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

NCT05243121 | Unknown

• 1 other identifier: AI-BMRI-S
• Study Type: observational
• Target: 5,000
• Locations: 1 country
• Sites: 1

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.

Conditions

Breast Neoplasms; Magnetic Resonance Imaging

Keywords

breast neoplasms; magnetic resonance imaging; screening; deep learning; machine learning

Outcome Measures

Primary Outcomes (1)

• Breast Cancer Screening

  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.

  5 years

Secondary Outcomes (2)

• The accuracy of radiologists and deep learning models

  5 years

• Health economics

  5 years

Study Arms (1)

Clinically symptomatic patients

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.

Diagnostic Test: MRI

Interventions

MRI DIAGNOSTIC_TEST

undergoing enhanced MRI

Clinically symptomatic patients

Eligibility Criteria

• Gender Eligibility Details: Female
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

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.

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• Peking University People's Hospital: lead

Study Sites (1)

Peking university people's hospital

Beijing, Beijing Municipality, 100044, China

RECRUITING

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Central Study Contacts

Yi Wang, doctor

CONTACT

86+010-88325813; wangyi@pkuph.edu.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 6 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director

Study Record Dates

• First Submitted: September 12, 2021
• First Posted: February 16, 2022
• Study Start: February 28, 2022
• Primary Completion: September 30, 2025
• Study Completion: September 30, 2025
• Last Updated: February 16, 2022

Record last verified: 2022-02

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)