Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography

NCT ID: NCT03708978

Last Updated: 2021-07-27

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

5809 participants

Study Classification

OBSERVATIONAL

Study Start Date

2018-04-05

Study Completion Date

2020-05-04

Brief Summary

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This project aims to establish a comprehensive artificial intelligence system for detecting and qualitative diagnosing breast lesions. Mammary images will be used to construct a diagnosis method based on deep learning. The system is proposed to automatically analyze the type of mammary glands, automatically identify and mark all breast lesions on the mammography images, provide the malignancy probability judgment of the lesions, the BI-RADS classification and the clinical suggestion, and also automatically generate the structured diagnosis report.

Detailed Description

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This is a multi-center study.The project contains a retrospective part(3000 samples anticipated) and a prospective part(7000 samples anticipated). In the retrospective part, investigators collected subjects with mammary images to design the deep learning method and construct a detective and diagnostic model for breast lesions. In the prospective part, investigators validate the accuracy of the constructed deep learning method, and established artificial intelligence system focusing on mammary diagnosis. Investigators will also explore the application pattern of the artificial intelligence system in clinical practice.

Conditions

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Women With Breast Cancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

OTHER

Study Groups

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mammography group

women who receives mammography because of suspected breast lesion(s)

mammography

Intervention Type DIAGNOSTIC_TEST

When a woman comes to the clinic to receive mammography. Then a radiologist will give a BI-RADS classification after reviewing the images. If a BI-RADS 4/5 is obtained, the woman will receive pathological biopsy to ensure there is a benign or malignant lesion. If a BI-RADS 3 is obtained, the woman will be followed up by a half-year interval until two year after the first mammography. At each follow up, she will receive mammography. If a BI-RADS 4/5 is obtained at follow up, she will receive pathological biopsy; if a BI-RADS 1/2/3 is obtained at follow up, she will be followed up by a half-year interval until two year. If a BI-RADS 1/2 is obtained at the first mammography, the woman will receive a second mammography after two year. During the study period, breast examination and results will be recorded for every subject. Radiologists will give the diagnosis with and without AI support.

Interventions

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mammography

When a woman comes to the clinic to receive mammography. Then a radiologist will give a BI-RADS classification after reviewing the images. If a BI-RADS 4/5 is obtained, the woman will receive pathological biopsy to ensure there is a benign or malignant lesion. If a BI-RADS 3 is obtained, the woman will be followed up by a half-year interval until two year after the first mammography. At each follow up, she will receive mammography. If a BI-RADS 4/5 is obtained at follow up, she will receive pathological biopsy; if a BI-RADS 1/2/3 is obtained at follow up, she will be followed up by a half-year interval until two year. If a BI-RADS 1/2 is obtained at the first mammography, the woman will receive a second mammography after two year. During the study period, breast examination and results will be recorded for every subject. Radiologists will give the diagnosis with and without AI support.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* the X-ray images of the breast were complete
* the results of pathological diagnosis or more than 2 years of mammography follow-up were available
* subject signs informed consent(this item was only for prospective study cases)

Exclusion Criteria

* there exists pathological diagnosis of breast lesions when receiving mammography
* there lacks pathological diagnosis or 2 years of mammography follow-up
* subject withdraws(this item was only for prospective study cases)
Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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Peking University

OTHER

Sponsor Role collaborator

Peking University Cancer Hospital & Institute

OTHER

Sponsor Role lead

Responsible Party

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Sun Ying-Shi

Chairman of Dept.Radiology

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Ying-Shi Sun, Professor

Role: STUDY_CHAIR

Peking University Cancer Hospital & Institute

Locations

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Beijing Cancer Hospital

Beijing, Beijing Municipality, China

Site Status

Beijing Chao Yang Women and Children's Health Hospital

Beijing, Beijing Municipality, China

Site Status

Beijing Da Xing People's Hospital

Beijing, Beijing Municipality, China

Site Status

Beijing Hang Tian Centre Hospital

Beijing, Beijing Municipality, China

Site Status

Beijing Nan Jiao Cancer Hospital

Beijing, Beijing Municipality, China

Site Status

Beijing Shi Jing Shan Hospital

Beijing, Beijing Municipality, China

Site Status

Beijing Shun Yi Qu Hospital

Beijing, Beijing Municipality, China

Site Status

Beijing Shun Yi Woman and Children Health Hospital

Beijing, Beijing Municipality, China

Site Status

Countries

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China

Other Identifiers

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BCA-AI

Identifier Type: -

Identifier Source: org_study_id

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