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A novel deep learning-based three-dimensional retinal vascular analysis for progression risk stratification in glaucoma patients
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注册号：

Registration number：

 ChiCTR2500104716 

最近更新日期：

Date of Last Refreshed on：

 2025-06-23 00:10:22 

注册时间：

Date of Registration：

 2025-06-23 00:00:00 

注册号状态：

预注册

Registration Status：

Prospective registration

注册题目：

A novel deep learning-based three-dimensional retinal vascular analysis for progression risk stratification in glaucoma patients

Public title：

A novel deep learning-based three-dimensional retinal vascular analysis for progression risk stratification in glaucoma patients

注册题目简写：

English Acronym：

研究课题的正式科学名称：

A novel deep learning-based three-dimensional retinal vascular analysis for progression risk stratification in glaucoma patients

Scientific title：

A novel deep learning-based three-dimensional retinal vascular analysis for progression risk stratification in glaucoma patients

研究课题代号(代码)：

Study subject ID：

在二级注册机构或其它机构的注册号：

The registration number of the Partner Registry or other register：

申请注册联系人：

Ruyue Shen 

研究负责人：

Ruyue Shen 

Applicant：

Ruyue Shen 

Study leader：

Ruyue Shen 

申请注册联系人电话：

Applicant telephone：

 +852 3943 0786

研究负责人电话：

Study leader's
telephone：

+852 3943 0786

申请注册联系人传真 ：

Applicant Fax：

研究负责人传真：

Study leader's fax：

申请注册联系人电子邮件：

Applicant E-mail：

 ruyueshen@cuhk.edu.hk

研究负责人电子邮件：

Study leader's E-mail：

 ruyueshen@cuhk.edu.hk

申请单位网址(自愿提供)：

Applicant website(voluntary supply)：

研究负责人网址(自愿提供)：

Study leader's website(voluntary supply)：

申请注册联系人通讯地址：

4/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

研究负责人通讯地址：

4/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

Applicant address：

4/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

Study leader's address：

4/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

申请注册联系人邮政编码：

Applicant postcode：

研究负责人邮政编码：

Study leader's postcode：

申请人所在单位：

The Chinese University of Hong Kong

Applicant's institution：

The Chinese University of Hong Kong

研究负责人所在单位：

The Chinese University of Hong Kong

Affiliation of the Leader：

The Chinese University of Hong Kong

是否获伦理委员会批准：

是

Approved by ethic committee：

Yes

伦理委员会批件文号：

Approved No. of ethic committee：

 CIRB-2024-489-3

伦理委员会批件附件：

Approved file of Ethical Committee：

 查看附件View

批准本研究的伦理委员会名称：

Central Institutional Review Board

Name of the ethic committee：

Central Institutional Review Board

伦理委员会批准日期：

Date of approved by ethic committee：

 2024-12-23 00:00:00

伦理委员会联系人：

Central Institutional Review Board

Contact Name of the ethic committee：

Central Institutional Review Board

伦理委员会联系地址：

Hospital Authority Building, 147B Argyle Street, Kowloon, Hong Kong

Contact Address of the ethic committee：

Hospital Authority Building, 147B Argyle Street, Kowloon, Hong Kong

伦理委员会联系人电话：

Contact phone of the ethic committee：

 +852 2300 6555

伦理委员会联系人邮箱：

Contact email of the ethic committee：

研究实施负责（组长）单位：

The Chinese University of Hong Kong

Primary sponsor：

The Chinese University of Hong Kong

研究实施负责（组长）单位地址：

3/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

Primary sponsor's address：

3/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

试验主办单位(项目批准或申办者)：

Secondary sponsor：

国家：

China

省(直辖市)：

Hong Kong

市(区县)：

Country：

China

Province：

Hong Kong

City：

单位(医院)：

Department of Ophthalmology and Visual Sciences (DOVS), The Chinese University of Hong Kong

具体地址：

3/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

Institution
hospital：

Department of Ophthalmology and Visual Sciences (DOVS), The Chinese University of Hong Kong

Address：

3/F, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon

经费或物资来源：

Health and Medical Research Fund

Source(s) of funding：

Health and Medical Research Fund

研究疾病：

Glaucoma  

Target disease：

Glaucoma

研究疾病代码：

Target disease code：

研究类型：

诊断试验

Study type：

Diagnostic test

研究所处阶段：

 其它 

Study phase：

N/A

研究设计：

诊断试验诊断准确性 

Study design：

Diagnostic test for accuracy 

研究目的：

Aim 1 • To develop a novel deep learning-based 3D model for retinal vasculature analysis in glaucoma patients. Aim 2 • To integrate the novel biomarkers of our proposed 3D DL retinal vasculature system with clinical biomarkers for the establishment of a risk stratification model of glaucoma progression.  

Objectives of Study：

Aim 1 • To develop a novel deep learning-based 3D model for retinal vasculature analysis in glaucoma patients. Aim 2 • To integrate the novel biomarkers of our proposed 3D DL retinal vasculature system with clinical biomarkers for the establishment of a risk stratification model of glaucoma progression.

药物成份或治疗方案详述：

 

Description for medicine or protocol of treatment in detail：

 

纳入标准：

Inclusion criteria

排除标准：

1. Other ocular diseases that may cause retinal vascular change, such as diabetic retinopathy, hypertension retinopathy; or AMD. 2. Extremely myopia (i.e., axial length > 27.0 mm). 3. OCTA images with insufficient image quality.

