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Clinical Trial Details — Status: Active, not recruiting

Administrative data

NCT number NCT03476291
Other study ID # JSPH-AIOCT-001
Secondary ID
Status Active, not recruiting
Phase
First received February 26, 2018
Last updated March 22, 2018
Start date June 30, 2017
Est. completion date December 31, 2020

Study information

Verified date February 2018
Source The First Affiliated Hospital with Nanjing Medical University
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The investigators expect to develop an algorithm that can interpret OCT images and automated determine whether the macula is normal or not by using OCT image-based deep learning techniques. And investigators wish to develop software applications that will help better screen and diagnose macular diseases in resource-limited areas.


Description:

The investigators will apply deep learning convolutional neural network by using ImageNet for an automated detection of multiple retinal diseases with OCT horizontal B-scans with a high-quality labeled database. Datasets, including training dataset, testing dataset and validation datasets, will be built by ophthalmologists of the First affiliated hospital of Nanjing Medical University according to the standardized annotation guidelines.


Recruitment information / eligibility

Status Active, not recruiting
Enrollment 20000
Est. completion date December 31, 2020
Est. primary completion date June 1, 2018
Accepts healthy volunteers
Gender All
Age group N/A and older
Eligibility Inclusion Criteria:

- All patients attending the Ophthalmology Department of the First Affiliated Hospital of Nanjing Medical University within 5 years and who received known, clear diagnoses with digital retinal imaging (including OCT, fundus digital photographs and fundus fluorescein angiography, at least with OCT images) as part of their routine clinical care, will be eligible for inclusion in this study.

Exclusion Criteria:

- Hardcopy examinations (i.e., photos of paper reports of OCT imaging performed at other hospitals) will be ineligible.

- Data from patients who have previously manually requested that their data should not be shared, even for research purposes in anonymised form, and have informed the Ophthalmology Department of the First Affiliated Hospital of Nanjing Medical University of this desire (even in previously conducted studies or other on-going studies in this hospital), will be excluded, and their data will not be upload to the cloud platform before research begins.

- Data from eyes tamponed with silicone oil or gas (i.e., C3F8) will be ineligible.

- Data with poor image quality, such as incomplete images, inverted images, blurred or cracked images and images with a very weak signal (i.e., vitreous haemorrhage), will be ineligible.

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
China The First Affiliated Hospital with Nanjing Medical University Nanjing Jiangsu

Sponsors (1)

Lead Sponsor Collaborator
The First Affiliated Hospital with Nanjing Medical University

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary receiver operating characteristic(ROC) curve of the algorithm It is also called sensitivity curve. The ROC curve shows how sensitive the algorithm model is to automatically detect the desired output. approximately 1 year
Primary Area under the ROC curve(AUC) It shows the operating value of the algorithm model, which can represent the effect of the model. approximately 1 year
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