该试验尚未获伦理委员会批准,请于批准后才开始征募参试者,并与我们联系上传伦理批件。 人工智能辅助系统在早期肺癌术前综合评估中的应用研究

注册号:

Registration number:

ChiCTR2000035689 

最近更新日期:

Date of Last Refreshed on:

2020-08-16 07:38:00 

注册时间:

Date of Registration:

2020-08-16 00:00:00 

注册号状态:

预注册

Registration Status:

Prospective registration

注册题目:

该试验尚未获伦理委员会批准,请于批准后才开始征募参试者,并与我们联系上传伦理批件。 人工智能辅助系统在早期肺癌术前综合评估中的应用研究

Public title:

Application Research of Artificial Intelligence Assistant System in in Comprehensive Preoperative Evaluation of Early Lung Cancer

注册题目简写:

English Acronym:

研究课题的正式科学名称:

人工智能辅助系统在早期肺癌术前综合评估中的应用研究

Scientific title:

Application Research of Artificial Intelligence Assistant System in in Comprehensive Preoperative Evaluation of Early Lung Cancer

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:

王亭亭 

研究负责人:

谢冬 

Applicant:

Tingting Wang 

Study leader:

Dong Xie 

申请注册联系人电话:

Applicant telephone:

+86 18018592024

研究负责人电话:

Study leader's
telephone:

+86 13918918907

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:

growingwtt@163.com

研究负责人电子邮件:

Study leader's E-mail:

kongduxd@163.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:

上海市区政民路507号

研究负责人通讯地址:

上海市区政民路507号

Applicant address:

507 Zhengmin Road, Yangpu District, Shanghai, China

Study leader's address:

507 Zhengmin Road, Yangpu District, Shanghai, China

申请注册联系人邮政编码:

Applicant postcode:

200433

研究负责人邮政编码:

Study leader's postcode:

200433

申请人所在单位:

上海肺科医院

Applicant's institution:

Shanghai Pulmonary Hospital

研究负责人所在单位:

上海肺科医院

Affiliation of the Leader:

Shanghai Pulmonary Hospital

是否获伦理委员会批准:

Approved by ethic committee:

No

伦理委员会批件文号:

Approved No. of ethic committee:

伦理委员会批件附件:

Approved file of Ethical Committee:

批准本研究的伦理委员会名称:

Name of the ethic committee:

伦理委员会批准日期:

Date of approved by ethic committee:

2013-08-26 00:00:00

伦理委员会联系人:

Contact Name of the ethic committee:

伦理委员会联系地址:

Contact Address of the ethic committee:

伦理委员会联系人电话:

Contact phone of the ethic committee:

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:

上海肺科医院

Primary sponsor:

Shanghai Pulmonary Hospital

研究实施负责(组长)单位地址:

上海市区政民路507号

Primary sponsor's address:

507 Zhengmin Road, Yangpu District, Shanghai, China

试验主办单位(项目批准或申办者):

Secondary sponsor:

国家:

中国

省(直辖市):

上海

市(区县):

Country:

China

Province:

Shanghai

City:

单位(医院):

上海肺科医院

具体地址:

上海市区政民路507号

Institution
hospital:

Shanghai Pulmonary Hospital

Address:

507 Zhengmin Road, Yangpu District

经费或物资来源:

科研经费

Source(s) of funding:

Research fund

研究疾病:

肺癌  

Target disease:

Lung cancer

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:

探索性研究/预试验 

Study phase:

0

研究设计:

连续入组 

Study design:

Sequential 

研究目的:

我们旨在评估基于CT图像建立的人工智能辅助系统在肺癌定性诊断、浸润程度判定和与治疗决策指导中的应用价值  

Objectives of Study:

We aim to evaluate the application value of artificial intelligence assisted systems based on CT images in the qualitative diagnosis of lung cancer, the invasiveness assessment, and the guidance of treatment decisions

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.肺部结节数目大于2;
2.患者CT图像质量差,或者合并基础肺部疾病:如大面积肺部感染,大量胸水,弥漫性间质性肺炎等
3.临床信息不全者;
4.肿瘤病史者;
5.胸部手术史。

Exclusion criteria:

1. The number of lung nodules exceeds 2;
2. The quality of CT images is poor, or patients with comorbidities including extensive pulmonary infection, massive pleural effusion, and diffused interstitial pneumonia, etc.;
3. Patients with imcomplete clinical information;
4. Patients with a history of malignancy;
5. With a history of thoracic surgery.

研究实施时间:

Study execute time:

From 2020-10-01 00:00:00 To 2022-10-01 00:00:00  

征募观察对象时间:

Recruiting time:

From 2020-12-01 00:00:00 To 2022-04-01 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):

病理学诊断结果

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):

Pathologic results

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):

人工智能辅助系统的判断

Index test:

the detection results of artificial intelligence assisted systems

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)

确认肺结节的患者

例数:

Sample size:

275

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):

Candidates with potential or diagnosed lung nodules

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):

早期肺癌筛查人群

例数:

Sample size:

275

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

Screening population for lung cancer

研究实施地点:

Countries of recruitment and research settings:

国家:

中国

省(直辖市):

上海 

市(区县):

 

Country:

China

Province:

Shanghai

City:

单位(医院):

上海肺科医院 

单位级别:

三甲 

Institution
hospital:

Shanghai Pulmonary Hospital

Level of the institution:

Tertiary A Hospital

测量指标:

Outcomes:

指标中文名:

诊断准确性

指标类型:

主要指标

Outcome:

Accuracy

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:

CT图像

组织:

Sample Name:

Computed Tomography Images

Tissue:

人体标本去向

使用后保存  

说明

Fate of sample:

Preservation after use  

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 years
最大 Max age 70 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):

N/A

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

N/A

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:

未说明

Blinding:

Not stated

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):

以发表文章的方式来公布结果

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

Through the published paper

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:

PACS 系统

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

PACS system

数据与安全监察委员会:

Data and Safety Monitoring Committee:

有/Yes

注册人:

Name of Registration:

 2020-08-16 07:33:32