Application of Deep-learning and Ultrasound Elastography in Opportunistic Screening of Breast Cancer

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.

ClinicalTrials.gov Identifier: NCT03851497

Recruitment Status : Completed

First Posted : February 22, 2019

Last Update Posted : March 26, 2021

Sponsor:

Collaborators:

Peking University Third Hospital

Beijing Hospital

Beijing Chao Yang Hospital

Beijing Zhongguancun Hospital

Peking University Aerospace Centre Hospital

Beijing Anzhen Community Health Service Center

First Hospital of Tsinghua University

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

The First Affiliated Hospital of Zhengzhou University

Henan Provincial People's Hospital

Third Affiliated Hospital of Zhengzhou University

Xinxiang Central Hospital

Henan Cancer Hospital

First Hospital of China Medical University

Shengjing Hospital

Liaoning Cancer Hospital & Institute

West China Hospital

Sichuan Provincial People's Hospital

Yan'an Hospital of Kunming City

Xi'an Central Hospital

Ningxia Medical University

First Hospital of Shijiazhuang City

Chengde Central Hospital

Qinghai Province Cancer Hospital

Gansu Cancer Hospital

Shanghai Zhongshan Hospital

Ruijin Hospital

The Affiliated Hospital of Qingdao University

Qingdao Central Hospital

Shandong Jining No.1 People's Hospital

Linyi Tumour Hospital

The First Affiliated Hospital of Shanxi Medical University

The Second Affiliated Hospital of Harbin Medical University

Second Hospital of Jilin University

The Second Hospital of the West Coast New Area of Qingdao

Fudan University

Tongji Hospital

Jiangsu Province People's Hospital

Peking University Shougang Hospital

Gansu Jiugang Hospital

Information provided by (Responsible Party):

Peking Union Medical College Hospital

Study Description

Brief Summary:

As the most common cancer expected to occur all over the world, breast cancer still faces with the unsatisfied diagnostic accuracy in US imaging. S-detect is a sophisticated CAD system for breast US imaging based on deep learning algorithms. E-breast is a software installed in US machines which automatically reveals tumor elastographic features. This multi-center study intends to further validate the diagnostic efficiency of S-detect and E-breast in opportunistic breast cancer screening populations in China. Our hypothesis is that S-detect and E-breast can increase the diagnostic accuracy and specificity as compared to routinely US examinations by doctors.

Condition or disease
Breast Cancer

Study Design

Layout table for study information

Study Type :	Observational
Actual Enrollment :	1200 participants
Observational Model:	Cohort
Time Perspective:	Prospective
Official Title:	A Multi-center Study of Deep Learning Diagnosis and Ultrasound Elastography in Opportunistic Screening of Breast Cancer
Actual Study Start Date :	January 1, 2019
Actual Primary Completion Date :	January 1, 2021
Actual Study Completion Date :	January 1, 2021

Resource links provided by the National Library of Medicine

MedlinePlus Genetics related topics: Breast cancer

MedlinePlus related topics: Breast Cancer

U.S. FDA Resources

Groups and Cohorts

Outcome Measures

Primary Outcome Measures :

Benign or malignant lesions as determined by pathology [ Time Frame: From 2019.1.1 to 2020.1.1 ]
The pathological diagnosis of benign or malignant lesions from surgery samples

Eligibility Criteria

Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.

Layout table for eligibility information

Ages Eligible for Study:	18 Years and older (Adult, Older Adult)
Sexes Eligible for Study:	Female
Gender Based Eligibility:	Yes
Gender Eligibility Description:	Biologically Female
Accepts Healthy Volunteers:	No
Sampling Method:	Probability Sample

Study Population

Asymptomatic female patients voluntarily asked for breast US examination in comprehensive hospitals for breast cancer screening.

Criteria

Inclusion Criteria:

Female over 18 years of age;
Had breast lesions detected by ultrasound.
No clinical symptoms such as nipple discharge, while breast lesions were not palpable.
Received breast surgery within one week of ultrasound examination.
Agreed to participant in this study and signed informed consent.

Exclusion Criteria:

Patients who had received a biopsy of breast lesion before the ultrasound examination.
Patients who were pregnant or lactating.
Patients who were undergoing neoadjuvant treatment.

Contacts and Locations