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.
Complete breast MRI data;
Negative pathology biopsy results or negative follow-up examinations for at least 12 months for non-cancer cases;
Positive biopsy results that meet the requirements for the pathological subtype of cancer for cancer cases;
Original data that can be used to verify clinical status, including radiological and pathological reports;
Partial mastectomy or puncture biopsy on the diseased side of the breast prior to breast MRI examination;
Poor image quality;
Implants in the affected breast;
Participants who underwent breast MR examinations at five institutions from 2014 to 2024 were enrolled. A test cohort prospectively collected at Peking University People's Hospital Health Examination Center, was enrolled to assess the robustness of the model.
Cohort
Other
Non-contrast breast MRI diagnostic model
Diagnostic testAn integrated AI model capable of generating synthetic contrast-enhanced images and distinguishing between benign and malignant lesions, as well as performing risk stratification
8
Treatment groupsSee each treatment group below.
MRI examination
A multi-parameter contrast-enhanced breast MRI examination was performed, including fat-suppressed T2-weighted imaging, diffusion-weighted imaging, dynamic contrast-enhanced sequences, and fat-suppressed T1-weighted imaging.
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