Artificial Intelligence Analysis for Magnetic Resonance Imaging in Screening and Diagnosis of Breast Cancer

Peking University

Status: Enrolling

Conditions: Breast Neoplasms; Magnetic Resonance Imaging

Treatments: Diagnostic Test: MRI

Study type: Observational

Funder types: Other

Identifiers

NCT05243121

AI-BMRI-S

Details and patient eligibility

About

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 mass in Chinese women, which can shorten the examination time and avoid enhanced imaging while ensuring the accuracy of the diagnosis.

Enrollment: 5,000 estimated patients

Sex: Female

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients with clinical symptoms (define as palpable mass, nipple discharge, asymmetric thickening or nodules, and abnormal skin changes)
• Patients undergoing full sequence BMRI examination
• 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.
• There are contraindications for breast-enhanced MRI examinations such as allergy to contrast agents.
• A prosthesis is implanted in the affected breast.
• Patients during lactation or pregnancy

Trial design

5,000 participants in 1 patient group

Clinically symptomatic patients

Description:

Clinically symptomatic patients (defined as palpable masses, nipple discharge, asymmetric thickening or nodules, and abnormal skin changes according to the guidelines) should be examined by BMRI at the judgment of the clinician.

Treatment:

Diagnostic Test: MRI