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出境医 / 临床实验 / Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01)
Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01)
Study Description
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.
Study Design
| 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 |
Arms 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.
|
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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.
|
Outcome Measures
Primary Outcome Measures :
- 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 :
- 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.
- Lymph node metastasis [ Time Frame: Baseline ]The value of Radiomics of multiparametric MRI in predicting axillary lymph node metastasis.
- 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.
- 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
- 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
Eligibility Criteria
| 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
Contacts and Locations
Contacts
| Contact: Herui Yao, PhD | +8613500018020 | yaoherui@mail.sysu.edu.cn | |
| Contact: Yunfang Yu, MD | +8613660238987 | yuyf9@mail.sysu.edu.cn |
Locations
| 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
| 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 |
| Tracking Information | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| First Submitted Date | June 26, 2019 | |||||||||||||||
| First Posted Date | July 1, 2019 | |||||||||||||||
| Last Update Posted Date | August 15, 2019 | |||||||||||||||
| Actual Study Start Date | May 28, 2019 | |||||||||||||||
| Estimated Primary Completion Date | May 31, 2020 (Final data collection date for primary outcome measure) | |||||||||||||||
| Current Primary Outcome Measures |
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.
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| Original Primary Outcome Measures | Same as current | |||||||||||||||
| Change History | ||||||||||||||||
| Current Secondary Outcome Measures |
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| Original Secondary Outcome Measures | Same as current | |||||||||||||||
| Current Other Pre-specified Outcome Measures | Not Provided | |||||||||||||||
| Original Other Pre-specified Outcome Measures | Not Provided | |||||||||||||||
| Descriptive Information | ||||||||||||||||
| Brief Title | Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01) | |||||||||||||||
| Official Title | Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01) | |||||||||||||||
| 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. | |||||||||||||||
| 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 | |||||||||||||||
| Study Design | Observational Model: Cohort Time Perspective: Retrospective |
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| Target Follow-Up Duration | Not Provided | |||||||||||||||
| Biospecimen | Not Provided | |||||||||||||||
| 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. | |||||||||||||||
| Condition |
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| Intervention | Other: No interventions
As this is a patient registry, there are no interventions.
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| Study Groups/Cohorts |
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| Publications * | Not Provided | |||||||||||||||
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* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline. |
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| Recruitment Information | ||||||||||||||||
| Recruitment Status | Recruiting | |||||||||||||||
| Estimated Enrollment |
1500 | |||||||||||||||
| Original Estimated Enrollment | Same as current | |||||||||||||||
| Estimated Study Completion Date | January 1, 2025 | |||||||||||||||
| Estimated Primary Completion Date | May 31, 2020 (Final data collection date for primary outcome measure) | |||||||||||||||
| Eligibility Criteria |
Inclusion Criteria:
Exclusion Criteria:
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| Sex/Gender |
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| Ages | 18 Years to 75 Years (Adult, Older Adult) | |||||||||||||||
| Accepts Healthy Volunteers | No | |||||||||||||||
| Contacts |
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| Listed Location Countries | China | |||||||||||||||
| Removed Location Countries | ||||||||||||||||
| Administrative Information | ||||||||||||||||
| NCT Number | NCT04003558 | |||||||||||||||
| Other Study ID Numbers | SYSEC-KY-KS-2019-054-001 | |||||||||||||||
| Has Data Monitoring Committee | No | |||||||||||||||
| U.S. FDA-regulated Product |
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| IPD Sharing Statement |
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| Responsible Party | Herui Yao, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University | |||||||||||||||
| Study Sponsor | Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University | |||||||||||||||
| Collaborators |
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| Investigators |
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| PRS Account | Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University | |||||||||||||||
| Verification Date | August 2019 | |||||||||||||||
