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

Recruiting

• Conditions: Breast Neoplasms; Magnetic Resonance Imaging
• Interventions: Diagnostic Test: MRI

• Registration Number: NCT05243121
• Lead Sponsor: Peking University People's Hospital

Brief Summary

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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2021-09-12
• Status Verified: 2022-02
• Study First Submitted QC: 2022-02-07
• Last Update Submitted: 2022-02-07
• Study First Posted: 2022-02-16
• Last Update Posted: 2022-02-16
• Study Start: 2022-02-28
• Primary Completion: 2025-09-30
• Study Completion: 2025-09-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: Female
• Target Recruitment: 5000

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

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Clinically symptomatic patients	MRI	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.

Primary Outcome Measures

Name	Time	Method
Breast Cancer Screening	5 years	Compare the area under the curve of the deep learning model of the BMRI full sequence, contrast-enhanced and non-contrast-enhanced sequence in the diagnosis of breast cancer.

Secondary Outcome Measures

Name	Time	Method
The accuracy of radiologists and deep learning models	5 years	Under the conditions of BMRI full sequence, contrast-enhanced and non-contrast-enhanced sequences, compare the sensitivity, specificity, positive predictive value and negative predictive value of breast tumor detection by radiologists and deep learning models.
Health economics	5 years	Compare the examination time, reading time and cost of BMRI full sequence, contrast-enhanced and non-contrast-enhanced sequences.

Trial Locations

Locations (1)

Peking university people's hospital; 🇨🇳 Beijing, Beijing, China