Axillary Lymph Node, Invasive Breast Cancer, Neoadjuvant Chemotherapy, Prognosis, Radiomics
Conditions
Keywords
Invasive Breast Cancer, Neoadjuvant Chemotherapy, Radiomics, Axillary Lymph Node Metastasis, Survival, Machine Learning Analysis
Brief summary
This study is aimed to illustrate whether Radiomics combining multiparametric MRI before and after neoadjuvant chemotherapy (NACT) with clinical data is a good way to predict axillary lymph node metastasis and prognosis in invasive-breast-cancer.
Detailed description
This study proposes to build a clinical predictive model to predict axillary lymph node metastasis and prognosis in invasive-breast-cancer patients who received neoadjuvant chemotherapy before surgery. The model is built based on breast MRI signatures extracted and analyzed via deep machine-learning algorithm methods. Invasive breast cancer patients undergo multiparametric MRI at baseline, then undergo multiparametric MRI after received neoadjuvant chemotherapy for at least 4 cycles as planned. After the surgery, responses to neoadjuvant chemotherapy are determined according to the histopathologically examination of the surgically resected specimens. After completion of treatment procedure, patients are followed up for 5 years.
Interventions
OTHERNo interventions
As this is a patient registry, there are no interventions.
Sponsors
Sun Yat-sen University
Tungwah Hospital of Sun Yat-Sen University
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to 75 Years
Healthy volunteers
No
Inclusion criteria
1. Primary lesion diagnosed as invasive breast cancer; 2. Imaging examination confirmed no distant organ metastasis; 3. Received neoadjuvant chemotherapy for drugs such as taxanes, anthracyclines, and platinum as planned; 4. Completed breast MRI examination before or after neoadjuvant chemotherapy; 5. Accepted breast cancer surgery and axillary lymph node dissection; 6. Eastern Cooperative Oncology Group performance status 0-2.
Exclusion criteria
1. History of ipsilateral axillary or breast surgery; 2. Inflammatory breast cancer; 3. Bilateral breast cancer; 4. Malignant tumor history in 5 years; 5. Patients with cervical or contralateral axillary lymph node metastasis; 6. Incomplete imaging or medical history data.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Disease free survival (DFS) | 5 years | The association between Radiomics of multiparametric MRI and 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
| Measure | Time frame | Description |
|---|---|---|
| pathological complete response (pCR) | Pathologic evaluation will be performed for each patient within 1 week after surgery | The value of Radiomics of breast MRI in predicting responses to neoadjuvant chemotherapy, including reaching pCR and not reaching pCR. |
| Pathological axillary lymph node status | Pathologic evaluation will be performed for each patient within 1 week after surgery | The value of Radiomics of breast MRI in predicting pathological axillary lymph node status is defined as axillary lymph node metastasis exists or not. |
| Overall survival (OS) | 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. |
| Breast cancer specific motality (BCSM) | 5 years | Defined as time between randomization and the time of death occur specific due to breast cancer |
| Recurrence free survival (RFS) | 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 |
Countries
China
Contacts
Primary ContactHerui Yao, Ph. D
Backup ContactYunfang Yu, MD
Outcome results
None listed