Development and Clinical Validation of a Diffusion-Weighted Imaging-Based Synthetic Contrast-Enhanced MRI System for Non-Contrast Breast Cancer Diagnosis and Risk Stratification
Sponsor: Peking University People's Hospital
Trial Details
| Condition | Breast Neoplasms, Artificial Intelligence (AI), Magnetic Resonance Imaging (MRI), Diffusion Magnetic Resonance Imaging, Deep Learning |
| Intervention | Non-contrast breast MRI diagnostic model |
| Status | Not_yet_recruiting |
| Participants | 12,000 |
| Est. Completion | 1 Dec 2026 |
| Last Updated | 9 June 2026 |
Primary Outcome
MRI examination
Eligibility Criteria
Inclusion Criteria
Inclusion Criteria: 1. Complete breast MRI data; 2. Negative pathology biopsy results or negative follow-up examinations for at least 12 months for non-cancer cases; 3. Positive biopsy results that meet the requirements for the pathological subtype of cancer for cancer cases; 4. Original data that can be used to verify clinical status, including radiological and pathological reports; Exclusion Criteria: 1. Partial mastectomy or puncture biopsy on the diseased side of the breast prior to breast MRI examination; 2. Poor image quality; 3. Implants in the affected breast;
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