PET-MRI for Axillary Staging in Node Negative Breast Cancer Patients
Overview
Axillary lymph node status is an important prognostic factor for patients with breast cancer. After breast cancer diagnosis, current nodal staging consists of axillary ultrasound (US) combined with tissue sampling when deemed necessary. In case of positive axillary lymph nodes, patients will undergo axillary lymph node dissection (ALND). In case of no suspicious axillary lymph nodes (i.e. clinically node negative patients), patients will undergo sentinel lymph node biopsy (SLNB). This surgical nodal staging is accompanied by co-morbidity. In theory, if non-invasive imaging can evaluate the lymph node status accurately, a node negative patient would no longer have to undergo axillary surgery. Since MRI is suitable for soft tissue imaging and PET has the advantage of showing increased metabolic uptake in lymph node metastases, a combination of these techniques in hybrid PET/MRI would be highly desirable. If dedicated axillary hybrid PET/MRI is equally accurate to SLNB for the detection of negative axillary lymph nodes, work-up could be more efficient by bypassing SLNB. However, the accuracy of dedicated axillary hybrid PET/MRI needs to be compared with the pathological outcome of SLNB (gold standard) first.
Full Title of Study: “Non-invasive Axillary Lymph Node Staging in Breast Cancer With PET-MRI”
Study Type
- Study Type: Interventional
- Study Design
- Allocation: N/A
- Intervention Model: Single Group Assignment
- Primary Purpose: Diagnostic
- Masking: None (Open Label)
- Study Primary Completion Date: December 2023
Interventions
- Diagnostic Test: Dedicated axillary hybrid PET-MRI
- All clinically node negative patients will undergo a hybrid PET-MRI axilla preoperatively, followed by breast surgery and SLNB.
Arms, Groups and Cohorts
- Experimental: Dedicated axillary hybrid PET-MRI axilla
Clinical Trial Outcome Measures
Primary Measures
- Accuracy of dedicated hybrid PET/MRI
- Time Frame: Participants will be followed from the moment of first outpatient clinic visit until final breast surgery, an expected average of 4 weeks
- Accuracy (sensitivity, negative predictive value (NPV) and false negative rate (FNR)) of dedicated axillary hybrid PET/MRI to exclude axillary lymph node metastases will be calculated.
Secondary Measures
- Accuracy of T2w MRI, DWI and Hybrid PET/MRI
- Time Frame: Participants will be followed from the moment of first outpatient clinic visit until final breast surgery, an expected average of 4 weeks
- Accuracy (sensitivity, negative predictive value (NPV) and false negative rate (FNR)) of three MRI sequences (T2w, DWI and hybrid PET/MRI) to exclude axillary lymph node metastases will be calculated separately as well.
Participating in This Clinical Trial
Inclusion Criteria
1. Female patient with histologically confirmed breast cancer and clinically confirmed negative lymph nodes in the axilla, scheduled to undergo SLNB 2. Patients who are willing and able to undergo the study procedures 3. The patient has provided personally written informed consent Exclusion Criteria:
1. Patients treated with neoadjuvant systemic therapy prior to axillary nodal staging 2. Patients with clinically positive axillary lymph nodes 3. Age < 18 years 4. Inability to provide informed consent 5. Pregnancy 6. Weight >100 kg (because of the format of the PET/MRI scanner) 7. General contraindications for MRI (such as pacemaker, aneurysm clips, metallic device in their body, severe claustrophobia) or PET (i.e. known allergy to 18F-FDG) 8. Hyperglycaemia (> 11 mmol/L) at the time of 18F-FDG injection
Gender Eligibility: Female
Minimum Age: 18 Years
Maximum Age: N/A
Are Healthy Volunteers Accepted: No
Investigator Details
- Lead Sponsor
- Maastricht University Medical Center
- Collaborator
- Erasmus Medical Center
- Provider of Information About this Clinical Study
- Sponsor
Clinical trials entries are delivered from the US National Institutes of Health and are not reviewed separately by this site. Please see the identifier information above for retrieving further details from the government database.