Using MRI to predict lymph node metastasis in breast cancer patients receiving chemotherapy
Novel Radiomics Signature on MRI Before and After Neoadjuvant Chemotherapy in Breast Cancer to Predict Axillary Lymph Node Metastasis and Prognosis (RBC-02)
This study is testing if special MRI scans can help predict if breast cancer has spread to lymph nodes in patients who are getting chemotherapy.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 600 (estimated) |
| Ages | 18 Years to 75 Years |
| Sex | Female |
| Sponsor | Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University Academic / other |
| Drugs / interventions | chemotherapy |
| Locations | 3 sites (Guangzhou, Guangdong and 2 other locations) |
| Trial ID | NCT04004559 on ClinicalTrials.gov |
What this trial studies
This observational study aims to develop a predictive model for axillary lymph node metastasis and prognosis in patients with invasive breast cancer who have undergone neoadjuvant chemotherapy. It utilizes multiparametric MRI scans taken before and after chemotherapy, combined with clinical data, to extract imaging signatures analyzed through deep machine learning algorithms. Patients will be monitored for five years post-treatment to assess outcomes based on histopathological examinations of surgical specimens. The goal is to enhance predictive accuracy for patient prognosis and treatment response.
Who should consider this trial
Good fit: Ideal candidates are patients diagnosed with invasive breast cancer who are scheduled to receive neoadjuvant chemotherapy and meet specific imaging and surgical criteria.
Not a fit: Patients with a history of breast or axillary surgery, inflammatory breast cancer, or those with distant metastasis will not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could significantly improve the ability to predict lymph node involvement and prognosis in breast cancer patients, leading to more personalized treatment strategies.
How similar studies have performed: Other studies utilizing radiomics and machine learning in cancer prognosis have shown promising results, indicating potential for success in this novel approach.
Eligibility criteria
Show full inclusion / exclusion criteria
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.
Where this trial is running
Guangzhou, Guangdong and 2 other locations
- Sun Yat-sen University Cancer Center — Guangzhou, Guangdong, China (Recruiting)
- Zhongshan Ophthalmic Center, Sun Yat-Sen University — Guangzhou, Guangdong, China (Not_yet_recruiting)
- Sun Yat-Sen Memorial Hospital of Sun Yat-sen University — Guangzhou, Guangdong, China (Recruiting)
Study contacts
- Principal investigator: Chuanmiao Xie, PhD — Sun Yat-sen University
- Study coordinator: Herui Yao, Ph. D
- Email: yaoherui@mail.sysu.edu.cn
- Phone: +8613500018020
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.