基于肺动脉CTA影像组学的非高危急性肺栓塞患者恶化风险的早期识别与预测

注册号:

Registration number:

ChiCTR2600126662 

最近更新日期:

Date of Last Refreshed on:

2026-06-12 17:58:17 

注册时间:

Date of Registration:

2026-06-12 00:00:00 

注册号状态:

补注册

Registration Status:

Retrospective registration

注册题目:

基于肺动脉CTA影像组学的非高危急性肺栓塞患者恶化风险的早期识别与预测

Public title:

Early Identification and Prediction of Deterioration Risk in Non-High-Risk Acute Pulmonary Embolism Patients Based on Pulmonary Artery CTA Radiomics

注册题目简写:

English Acronym:

研究课题的正式科学名称:

基于肺动脉CTA影像组学的非高危急性肺栓塞患者恶化风险的早期识别与预测

Scientific title:

Early Identification and Prediction of Deterioration Risk in Non-High-Risk Acute Pulmonary Embolism Patients Based on Pulmonary Artery CTA Radiomics

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:

周晓明 

研究负责人:

周晓明 

Applicant:

Zhou Xiaoming 

Study leader:

Zhou Xiaoming 

申请注册联系人电话:

Applicant telephone:

+86 18940256517

研究负责人电话:

Study leader's
telephone:

+86 10 88396849

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:

zhouxmcmu@163.com

研究负责人电子邮件:

Study leader's E-mail:

zhouxmcmu@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:

中国北京市西城区北礼士路167号

研究负责人通讯地址:

中国北京市西城区北礼士路167号

Applicant address:

167 Beilishi Road, Xicheng District, Beijing, China

Study leader's address:

167 Beilishi Road, Xicheng District, Beijing, China

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:

中国医学科学院阜外医院

Applicant's institution:

Fuwai Hospital, Chinese Academy of Medical Sciences

研究负责人所在单位:

中国医学科学院阜外医院

Affiliation of the Leader:

Fuwai Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College

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:

2024-2464

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:

中国医学科学院阜外医院伦理委员会

Name of the ethic committee:

Ethics Committee of Fuwai Hospital, Chinese Academy of Medical Sciences

伦理委员会批准日期:

Date of approved by ethic committee:

2025-12-31 00:00:00

伦理委员会联系人:

丁丽娟

Contact Name of the ethic committee:

Ding Lijuan

伦理委员会联系地址:

中国北京市西城区北礼士路167号

Contact Address of the ethic committee:

167 Beilishi Road, Xicheng District, Beijing, China

伦理委员会联系人电话:

Contact phone of the ethic committee:

+86 10 88396282

伦理委员会联系人邮箱:

Contact email of the ethic committee:

dinglijuan@fuwai.com

研究实施负责(组长)单位:

中国医学科学院阜外医院

Primary sponsor:

Fuwai Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College

研究实施负责(组长)单位地址:

中国北京市西城区北礼士路167号

Primary sponsor's address:

167 Beilishi Road, Xicheng District, Beijing, 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):

北京

市(区县):

Country:

China

Province:

Beijing

City:

单位(医院):

中国医学科学院阜外医院

具体地址:

中国北京市西城区北礼士路167号

Institution
hospital:

Fuwai Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College

Address:

167 Beilishi Road, Xicheng District, Beijing, China

经费或物资来源:

自筹

Source(s) of funding:

Self-funded

研究疾病:

急性非高危肺栓塞;血流动力学恶化(休克、低血压);呼吸衰竭;右心功能不全;全因死亡。  

Target disease:

Acute non-high-risk pulmonary embolism; Hemodynamic deterioration (shock, hypotension); Respiratory failure; Right ventricular dysfunction; All-cause mortality.

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:

其它 

Study phase:

N/A

研究设计:

队列研究 

Study design:

Cohort study 

研究目的:

本项目旨在通过多中心回顾性分析与前瞻性验证相结合的研究设计,构建并验证一套基于肺动脉CTA影像组学与多模态数据的智能风险预测体系。具体目标为:首先,利用卷积网络、注意力机制等深度学习技术,融合肺动脉CTA影像组学特征及临床、超声等多源数据,从血管、血栓、心肺解剖与功能等多维度构建能够早期识别非高危急性肺栓塞患者“恶化倾向”的智能评估模型;其次,通过独立的多中心前瞻性队列对该模型进行外部验证,系统评估其预测效能,并将其与传统肺栓塞严重程度评分(PESI/sPESI)进行优劣比较,最终形成一种能够快速、准确识别非高危肺栓塞恶化风险的临床预测工具,以辅助临床决策、改善患者预后。  