Exclusion criteria：

1. Other ocular diseases that may cause retinal vascular change, such as diabetic retinopathy, hypertension retinopathy; or AMD. 2. Extremely myopia (i.e., axial length > 27.0 mm). 3. OCTA images with insufficient image quality.

研究实施时间：

Study execute time：

从 From 2025-07-01 00:00:00至 To 2027-04-30 00:00:00  

征募观察对象时间：

Recruiting time：

从 From 2025-07-01 00:00:00 至 To 2026-07-01 00:00:00

诊断试验：

Diagnostic Tests：

金标准或参考标准（即可准确诊断某疾病的单项方法或多项联合方法，在本研究中用于诊断是否有该病的临床参考标准）：

Glaucoma is defined when at least one eye had the presence of the structural and functional evidence of glaucoma, including glaucomatous optic disc cupping, RNFL damage, or neuroretinal rim loss, and minimal criteria for glaucomatous VF defect as per published standard (38): glaucoma hemifield test result outside normal limits, pattern standard deviation (PSD) with P < 0.05 or a cluster of 3 or more points in the pattern deviation plot in a single hemifield with P < 0.05, one of which must have P < 0.01. Any one of the preceding criteria, if repeatable, was considered sufficient evidence for the glaucomatous visual field (VF) defect.

Gold Standard or Reference Standard (The clinical reference standards required to establish the presence or absence of the target condition in the tested population in present study):

Glaucoma is defined when at least one eye had the presence of the structural and functional evidence of glaucoma, including glaucomatous optic disc cupping, RNFL damage, or neuroretinal rim loss, and minimal criteria for glaucomatous VF defect as per published standard (38): glaucoma hemifield test result outside normal limits, pattern standard deviation (PSD) with P < 0.05 or a cluster of 3 or more points in the pattern deviation plot in a single hemifield with P < 0.05, one of which must have P < 0.01. Any one of the preceding criteria, if repeatable, was considered sufficient evidence for the glaucomatous visual field (VF) defect.

指标试验（即本研究的待评估诊断试验，无论为方法、生物标志物或设备，均请列出名称）：

A novel deep learning-based three-dimensional retinal vascular analysis

Index test:

A novel deep learning-based three-dimensional retinal vascular analysis

目标人群（可以是某种疾病患者或正常人群，详细描述其疾病特征，注意应纳入符合分布特点的全序列病例，具有良好的代表性）

Participants with glaucoma

例数:

Sample size:

464

Target condition (The target condition is a particular disease or disease stage that the index test will be intended to identify. Please specify the characteristics in detail; the population should has a complete spectrum and good representative):

Participants with glaucoma

容易混淆的疾病人群（即与目标疾病不易区分的一种或多种不同疾病，应避免采用正常人群对照的病例-对照设计）：

nil

例数:

Sample size:

0

Population with condition difficult to distinguish from the target condition, the normal population in a case-control study design should be avoid:

nil

研究实施地点：

Countries of recruitment and research settings：

国家：

 China

省(直辖市)：

 Hong Kong SAR  

市(区县)：

  

Country：

China

Province：

Hong Kong SAR

City：

单位(医院)：

 Hong Kong Eye Hospital 

单位级别：

 NA 

Institution
hospital：

Hong Kong Eye Hospital

Level of the institution：

NA

测量指标：

Outcomes：

指标中文名：

The accuracy of deep learning system for feature extraction, progression detection, and risk stratification for glaucoma progression

指标类型：

主要指标

Outcome：

The accuracy of deep learning system for feature extraction, progression detection, and risk stratification for glaucoma progression

Type：

Primary indicator

测量时间点：

测量方法：

Measure time point of outcome：

Measure method：

指标中文名：

Sensitivity

指标类型：

主要指标

Outcome：

Sensitivity

Type：

Primary indicator

测量时间点：

测量方法：

Measure time point of outcome：

Measure method：

指标中文名：

Specificity

指标类型：

主要指标

Outcome：

Specificity

Type：

Primary indicator

测量时间点：

测量方法：

Measure time point of outcome：

Measure method：

采集人体标本：

Collecting sample(s)
from participants：

标本中文名：

N/A

组织：

Sample Name：

N/A

Tissue：

人体标本去向

 其它  

说明

Fate of sample：

0thers  

Note：

征募研究对象情况：

Recruiting status：

尚未开始

Not yet recruiting

年龄范围：

Participant age：
最小 Min age 18 岁 years
最大 Max age 80 岁 years

性别：

男女均可

Gender：

Both

随机方法（请说明由何人用什么方法产生随机序列）：

NA

Randomization Procedure (please state who generates the random number sequence and by what method)：

NA

是否公开试验完成后的统计结果:

Calculated Results after the Study Completed public access:

不公开/Private

盲法：

Blinding：

是否共享原始数据：

IPD sharing

否No

共享原始数据的方式（说明：请填入公开原始数据日期和方式，如采用网络平台，需填该网络平台名称和网址）：

NA

The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url)：

NA

数据采集和管理（说明：数据采集和管理由两部分组成，一为病例记录表(Case Record Form, CRF)，二为电子采集和管理系统(Electronic Data Capture, EDC)，如ResMan即为一种基于互联网的EDC：

NA

Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture：

NA

数据与安全监察委员会：

Data and Safety Monitoring Committee：

暂未确定/Not yet

注册人：

Name of Registration：

  2025-06-23 00:10:09
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