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

Sun Yat-sen University

Status: Enrolling

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

Treatments: Other: No interventions

Study type: Observational

Funder types: Other

Identifiers

NCT04003558

SYSEC-KY-KS-2019-054-001

Details and patient eligibility

About

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.

Full 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.

Enrollment: 1,500 estimated patients

Sex: Female

Ages: 18 to 75 years old

Volunteers: No Healthy Volunteers

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

Trial design

1,500 participants in 4 patient groups

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

Description:

The cohort of Sun Yat-Sen Memorial Hospital of Sun Yat-sen University is a training cohort.

Treatment:

Other: No interventions

Sun Yat-sen University Cancer Center

Description:

The cohort of Sun Yat-sen University Cancer Center is a validation cohort.

Treatment:

Other: No interventions

Tungwah Hospital of Sun Yat-Sen University

Description:

The cohort of Tungwah Hospital of Sun Yat-Sen University is a validation cohort.

Treatment:

Other: No interventions

Shunde hospital of southern medical university

Description:

The cohort of Shunde hospital of southern medical university is a validation cohort.

Treatment:

Other: No interventions