Objectives of Study:

This project aims to develop and validate an intelligent risk prediction system based on pulmonary artery CTA radiomics and multimodal data through a multicenter retrospective analysis and prospective validation study design. The specific objectives are: first, to utilize deep learning technologies such as convolutional networks and attention mechanisms, integrating pulmonary artery CTA radiomics features with multi-source data including clinical and ultrasound information, to construct an intelligent assessment model capable of early identification of "deterioration tendency" in non-high-risk acute pulmonary embolism patients from multiple dimensions such as vascular, thrombus, cardiopulmonary anatomy, and function; second, to externally validate this model through an independent multicenter prospective cohort, systematically evaluate its predictive performance, and compare its advantages and disadvantages with traditional pulmonary embolism severity scores (PESI/sPESI), ultimately forming a clinical prediction tool that can rapidly and accurately identify the risk of deterioration in non-high-risk pulmonary embolism to support clinical decision-making and improve patient outcomes.

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. 慢性或者复发的肺栓塞; 2. 患者病情未能完成肺动脉CTA评估或缺少肺动脉CTA原始DICOM数据; 3. 入院前已接受溶栓治疗; 4. CTA图像质量不佳; 5. 存在其他肺动脉阻塞性肺血管病(如肺动脉肿瘤等); 6. 合并其他心血管疾病(如先天性心脏病、心肌病、瓣膜病等); 7. 无法满足入院后30天随访要求。

Exclusion criteria:

1. Chronic or recurrent pulmonary embolism; 2. Failure to complete pulmonary artery CTA evaluation or lack of original DICOM data from pulmonary artery CTA; 3. Having received thrombolytic therapy prior to admission; 4. Poor quality of CTA images; 5. Presence of other pulmonary artery obstructive vascular diseases (e.g., pulmonary artery tumors, etc.); 6. Comorbidity with other cardiovascular diseases (e.g., congenital heart disease, cardiomyopathy, valvular disease, etc.); 7. Inability to meet the 30-day post-admission follow-up requirement.

研究实施时间:

Study execute time:

From 2026-01-01 00:00:00 To 2027-12-31 00:00:00  

征募观察对象时间:

Recruiting time:

From 2026-01-09 00:00:00 To 2027-12-31 00:00:00

干预措施:

Interventions:

组别:

回顾性训练队列

样本量:

1500

Group:

Retrospective Training Cohort

Sample size:

干预措施:

干预措施代码:

Intervention:

None

Intervention code:

组别:

前瞻性验证队列

样本量:

400

Group:

Prospective Validation Cohort

Sample size:

干预措施:

干预措施代码:

Intervention:

None

Intervention code:

研究实施地点:

Countries of recruitment and research settings:

国家:

中国

省(直辖市):

北京 

市(区县):

 

Country:

China

Province:

Beijing

City:

单位(医院):

中国医学科学院阜外医院 

单位级别:

三级甲等 

Institution
hospital:

Fuwai Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College

Level of the institution:

Tertiary A

测量指标:

Outcomes:

指标中文名:

与传统急性肺栓塞临床预后判定指标 PESI 评分以及 sPESI 评分,基于肺动脉 CTA 影像学组学的非高危急性肺栓塞患者短期“恶化倾向”的风险预测模型的预测效能

指标类型:

主要指标

Outcome:

Predictive performance of a risk prediction model based on pulmonary artery CTA radiomics for short-term deterioration tendency in non-high-risk acute pulmonary embolism patients, compared with traditional clinical prognostic assessment tools PESI and sPESI

Type:

Primary indicator

测量时间点:

测量方法:

诊断效能:Delong检验比较新模型 vs PESI vs sPESI的AUC差异;绘制校准曲线评估预测-观测一致性。

Measure time point of outcome:

Measure method:

Diagnostic accuracy: DeLong's test to compare AUC differences among the new model, PESI, and sPESI; calibration curves were plotted to assess prediction-observation consistency.

采集人体标本:

Collecting sample(s)
from participants:

标本中文名:

组织:

Sample Name:

NA

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:

正在进行

Recruiting

年龄范围:

Participant age:

最小 Min age 18 years
最大 Max age NA 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:

不公开/Private

盲法:

Blinding:

None

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):

研究结束后半年;国家生物信息中心(https://www.cncb.ac.cn/)

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

Six months after the completion of the research; China National Center for Bioinformation (https://www.cncb.ac.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:

病例报告表

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

Case Report Form (CRF)

数据与安全监察委员会:

Data and Safety Monitoring Committee:

有/Yes

注册人:

Name of Registration:

 2026-06-12 17:58:07