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注册号: Registration number: |
ChiCTR2600126186 |
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最近更新日期: Date of Last Refreshed on: |
2026-06-04 17:03:21 |
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注册时间: Date of Registration: |
2026-06-04 00:00:00 |
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注册号状态: |
预注册 |
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Registration Status: |
Prospective registration |
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注册题目: |
应用飞秒激光多模态分子成像平台构建乳腺癌多组学智能诊断与疗效预测系统 |
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Public title: |
Intelligent Multi-omics Diagnosis and Prognosis System for Breast Cancer Based on Femtosecond Laser Multimodal Molecular Imaging |
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注册题目简写: |
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English Acronym: |
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研究课题的正式科学名称: |
应用飞秒激光多模态分子成像平台构建乳腺癌多组学智能诊断与疗效预测系统 |
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Scientific title: |
Intelligent Multi-omics Diagnosis and Prognosis System for Breast Cancer Based on Femtosecond Laser Multimodal Molecular Imaging |
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研究课题代号(代码): Study subject ID: |
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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: |
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申请注册联系人: |
王钰雷 |
研究负责人: |
王钰雷 |
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Applicant: |
Yulei Wang |
Study leader: |
Yulei Wang |
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申请注册联系人电话: Applicant telephone: |
+86 18925114490 |
研究负责人电话:
Study leader's |
+86 20 83827812 |
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申请注册联系人传真 : Applicant Fax: |
研究负责人传真: Study leader's fax: |
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申请注册联系人电子邮件: Applicant E-mail: |
yuleiwang@whu.edu.cn |
研究负责人电子邮件: Study leader's E-mail: |
yuleiwang@whu.edu.cn |
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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): |
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申请注册联系人通讯地址: |
广东省茂名市茂南区为民路101号 |
研究负责人通讯地址: |
广东省茂名市为民路101号 |
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Applicant address: |
101 Weimin Road, Maoming, Guangdong |
Study leader's address: |
101 Weimin Road, Maoming City, Guangdong Province |
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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: |
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申请人所在单位: |
茂名市人民医院 |
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Applicant's institution: |
Maoming People's Hospital |
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研究负责人所在单位: |
茂名市人民医院 |
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Affiliation of the Leader: |
Maoming People's Hospital |
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是否获伦理委员会批准: |
是 |
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Approved by ethic committee: |
Yes |
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伦理委员会批件文号: Approved No. of ethic committee: |
PJ2025MI-K044-02 |
伦理委员会批件附件: Approved file of Ethical Committee: |
查看附件View |
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批准本研究的伦理委员会名称: |
茂名市人民医院医学伦理委员会 |
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Name of the ethic committee: |
Medical Ethics Committee of Maoming People's Hospital |
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伦理委员会批准日期: Date of approved by ethic committee: |
2025-09-29 00:00:00 | ||
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伦理委员会联系人: |
陈西燕 |
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Contact Name of the ethic committee: |
Chen Xiyan |
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伦理委员会联系地址: |
广东省茂名市为民路101号 |
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Contact Address of the ethic committee: |
101 Weimin Road, Maoming City, Guangdong Province |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
+86 668 2922871 |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
13432351502@163.com |
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研究实施负责(组长)单位: |
茂名市人民医院 |
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Primary sponsor: |
Maoming People's Hospital |
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研究实施负责(组长)单位地址: |
广东省茂名市为民路101号 |
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Primary sponsor's address: |
101 Weimin Road, Maoming City, Guangdong Province |
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试验主办单位(项目批准或申办者): Secondary sponsor: |
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经费或物资来源: |
茂名市人民医院临床研究项目 |
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Source(s) of funding: |
Maoming People's Hospital Clinical Research Program |
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研究疾病: |
乳腺肿瘤 ; |
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Target disease: |
Breast cancer; breast tumor |
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研究疾病代码: |
