详细信息,包括研究的设计方式和研究的衡量标准。

研究是如何设计的?

设计细节

研究衡量的是什么?

主要结果指标

结果测量
大体时间
Measure of the diagnostic accuracy of the AI algorithm against gold standard clinical assessment associated with cancer treatment.
大体时间:12 months
12 months

次要结果测量

结果测量
大体时间
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.
大体时间:12 months
12 months

其他结果措施

结果测量
大体时间
F1 score of the proposed algorithm compared against baseline algorithms.
大体时间:13 months
13 months
Recorded questionnaire/ interview with ophthalmologist and cancer specialists.
大体时间:9 months
9 months
Number of novel relationships identified
大体时间:12 months
12 months

合作者和调查者

在这里您可以找到参与这项研究的人员和组织。

研究记录日期

这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查,以确保它们在发布到公共网站之前符合特定的质量控制标准。

研究主要日期

学习开始 (实际的)

2021年6月18日

初级完成 (预期的)

2022年12月31日

研究完成 (预期的)

2022年12月31日

研究注册日期

首次提交

2021年5月17日

首先提交符合 QC 标准的

2021年5月24日

首次发布 (实际的)

2021年5月25日

研究记录更新

最后更新发布 (实际的)

2022年11月9日

上次提交的符合 QC 标准的更新

2022年11月8日

最后验证

2022年11月1日

更多信息

与本研究相关的术语

其他研究编号

  • NHS001768

计划个人参与者数据 (IPD)

计划共享个人参与者数据 (IPD)?

不

药物和器械信息、研究文件

研究美国 FDA 监管的药品

不

研究美国 FDA 监管的设备产品

不

此信息直接从 clinicaltrials.gov 网站检索,没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求,请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改,我们的网站上也会自动更新.

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