Non-Contrast Breast MRI Diagnosis and Risk Stratification Using DWI-Generated Synthetic Contrast Enhancement

This study is conducted under the ethics-approved project titled "Artificial Intelligence Solution for Simplifying the Diagnostic Workflow of Breast MRI''.The goal of this observational study is to develop an integrated breast MRI system that uses diffusion-weighted imaging (DWI) to create synthetic contrast-enhanced images. This system aims to diagnose and screen for breast cancer without the need for contrast agents, while using a generated risk score to perform imaging-based triage and risk stratification. Participants will include people aged 18 and older who require a breast MRI either for evaluation of a suspicious finding or for high-risk screening. This study seeks to answer two main questions: * Can synthetic contrast-enhanced images generated from DWI match real contrast-enhanced images in their ability to distinguish benign from malignant breast lesions? * Can the risk score derived from DWI-based synthetic images enable imaging-level risk stratification, allowing people at lower risk to avoid contrast agent injection? Researchers will compare the quality of synthetic images against real contrast-enhanced images and will recruit radiologists to assess how well these images perform for diagnostic and screening tasks. MRI data from participants undergoing breast MRI will be used to train, validate, and test this integrated system.

NCT Number	NCT07598084
Lead Sponsor	Peking University People's Hospital
Conditions	Breast Neoplasms, Artificial Intelligence (AI), Magnetic Resonance Imaging (MRI), Diffusion Magnetic Resonance Imaging, Deep Learning
Enrollment	12,000 participants
Start Date	2026-06
Primary Completion	2026-12 (estimated)
Study Completion	2027-05 (estimated)
Updated on ClinicalTrials.gov	2026-06-09