基于影像-临床-分子多模态融合的上尿路尿路上皮癌术前诊断与病理风险预测深度学习模型研究

注册号:

Registration number:

ChiCTR2600117275 

最近更新日期:

Date of Last Refreshed on:

2026-01-21 17:52:59 

注册时间:

Date of Registration:

2026-01-21 00:00:00 

注册号状态:

预注册

Registration Status:

Prospective registration

注册题目:

基于影像-临床-分子多模态融合的上尿路尿路上皮癌术前诊断与病理风险预测深度学习模型研究

Public title:

Development of a Multi-modal Deep Learning Model Integrating Imaging, Clinical, and Molecular Data for Preoperative Diagnosis and Pathologic Risk Prediction in Upper Tract Urothelial Carcinoma

注册题目简写:

English Acronym:

研究课题的正式科学名称:

基于影像-临床-分子多模态融合的上尿路尿路上皮癌术前诊断与病理风险预测深度学习模型研究

Scientific title:

Development of a Multi-modal Deep Learning Model Integrating Imaging, Clinical, and Molecular Data for Preoperative Diagnosis and Pathologic Risk Prediction in Upper Tract Urothelial Carcinoma

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:

张琦 

研究负责人:

张琦 

Applicant:

Qi Zhang 

Study leader:

Qi Zhang 

申请注册联系人电话:

Applicant telephone:

+86 13858019285

研究负责人电话:

Study leader's
telephone:

+86 13858019285

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:

urology@zju.edu.cn

研究负责人电子邮件:

Study leader's E-mail:

clinic@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:

浙江省杭州市拱墅区上塘路158号

研究负责人通讯地址:

浙江省杭州市拱墅区上塘路158号

Applicant address:

No. 158, Shangtang Road, Gongshu District, Hangzhou, Zhejiang Province

Study leader's address:

No. 158, Shangtang Road, Gongshu District, Hangzhou, Zhejiang Province

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:

浙江省人民医院

Applicant's institution:

Zhejiang Provincial People's Hospital

研究负责人所在单位:

浙江省人民医院

Affiliation of the Leader:

Zhejiang Provincial People's 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:

浙人医伦审2025研第(526)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:

浙江省人民医院医学伦理委员会

Name of the ethic committee:

Ethical Committee of Zhejiang Provincial Peoples Hospital

伦理委员会批准日期:

Date of approved by ethic committee:

2025-12-15 00:00:00

伦理委员会联系人:

李青青

Contact Name of the ethic committee:

Li Qingqing

伦理委员会联系地址:

浙江省杭州市拱墅区上塘路158号

Contact Address of the ethic committee:

No. 158, Shangtang Road, Gongshu District, Hangzhou, Zhejiang Province

伦理委员会联系人电话:

Contact phone of the ethic committee:

+86 571 85893643

伦理委员会联系人邮箱:

Contact email of the ethic committee:

zryllwyh@163.com

研究实施负责(组长)单位:

浙江省人民医院

Primary sponsor:

Zhejiang Provincial People's Hospital

研究实施负责(组长)单位地址:

浙江省杭州市拱墅区上塘路158号

Primary sponsor's address:

No. 158, Shangtang Road, Gongshu District, Hangzhou, Zhejiang Province

试验主办单位(项目批准或申办者):

Secondary sponsor:

国家:

中国

省(直辖市):

浙江省

市(区县):

Country:

China

Province:

Zhejiang

City:

单位(医院):

浙江省人民医院

具体地址:

浙江省杭州市拱墅区上塘路158号

Institution
hospital:

Zhejiang Provincial People's Hospital

Address:

No. 158, Shangtang Road, Gongshu District, Hangzhou, Zhejiang Province

经费或物资来源:

浙江省自然科学基金

Source(s) of funding:

Zhejiang Provincial Natural Science Foundation

研究疾病:

肾细胞癌  

Target disease:

Renal cell carcinoma

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:

连续入组 

Study design:

Sequential 

研究目的:

本研究旨在构建基于影像–临床–分子特征融合的 UTUC 术前智能预测模型,利用深度学习方法整合增强 CT 放射组学特征、关键临床指标及分子亚型相关信息,从而提升对 UTUC 的自动识别与高级别病理风险预测能力。研究目标在于实现更准确的肿瘤风险分层、减少误诊与不必要手术,并形成一个具备可解释性和可推广性的辅助决策系统,为临床提供更可靠的术前评估手段,推动 UTUC 诊断和管理向精准医学方向发展。  

Objectives of Study:

