Clinical trial NCT03708978: Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography
Official title: Development of Artificial Intelligence System for Detection and Diagnosis of Breast Lesion Using Mammography
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Women With Breast Cancer
Lead sponsor: Peking University Cancer Hospital & Institute
Sponsor class: OTHER
Collaborators: name: Peking University
First posted: 2018-10-17
Enrollment: 5809
Sex: FEMALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: OTHER
Sampling method: PROBABILITY_SAMPLE
Study population: Women with suspected Breast Lesion

Brief summary: 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: 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.

Eligibility criteria: 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)

Primary outcomes:
measure: benign-malignant diagnosis accuracy
timeFrame: from the first mammography to pathological result obtained(an average of 3 weeks if mammography BI-RADS 4 or 5 obtained)
measure: benign-malignant diagnosis accuracy
timeFrame: from the first mammography to 2-year-after mammography
Secondary outcomes:
measure: lesion detection accuracy
timeFrame: from the first mammography to radiologist diagnosis (within 3 days after the mammography taken)
Other outcomes:
Locations:
city: Beijing
country: China
facility: Beijing Cancer Hospital
state: Beijing
city: Beijing
country: China
facility: Beijing Chao Yang Women and Children's Health Hospital
state: Beijing
city: Beijing
country: China
facility: Beijing Da Xing People's Hospital
state: Beijing
city: Beijing
country: China
facility: Beijing Hang Tian Centre Hospital
state: Beijing
city: Beijing
country: China
facility: Beijing Nan Jiao Cancer Hospital
state: Beijing
city: Beijing
country: China
facility: Beijing Shi Jing Shan Hospital
state: Beijing
city: Beijing
country: China
facility: Beijing Shun Yi Qu Hospital
state: Beijing
city: Beijing
country: China
facility: Beijing Shun Yi Woman and Children Health Hospital
state: Beijing
Study officials:
affiliation: Peking University Cancer Hospital & Institute
name: Ying-Shi Sun, Professor
role: STUDY_CHAIR
References: