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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

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

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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 related topics: Breast Cancer




Primary Outcome Measures :
  1. 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



Information from the National Library of Medicine

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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.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03851497


Locations
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China, Beijing
Peking Union Medical College Hospital
Beijing, Beijing, China, 100730
Sponsors and Collaborators
Peking Union Medical College Hospital
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
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Responsible Party: Peking Union Medical College Hospital
ClinicalTrials.gov Identifier: NCT03851497    
Other Study ID Numbers: S-detect 2019
First Posted: February 22, 2019    Key Record Dates
Last Update Posted: March 26, 2021
Last Verified: March 2021

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Additional relevant MeSH terms:
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Breast Neoplasms
Neoplasms by Site
Neoplasms
Breast Diseases
Skin Diseases