Artificial Intelligence Analysis for Magnetic Resonance Imaging in Screening Breast Cancer in High-risk Women

Peking University People's Hospital Breast Center

Use Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI. Build an abbreviated protocal, and investigate whether an abbreviated protocol was suitable for breast magnetic resonance imaging screening for breast cancer in high-risk Chinese women, which can shorten the examination time and avoid enhanced imaging while ensuring the accuracy of the diagnosis.

Inclusion Criteria:

• Patients undergoing full sequence BMRI examination
• Written informed consent and complete the clinical data questionnaire
• Through the follow-up database, at least 6 months of follow-up results can be obtained to determine whether the diagnosis result is negative/benign/malignant; for patients who need pathological biopsy, the pathological biopsy results shall prevail to determine the lesion benign/malignant.

Exclusion Criteria:

• The breast had received radiotherapy, chemotherapy, biology and other treatments before BMRI.
• Signs or symptoms of breast disease
• There are contraindications for breast-enhanced MRI examinations such as allergy to contrast agents.
• Patients during lactation or pregnancy