基于人工智能的克罗恩病的CTE严重程度评估系统的技术研究及应用

注册号:

Registration number:

ChiCTR2500102948 

最近更新日期:

Date of Last Refreshed on:

2025-05-22 08:49:33 

注册时间:

Date of Registration:

2025-05-22 00:00:00 

注册号状态:

预注册

Registration Status:

Prospective registration

注册题目:

基于人工智能的克罗恩病的CTE严重程度评估系统的技术研究及应用

Public title:

Technical research and application of AI-based CTE severity evaluation system for Crohn's disease.

注册题目简写:

English Acronym:

研究课题的正式科学名称:

基于人工智能的克罗恩病的CTE严重程度评估系统的技术研究及应用

Scientific title:

Technical research and application of AI-based CTE severity evaluation system for Crohn's disease.

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:

孟薇 

研究负责人:

魏艳玲 

Applicant:

Wei Meng 

Study leader:

Yanling Wei 

申请注册联系人电话:

Applicant telephone:

+86 182 7201 0021

研究负责人电话:

Study leader's
telephone:

+86 153 1035 4666

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:

2239004002@qq.com

研究负责人电子邮件:

Study leader's E-mail:

lingzi016@126.com

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:

重庆市渝中区长江支路10号

研究负责人通讯地址:

重庆市渝中区长江支路10号

Applicant address:

Changjiang Zhi Road, Yu zhong Disctrict, Chongqing

Study leader's address:

Changjiang Zhi Road, Yu zhong Disctrict, Chongqing

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:

中国人民解放军陆军特色医学中心(大坪医院)

Applicant's institution:

Army Medical Center(Daping Hospital)

研究负责人所在单位:

中国人民解放军陆军特色医学中心(大坪医院)

Affiliation of the Leader:

Army Medical Center(Daping Hospital)

是否获伦理委员会批准:

Approved by ethic committee:

Yes

伦理委员会批件文号:

Approved No. of ethic committee:

医研伦审(2024)第241-01号

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:

中国人民解放军陆军特色医学中心伦理委员会

Name of the ethic committee:

Ethics committee of Army Medical Center of PLA

伦理委员会批准日期:

Date of approved by ethic committee:

2024-08-21 00:00:00

伦理委员会联系人:

王晶晶

Contact Name of the ethic committee:

Jing

伦理委员会联系地址:

重庆市渝中区长江支路10号

Contact Address of the ethic committee:

Changjiang Zhi Road, Yu zhong Disctrict, Chongqing

伦理委员会联系人电话:

Contact phone of the ethic committee:

+86 68757140

伦理委员会联系人邮箱:

Contact email of the ethic committee:

wii1017@163.com

研究实施负责(组长)单位:

中国人民解放军陆军特色医学中心(大坪医院)

Primary sponsor:

Army Medical Center of PLA (Daping Hospital)

研究实施负责(组长)单位地址:

重庆市渝中区长江支路10号

Primary sponsor's address:

Changjiang Zhi Road, Yu zhong Disctrict, Chongqing

试验主办单位(项目批准或申办者):

Secondary sponsor:

国家:

中国

省(直辖市):

重庆

市(区县):

渝中区

Country:

China

Province:

Chongqing

City:

Yuzhong

单位(医院):

中国人民解放军陆军特色医学中心(大坪医院)

具体地址:

重庆市渝中区长江支路10号

Institution
hospital:

Army Medical Center of PLA (Daping Hospital)

Address:

Changjiang Zhi Road, Yu zhong Disctrict, Chongqing

经费或物资来源:

重庆英才计划

Source(s) of funding:

Chongqing Talent Program

研究疾病:

克罗恩病  

Target disease:

Crohn's disease

研究疾病代码:

Target disease code:

研究类型:

观察性研究

Study type:

Observational study

研究所处阶段:

回顾性研究 

Study phase:

Retrospective study

研究设计:

连续入组 

Study design:

Sequential 

研究目的:

本研究旨在通过深度学习技术分析克罗恩病CTE影像,开发一款搭载人工智能的先进影像系统,该系统可实现对病变部位的更快、更精准识别并显示异常结构区域。进一步,本研究将融合CTE影像分析得到的数值数据与临床生物标志物的检测数值,构建一个创新的量化评分模型。这一模型预期更简便、更准确诊断和评估CD严重程度提供新思路,提高对CD严重程度评估的准确性,为临床提供一种新的诊断和评估工具,推动个性化医疗的发展。  

Objectives of Study:

This study aims to analyze Crohn's disease CTE images by deep learning technology, and develop an advanced imaging system equipped with artificial intelligence, which can realize faster and more accurate identification and display of abnormal structural areas of the lesion site. Further, this study will integrate the numerical data obtained from CTE image analysis with the detection values of clinical biomarkers to build an innovative quantitative scoring model. This model is expected to provide a new way of diagnosing and evaluating the severity of CD more easily and accurately, improve the accuracy of evaluating the severity of CD, provide a new diagnostic and evaluation tool for clinical practice, and promote the development of personalized medicine.

