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

Study Overview
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Brief Summary
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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
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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.

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

Conditions
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Breast Neoplasm Female, Early-stage Breast Cancer, Radiomics, Axillary Lymph Node, Survival, Prosthesis

Intervention / Treatment
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* Other: No interventions


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 75 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Sun Yat-Sen Memorial Hospital of Sun Yat-sen University<br>The cohort of Sun Yat-Sen Memorial Hospital of Sun Yat-sen University is a training cohort. | Other: No interventions<br>* As this is a patient registry, there are no interventions.<br>|
| Sun Yat-sen University Cancer Center<br>The cohort of Sun Yat-sen University Cancer Center is a validation cohort. | Other: No interventions<br>* As this is a patient registry, there are no interventions.<br>|
| Tungwah Hospital of Sun Yat-Sen University<br>The cohort of Tungwah Hospital of Sun Yat-Sen University is a validation cohort. | Other: No interventions<br>* As this is a patient registry, there are no interventions.<br>|
| Shunde hospital of southern medical university<br>The cohort of Shunde hospital of southern medical university is a validation cohort. | Other: No interventions<br>* As this is a patient registry, there are no interventions.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Disease free survival (DFS) | 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 | 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 | The value of Radiomics of multiparametric MRI in predicting axillary lymph node metastasis. | Baseline | 
| Overall survival (OS) | 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) | Defined as time between randomization and the time of death occur specific due to breast cancer | 5 years | 
| Recurrence free survival (RFS) | 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 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Early-stage Breast Cancer, Radiomics, Axillary lymph node metastasis, Tumor microenvironment, Survival, Deep learning