Using MRI to predict chemotherapy response in liver metastasis of breast cancer
Clinical Study of Dynamic Contrast-enhanced Magnetic Resonance Imaging Combined With IVIM-DWI for Early Prediction of Chemosensitivity in Liver Metastasis of Breast Cance
Zhejiang Cancer Hospital · NCT05550090
This study is testing if special MRI scans can help doctors predict how well chemotherapy will work for breast cancer patients with liver metastases.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 40 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Zhejiang Cancer Hospital (other) |
| Drugs / interventions | chemotherapy |
| Locations | 1 site (Hangzhou, Zhejiang) |
| Trial ID | NCT05550090 on ClinicalTrials.gov |
What this trial studies
This observational study aims to utilize dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to predict the early chemotherapy sensitivity of liver metastases in breast cancer patients. By analyzing changes in functional parameters from MRI scans taken before and after chemotherapy, the study seeks to identify biomarkers that can guide treatment decisions. Additionally, artificial intelligence will be employed to analyze imaging data for improved prediction of treatment outcomes.
Who should consider this trial
Good fit: Ideal candidates include patients with pathologically confirmed breast cancer and liver metastasis, who are planning to undergo systemic chemotherapy.
Not a fit: Patients with contraindications to MRI or those with diffuse liver disease may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could enable earlier and more accurate predictions of chemotherapy response, leading to optimized treatment plans for patients with liver metastasis of breast cancer.
How similar studies have performed: While the use of MRI in predicting chemotherapy response is established, the specific combination of DCE-MRI and IVIM-DWI for this purpose in liver metastasis of breast cancer is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. The primary lesion was pathologically confirmed to be breast cancer, and the patients diagnosed by two imaging methods or pathologically confirmed to be liver metastasis of breast cancer had at least one liver metastasis with the longest diameter ≥ 10mm; 2. No second primary malignant tumor; 3. ECOG score, 0-2 ; 4. The organ function is normal and can tolerate chemotherapy and other anti-tumor treatments; 5. The patient plans to receive systemic chemotherapy or systemic anti-tumor treatment, and the whole process of cooperative treatment. The patient has good compliance with the planned treatment and follow-up, can understand the research process of this study and sign a written informed consent; 6. Contraception during the study period and within 6 months after treatment, non lactation period. Exclusion Criteria: 1. For patients contraindicated to MR examination, such as built-in metal instruments and allergy to contrast agents; 2. The patient had diffuse liver metastasis or the number of liver metastatic tumors was more than 5; 3. Patients who cannot complete 2 cycles of chemotherapy or systemic anti-tumor treatment; 4. Unable to cooperate with follow-up; 5. Patients who are not suitable for the study according to the investigator.
Where this trial is running
Hangzhou, Zhejiang
- Zhejiang Cancer Hospital — Hangzhou, Zhejiang, China (RECRUITING)
Study contacts
- Principal investigator: Ping Huang — Zhejiang Cancer Hospital
- Study coordinator: Ping Huang
- Email: zlyyhp@163.com
- Phone: +8613685766632
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.
Conditions: Metastatic Breast Cancer in the Liver, Liver metastasis, Breast cancer, Efficacy prediction