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Target disease code: |
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研究类型: |
诊断试验 |
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Study type: |
Diagnostic test |
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研究所处阶段: |
探索性研究/预试验 | ||||||||||||||||||||||
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Study phase: |
0 |
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研究设计: |
诊断试验诊断准确性 |
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Study design: |
Diagnostic test for accuracy |
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研究目的: |
精准的诊断和治疗是乳腺癌全程管理的基石。我们前期发现飞秒激光多模态分子成像技术在无标记和免制片的情况下可准确判断乳腺良恶性病灶和识别三阴性亚型,智能模型的预测效能AUC可分别达到0.99和0.97以上,同时也初步发现该技术在预测基因突变和免疫治疗疗效中具有明显优势。因此,本项目拟从临床需求出发,在人工智能辅助下深入探索该技术提取的多模态分子成像数据在预测乳腺良恶性病灶、分子分型、关键基因突变及新辅助免疫治疗疗效中的作用,旨在构建临床应用级的智能诊断与多组学疗效预测系统,并在组织原位实现模型决策特征的可视化,从组织细胞形态、微环境、细胞能量代谢等多维度表型中挖掘新型标志物,进而为乳腺癌快速诊断、有效富集基因突变检测人群、精准预测免疫治疗疗效等临床问题提供全新的解决方案。因此,本项目有望为乳腺癌快速诊断与精准治疗提供全新的策略,并为飞秒激光多模态分子成像技术在临床转化应用提供重要的参考依据。 |
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Objectives of Study: |
Our preliminary work has shown that femtosecond laser multimodal molecular imaging technology can accurately differentiate between benign and malignant breast lesions and identify the triple-negative subtype without the need for labeling or slide preparation. The predictive efficacy (AUC) of our intelligent models reached over 0.99 and 0.97, respectively. We have also initially observed that this technology offers a significant advantage in predicting gene mutations and the efficacy of immunotherapy. Therefore, this project will focus on clinical needs, utilizing Artificial Intelligence (AI) to thoroughly explore the role of multimodal molecular imaging data extracted by this technology in predicting benign/malignant breast lesions, molecular subtyping, key gene mutations, and the efficacy of neoadjuvant immunotherapy. The aim is to construct a clinical-grade intelligent diagnosis and multi-omics treatment efficacy prediction system. Furthermore, the project intends to visualize the model decision features in situ within the tissue, thereby discovering novel biomarkers from multi-dimensional phenotypes, including tissue cell morphology, microenvironment, and cellular energy metabolism. This work will provide a new solution for clinical problems such as rapid breast cancer diagnosis, effective enrichment of populations for gene mutation detection, and precise prediction of immunotherapy efficacy. |
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药物成份或治疗方案详述: |
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Description for medicine or protocol of treatment in detail: |
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纳入标准: |
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Inclusion criteria |
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排除标准: |
1.拒绝参加该临床观察性研究的患者。 |
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Exclusion criteria: |
1.Patients who refuse to participate in the clinical observational study. |
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研究实施时间: Study execute time: |
从 From 2025-10-16 00:00:00至 To 2028-10-16 00:00:00 |
征募观察对象时间: Recruiting time: |
从 From 2026-07-01 00:00:00 至 To 2028-09-30 00:00:00 |
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诊断试验: Diagnostic Tests: |
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研究实施地点: Countries of recruitment and research settings: |
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测量指标: Outcomes: |
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采集人体标本:
Collecting sample(s)
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征募研究对象情况: Recruiting status: |
尚未开始 Not yet recruiting |
年龄范围: Participant age: |
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性别: |
男女均可 |
Gender: |
Both |
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随机方法(请说明由何人用什么方法产生随机序列): |
无 |
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Randomization Procedure (please state who generates the random number sequence and by what method): |
None |
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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 |
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盲法: |
无 |
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Blinding: |
None |
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是否共享原始数据: IPD sharing |
否No |
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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): |
发表学术论文时提供原始数据 |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
Raw Data Provision Concurrent with Article Publication |
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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: |
病例报告表记录诊断结果和疗效信息,access数据库进行汇总分析 |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
The diagnostic and efficacy data captured in the Case Report Forms will be summarized and analyzed using Microsoft Access. |
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数据与安全监察委员会: Data and Safety Monitoring Committee: |
有/Yes |