Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
With
Sun Yat-sen University
Tungwah Hospital of Sun Yat-Sen University
Southern Medical University, China
Zhongshan Ophthalmic Center, Sun Yat-sen University
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.
Age
18–75
Sex
FEMALE
Healthy volunteers
Not accepted
You may be eligible if
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
You may not be if
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
Clareo Health | Deep Learning Algorithms for Prediction of Lymph Node Metastasis and Prognosis in Breast Cancer MRI Radiomics (RBC-01)
