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Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04003558
Recruitment Status : Recruiting
First Posted : July 1, 2019
Last Update Posted : August 15, 2019
Sponsor:
Collaborators:
Sun Yat-sen University
Tungwah Hospital of Sun Yat-Sen University
Shunde Hospital of Southern Medical University
Zhongshan Ophthalmic Center, Sun Yat-sen University
Information provided by (Responsible Party):
Herui Yao, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Brief Summary:
This bi-directional, multicentre study aims to assess multiparametric MRI Radiomics-based prediction model for identifying metastasis lymph nodes and prognostic prediction in breast cancer.

Condition or disease Intervention/treatment
Breast Neoplasm Female Early-stage Breast Cancer Radiomics Axillary Lymph Node Survival, Prosthesis Other: No interventions

Detailed Description:
Sensitivity for prediction of lymph node metastasis and survival of currently available prognostic scores in limited. This study proposes to establish a deep learning algorithms of multiparametric MRI radiomics and nomogram for identifying lymph node metastasis and prognostic prediction of breast cancer. The study will investigate the relationship between the radiomics and the tumor microenvironment. The study includes the construction of multiparametric MRI radiomics-based prediction model and the validation of the prediction model.

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Study Type : Observational
Estimated Enrollment : 1500 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01)
Actual Study Start Date : May 28, 2019
Estimated Primary Completion Date : May 31, 2020
Estimated Study Completion Date : January 1, 2025

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Breast Cancer

Group/Cohort Intervention/treatment
Sun Yat-Sen Memorial Hospital of Sun Yat-sen University
The cohort of Sun Yat-Sen Memorial Hospital of Sun Yat-sen University is a training cohort.
Other: No interventions
As this is a patient registry, there are no interventions.

Sun Yat-sen University Cancer Center
The cohort of Sun Yat-sen University Cancer Center is a validation cohort.
Other: No interventions
As this is a patient registry, there are no interventions.

Tungwah Hospital of Sun Yat-Sen University
The cohort of Tungwah Hospital of Sun Yat-Sen University is a validation cohort.
Other: No interventions
As this is a patient registry, there are no interventions.

Shunde hospital of southern medical university
The cohort of Shunde hospital of southern medical university is a validation cohort.
Other: No interventions
As this is a patient registry, there are no interventions.




Primary Outcome Measures :
  1. Disease free survival (DFS) [ Time Frame: 5 years ]
    Disease free survival (DFS), which defined as the time from the diagnosis of breast cancer to the confirmed time of metastatic disease, or death due to any other cause.


Secondary Outcome Measures :
  1. The correlation of radiomics features and tumor microenvironment [ Time Frame: baseline (Completed MRI data before biopsy,surgery,neoadjuvant and radiotherapy.) ]
    Radiomics is a tool to analyze tumor microenvironment characteristics based on breast MRI images.

  2. Lymph node metastasis [ Time Frame: Baseline ]
    The value of Radiomics of multiparametric MRI in predicting axillary lymph node metastasis.

  3. Overall survival (OS) [ Time Frame: 5 years ]
    The association between Radiomics of multiparametric MRI and overall survival (OS), which defined as the time from the beginning of diagnosis of breast cancer to the death with any causes.

  4. Beast cancer specific motality (BCSM) [ Time Frame: 5 years ]
    Defined as time between randomization and the time of death occur specific due to breast cancer

  5. Recurrence free survival (RFS) [ Time Frame: 5 years ]
    defined as time between randomization and the time of any recurrence of ipsilateral chest, breast, regional lymph node recurrence, distant metastases, or death occurred



Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.


