Status:
NOT_YET_RECRUITING
AI-Based Self-Supervised Learning Model Using Non-Contrast Breast MRI for Early Screening and Clinical Utility Evaluation
Lead Sponsor:
Second Affiliated Hospital, School of Medicine, Zhejiang University
Collaborating Sponsors:
Alibaba DAMO Academy
Conditions:
Breast Cancer Detection
Early Detection of Cancer
Eligibility:
FEMALE
30-70 years
Phase:
NA
Brief Summary
Breast cancer is the most common malignant disease among women worldwide, with rising incidence and younger age at onset in China. Early detection is critical for improving survival, yet current scree...
Detailed Description
This is a prospective, investigator-initiated clinical study designed to evaluate the role of radiomics and artificial intelligence in non-invasive, early detection and diagnosis of breast cancer. Whi...
Eligibility Criteria
Inclusion
- Female, age 30-70 years
- Completed breast MRI scan, including at least T2WI, DWI, and ADC sequences
- Multimodal data acquired within the same time window (≤90 days)
- A clear clinical outcome: pathologically confirmed or ≥12-24 months of negative follow-up
- The time window between imaging examination and outcome determination was ≤90 days
- Signed informed consent
Exclusion
- Absolute contraindications to MRI (pacemaker, cochlear implant, ocular metal foreign body, etc.)
- Pregnant or lactating women
- Recent history of breast surgery/radiotherapy (≤6 months) or imaging after neoadjuvant therapy
- Substandard image quality (severe motion artifact, signal-to-noise ratio below threshold)
- Incomplete clinical data or time window exceeded
- Known breast cancer metastasis or recurrence
Key Trial Info
Start Date :
October 1 2025
Trial Type :
INTERVENTIONAL
Allocation :
ESTIMATED
End Date :
December 1 2027
Estimated Enrollment :
30000 Patients enrolled
Trial Details
Trial ID
NCT07205276
Start Date
October 1 2025
End Date
December 1 2027
Last Update
October 3 2025
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