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

August 13, 2019 updated by: Herui Yao, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

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.

Study Type

Observational

Enrollment (Anticipated)

1500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • China
    • Guangdong
      • Dongguan, Guangdong, China, 523000
        • Not yet recruiting
        • Tungwah Hospital of Sun Yat-Sen University
        • Contact:
        • Principal Investigator:
          • Jie Ouyang, PhD
      • Foshan, Guangdong, China, 528300
        • Recruiting
        • Shunde Hospital of Southern Medical University
        • Contact:
        • Principal Investigator:
          • Qiugen Hu, PhD
        • Sub-Investigator:
          • Xiaohong Li, MD
      • Guangzhou, Guangdong, China, 510000
        • Not yet recruiting
        • Sun Yat-Sen University Cancer Center
        • Contact:
        • Principal Investigator:
          • Chuanmiao Xie, PhD
        • Sub-Investigator:
          • Nian Lu, MD
      • Guangzhou, Guangdong, China, 510120
        • Recruiting
        • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
        • Contact:
        • Sub-Investigator:
          • Yufang Yu, MD
        • Sub-Investigator:
          • Yujie Tan, MD
        • Sub-Investigator:
          • Kai Chen, MD
      • Guangzhou, Guangdong, China, 510000
        • Not yet recruiting
        • Zhongshan Ophthalmic Center, Sun Yat-sen University
        • Contact:
        • Contact:
        • Sub-Investigator:
          • Wenben Chen, MD

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

16 years to 73 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

Female

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.

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Retrospective

Cohorts and Interventions

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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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.
5 years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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.
baseline (Completed MRI data before biopsy,surgery,neoadjuvant and radiotherapy.)
Lymph node metastasis
Time Frame: Baseline
The value of Radiomics of multiparametric MRI in predicting axillary lymph node metastasis.
Baseline
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.
5 years
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 years
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
5 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Collaborators

Sun Yat-sen University
Zhongshan Ophthalmic Center, Sun Yat-sen University
Southern Medical University, China
Tungwah Hospital of Sun Yat-Sen University

Investigators

  • 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, Southern Medical University, China
  • Principal Investigator: Haotian Lin, PhD, Zhongshan Ophthalmic Center, Sun Yat-sen University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 28, 2019

Primary Completion (Anticipated)

May 31, 2020

Study Completion (Anticipated)

January 1, 2025

Study Registration Dates

First Submitted

June 26, 2019

First Submitted That Met QC Criteria

June 28, 2019

First Posted (Actual)

July 1, 2019

Study Record Updates

Last Update Posted (Actual)

August 15, 2019

Last Update Submitted That Met QC Criteria

August 13, 2019

Last Verified

August 1, 2019

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • SYSEC-KY-KS-2019-054-001

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

IPD 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.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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