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Ages Eligible for Study:   18 Years to 75 Years   (Adult, Older Adult)
Sexes Eligible for Study:   Female
Gender Based Eligibility:   Yes
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Patients who had early stage breast cancer and completed the breast MRI examination before operation,lymph node biopsy,neoadjuvant chemotherapy,and radiotherapy.
Criteria

Inclusion Criteria:

  • The primary lesion was diagnosed as invasive breast cancer
  • Patients can have regional lymph node metastasis,but no distant organ metastasis
  • Complete the breast MRI examination before treatment
  • Accept breast cancer surgery or lymph node biopsy
  • Eastern Cooperative Oncology Group performance status 0-2

Exclusion Criteria:

  • Inflammatory breast cancer
  • Accompanied with other primary malignant tumors
  • Perform surgery,radiotherapy and lymph node biopsy before breast MRI examination
  • Patients who have neoadjuvant chemotherapy
  • Patients had distant and contralateral axillary lymph node metastasis
  • The pathologic diagnosis was extensive ductal carcinoma in situ

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04003558


Contacts
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Contact: Herui Yao, PhD +8613500018020 yaoherui@mail.sysu.edu.cn
Contact: Yunfang Yu, MD +8613660238987 yuyf9@mail.sysu.edu.cn

Locations
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China, Guangdong
Tungwah Hospital of Sun Yat-Sen University Not yet recruiting
Dongguan, Guangdong, China, 523000
Contact: Jie Ouyang, PhD    +8613537479470    kitty865@163.com   
Principal Investigator: Jie Ouyang, PhD         
Shunde hospital of southern medical university Recruiting
Foshan, Guangdong, China, 528300
Contact: Qiugen Hu, PhD    +8613928206009    hu6009@163.com   
Principal Investigator: Qiugen Hu, PhD         
Sub-Investigator: Xiaohong Li, MD         
Sun Yat-sen University Cancer Center Not yet recruiting
Guangzhou, Guangdong, China, 510000
Contact: Chuanmiao Xie, PhD    +8618903050011    xiechm@sysucc.org.cn   
Principal Investigator: Chuanmiao Xie, PhD         
Sub-Investigator: Nian Lu, MD         
Zhongshan Ophthalmic Center, Sun Yat-Sen University Not yet recruiting
Guangzhou, Guangdong, China, 510000
Contact: Haotian Lin, PhD    +8613802793086    gddlht@aliyun.com   
Contact: Wenben Chen, MD    +8618819472798    Weberchan@foxmail.com   
Principal Investigator: Haotian Lin, PhD         
Sub-Investigator: Wenben Chen, MD         
Sun Yat-Sen Memorial Hospital of Sun Yat-sen University Recruiting
Guangzhou, Guangdong, China, 510120
Contact: Herui Yao, PhD    +8613500018020    yaoherui@mail.sysu.edu.cn   
Principal Investigator: Herui Yao, PhD         
Sub-Investigator: Yufang Yu, MD         
Sub-Investigator: Yujie Tan, MD         
Sub-Investigator: Kai Chen, MD         
Sponsors and Collaborators
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Sun Yat-sen University
Tungwah Hospital of Sun Yat-Sen University
Shunde Hospital of Southern Medical University
Zhongshan Ophthalmic Center, Sun Yat-sen University
Investigators
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Study Chair: Herui Yao, PhD Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Principal Investigator: Chuanmiao Xie, PhD Sun Yat-sen University
Principal Investigator: Jie Ouyang, PhD Tungwah Hospital of Sun Yat-Sen University
Principal Investigator: Qiugen Hu, PhD Shunde Hospital of Southern Medical University
Principal Investigator: Haotian Lin, PhD Zhongshan Ophthalmic Center, Sun Yat-sen University
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Responsible Party: Herui Yao, Principal Investigator, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
ClinicalTrials.gov Identifier: NCT04003558    
Other Study ID Numbers: SYSEC-KY-KS-2019-054-001
First Posted: July 1, 2019    Key Record Dates
Last Update Posted: August 15, 2019
Last Verified: August 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Plan Description: Requests for the individual data or study documents will be considered where the proposed use aligns with public good purposes, does not conflict with other requests, and the requestor is willing to sign a data access agreement. Contact is though the corresponding author.

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Herui Yao, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University:
Early-stage Breast Cancer
Radiomics
Axillary lymph node metastasis
Tumor microenvironment
Survival
Deep learning
Additional relevant MeSH terms:
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Breast Neoplasms
Neoplasm Metastasis
Prosthesis Failure
Neoplasms by Site
Neoplasms
Breast Diseases
Skin Diseases
Neoplastic Processes
Pathologic Processes
Postoperative Complications