This study aims to develop a preoperative intelligent prediction model for UTUC based on the integration of imaging, clinical, and molecular features. It uses deep learning methods to combine enhanced CT radiomics features, key clinical indicators, and molecular subtype-related information to improve the automatic identification of UTUC and the prediction of high-grade pathological risk. The research goal is to achieve more accurate tumor risk stratification, reduce misdiagnosis and unnecessary surgeries, and create an interpretable and generalizable decision-support system. This will provide clinicians with a more reliable preoperative assessment tool and advance the diagnosis and management of UTUC toward precision 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.非肾细胞癌患者,或病理诊断不明确; 2.既往接受过系统性靶向治疗、免疫治疗或放疗,且目前为复发或广泛转移期; 3.合并严重心肺功能不全、肝肾功能衰竭、活动性感染等,无法耐受手术或辅助治疗; 4.合并严重精神疾病、认知障碍或其他影响研究依从性的状况; 5.无法配合术后随访或预计无法完成研究期内相关评估与数据采集; 6.当前参与其他可能干扰本研究评价的干预性临床研究。

Exclusion criteria:

1. Patients with non-renal cell carcinoma, or those with an unclear pathological diagnosis; 2. Patients who have previously received systemic targeted therapy, immunotherapy, or radiotherapy, and are currently in a recurrent or widely metastatic stage; 3. Patients with severe cardiac or pulmonary dysfunction, liver or kidney failure, active infections, etc., who cannot tolerate surgery or adjuvant therapy; 4. Patients with severe psychiatric disorders, cognitive impairment, or other conditions affecting study compliance; 5. Patients unable to cooperate with postoperative follow-up or expected to be unable to complete relevant assessments and data collection during the study period; 6. Patients currently participating in other interventional clinical studies that may interfere with the evaluation of this study.

研究实施时间:

Study execute time:

From 2026-02-01 00:00:00 To 2028-02-01 00:00:00  

征募观察对象时间:

Recruiting time:

From 2026-02-01 00:00:00 To 2028-02-01 00:00:00

干预措施:

Interventions:

组别:

观察组

样本量:

500

Group:

Observation group

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):

浙江省 

市(区县):

 

Country:

China

Province:

Zhejiang

City:

单位(医院):

浙江省人民医院 

单位级别:

三级甲等 

Institution
hospital:

Zhejiang Provincial People's Hospital

Level of the institution:

Tertiary A

国家:

中国

省(直辖市):

浙江省 

市(区县):

 

Country:

China

Province:

Zhejiang

City:

单位(医院):

杭州市富阳区第一人民医院 

单位级别:

三级乙等 

Institution
hospital:

The First People's Hospital of Fuyang

Level of the institution:

Tertiary B

国家:

中国

省(直辖市):

浙江省 

市(区县):

 

Country:

China

Province:

Zhejiang

City:

单位(医院):

衢州市人民医院 

单位级别:

三级甲等 

Institution
hospital:

Quzhou People Hospital

Level of the institution:

Tertiary A

国家:

中国

省(直辖市):

浙江省 

市(区县):

 

Country:

China

Province:

Zhejiang

City:

单位(医院):

永康市第一人民医院 

单位级别:

三级乙等 

Institution
hospital:

Yongkang First People’s Hospital

Level of the institution:

Tertiary B

国家:

中国

省(直辖市):

浙江省 

市(区县):

 

Country:

China

Province:

Zhejiang

City:

单位(医院):

浙江省肿瘤医院 

单位级别:

三级甲等 

Institution
hospital:

Zhejiang Cancer Hospital

Level of the institution:

Tertiary A

测量指标:

Outcomes:

指标中文名:

病理风险等级预测准确性

指标类型:

主要指标

Outcome:

Accuracy of pathological risk classification

Type:

Primary indicator

测量时间点:

术后病理报告出具时

测量方法:

Measure time point of outcome:

When the postoperative pathological report is issued

Measure method:

指标中文名:

模型校准度

指标类型:

次要指标

Outcome:

Model calibration performance

Type:

Secondary indicator

测量时间点:

模型训练结束及验证时

测量方法:

Measure time point of outcome:

When the model training is completed and validated

Measure method:

指标中文名:

决策曲线分析的净获益

指标类型:

次要指标

Outcome:

Net clinical benefit by decision curve analysis

Type:

Secondary indicator

测量时间点:

模型完成训练和验证时

测量方法:

Measure time point of outcome:

When the model training is completed and validated

Measure method:

指标中文名:

分子分型预测准确性

指标类型:

次要指标

Outcome:

Predictive performance for molecular subtyp

Type:

Secondary indicator

测量时间点:

术后分子病理结果确认时

测量方法:

Measure time point of outcome:

When confirming the postoperative molecular pathological results

Measure method:

采集人体标本:

Collecting sample(s)
from participants:

标本中文名:

上尿路尿路上皮癌组织样本

组织:

Sample Name:

Tissue samples of upper urinary tract urothelial carcinoma

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 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

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):

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

None

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:

CRF,EDC

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

CRF,EDC

数据与安全监察委员会:

Data and Safety Monitoring Committee:

无/No

注册人:

Name of Registration:

 2026-01-21 17:52:46