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.研究对象既往有肠道手术史; 2.CTE图像质量差,肠道解剖结构难以辨认。

Exclusion criteria:

1. The subjects had a history of intestinal surgery. 2. CTE images are of poor quality and the intestinal anatomy is difficult to identify.

研究实施时间:

Study execute time:

From 2024-07-30 00:00:00 To 2026-06-30 00:00:00  

征募观察对象时间:

Recruiting time:

From 2025-06-01 00:00:00 To 2026-01-31 00:00:00

干预措施:

Interventions:

组别:

克罗恩病组

样本量:

800

Group:

Crohn's Disease Group

Sample size:

干预措施:

干预措施代码:

Intervention:

NA

Intervention code:

研究实施地点:

Countries of recruitment and research settings:

国家:

中国

省(直辖市):

重庆 

市(区县):

渝中区 

Country:

China

Province:

Chongqing

City:

Yuzhong

单位(医院):

中国人民解放军陆军特色医学中心(大坪医院) 

单位级别:

三甲 

Institution
hospital:

Army Medical Center(Daping Hospital)

Level of the institution:

Tertiary A

国家:

中国

省(直辖市):

浙江 

市(区县):

杭州市 

Country:

China

Province:

Zhejiang

City:

Hangzhou

单位(医院):

浙江大学医学院附属邵逸夫医院 

单位级别:

三甲 

Institution
hospital:

Sir Run Run Shaw Hospital , affiliated with the Zhejiang University School of Medicine

Level of the institution:

Tertiary A

国家:

中国

省(直辖市):

重庆 

市(区县):

沙坪坝区 

Country:

China

Province:

Chongqing

City:

Shapingba

单位(医院):

陆军军医大学第二附属医院(新桥医院) 

单位级别:

三甲 

Institution
hospital:

The Second Affiliated Hospital of Army Medical University (Xinqiao Hospital)

Level of the institution:

Tertiary A

测量指标:

Outcomes:

指标中文名:

人工智能辅助分级模型评估克罗恩病严重程度

指标类型:

主要指标

Outcome:

An AI-assisted grading model to assess Crohn's disease severity

Type:

Primary indicator

测量时间点:

测量方法:

验证深度学习预测模型评估克罗恩病严重程度准确率

Measure time point of outcome:

Measure method:

To verify the accuracy of deep learning prediction model in evaluating Crohn's disease severity

指标中文名:

CD量化性评分评估克罗恩病严重程度

指标类型:

次要指标

Outcome:

The CD quantitative score assessed the severity of Crohn's disease

Type:

Secondary indicator

测量时间点:

测量方法:

通过CTE图像数据与临床血清学指标相结合,采用多元性回归分析,构建一个量化性评分系统,并对CD量化性评分模型进行验证。

Measure time point of outcome:

Measure method:

Through the combination of CTE image data and clinical serological indicators, multivariate regression analysis was used to construct a quantitative scoring system, and the quantitative scoring model of CD was verified.

采集人体标本:

Collecting sample(s)
from participants:

标本中文名:

组织:

Sample Name:

None

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 years
最大 Max age 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):

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

None

是否公开试验完成后的统计结果:

Calculated Results after the Study Completed public access:

公开/Public

盲法:

Blinding:

试验完成后的统计结果(上传文件):

Calculated Results after
the Study Completed(upload file):

是否共享原始数据:

IPD sharing

是Yes

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):

中国临床研究注册中心

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

https://www.chictr.org.cn/

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:

所有临床资料、血清学检查结果将会录入至数据表格,由项目组成员孟薇、唐宗源统一录入和分析,数据管理由项目组成员魏艳玲、阮广聪共同管理。所有CTE影像资料将会以图片形式保存,由项目组成员孟薇、阮广聪、肖志凤共同管理。数据安全由项目组成员孟薇、阮广聪共同管理,并由项目组成员赵雪霏、田宇婷进行监察。

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

All clinical data and serological test results will be entered into the data table, which will be uniformly entered and analyzed by Wei Meng and Zongyuan Tang, members of the project team. Data management will be jointly managed by Yanling Wei and Guangcong Ruan, members of the project team. All CTE image data will be saved as pictures and managed by the project team members Wei Meng, Guangcong Ruan and Zhifeng Xiao. Data security is jointly managed by Wei Meng and Guangcong Ruan, and supervised by Xuefei Zhao and Yuting Tian.

数据与安全监察委员会:

Data and Safety Monitoring Committee:

有/Yes

注册人:

Name of Registration:

 2025-05-22 08:49:16