Research of Automated Maculopathy Screening Based on AI T... | NCT03476291

Studies
Research of Automated Maculopathy Screening Based on AI Techniques Using OCT Images

NCT03476291

Sponsor

The First Affiliated Hospital with Nanjing Medical University

Status

Unknown status

Last Update Posted

Mar 26, 2018Actual

Enrollment

20,000Estimated

Phase

Not provided

Conditions

Maculopathy

Interventions

Not provided

Countries

China

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Feb 2018

Overall Recruitment Status or Expanded Access Status

Unknown status

Last Known Status

Active, not recruiting

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Jun 30, 2017Actual

Primary Completion Date

Jun 1, 2018Estimated

Completion Date

Dec 31, 2020Estimated

First Submitted Date

Feb 26, 2018

First Submission Date that Met QC Criteria

Mar 22, 2018

First Posted Date

Mar 26, 2018Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Mar 22, 2018

Last Update Posted Date

Mar 26, 2018Actual

Oversight Module

Has Data Monitoring Committee (DMC)

Yes

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief 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.

Detailed 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.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

20,000Estimated

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
Normal		normal macular structure of horizontal OCT B-scans
Abnormal		abnormal macular structure of horizontal OCT B-scans, including many sub-categories of pathological features, like epiretinal membrane, pigment epithelium detachment, ect.

Interventions

Not provided

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
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
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

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

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.

Accepts Healthy Volunteers

Not provided

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

Not provided

Maximum Age

Not provided

Standard Ages

ChildAdultOlder Adult

Study Population

no age limited, no gender-based

Sampling Method

Non-Probability Sample

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Name	Affiliation	Role
Songtao Yuan, doctor	The First Affiliated Hospital with Nanjing Medical University	Principal Investigator

Locations

Facility	Status	City	State	ZIP	Country	Contacts
The First Affiliated Hospital with Nanjing Medical University		Nanjing	Jiangsu	210029	China

IPD Sharing Statement Module

Plan to Share IPD

Description

Not provided

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

ID	Term
D012162	Retinal Degeneration
D012164	Retinal Diseases
D005128	Eye Diseases