Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics

Artificial Intelligence Clinical Trial

Official title:

Development of an Artificial Intelligence Precise Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04535466
• Other study ID #: SYSU_AI01
• Status: Recruiting
• Start date: September 1, 2020
• Est. completion date: September 1, 2020

Study information

• Verified date: August 2020
• Source: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
• Contact: Yaping Yang, Doctor
• Phone: 86020-34071145
• Email: yangyap2[@]mail.sysu.edu.cn
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

It is a prospective, observational cohort study of patients with dense breast tissue. The study was based on the radiomics and other clinicopathological information of patients to establish the diagnostic system for breast disease by using artificial intelligence.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1000
• Est. completion date: September 1, 2020
• Est. primary completion date: September 1, 2020
• Accepts healthy volunteers: No
• Gender: Female
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria:

• Female patients with dense breast density tissue

• Digital breast tomosynthesis was performed

• Breast ultrasound examination was performed

• Pathologic examination of breast lesions was performed

Exclusion Criteria:

• Incomplete clinicopathologic data

• Female patients with fatty glands of the breast

Related Conditions & MeSH terms

• Artificial Intelligence
• Breast Diseases
• Dense Breast Density
• Predictive Cancer Model

Locations

Country	Name	City	State
China	Breast tumor center of Sun Yat-sen Memorial Hospital	Guangzhou	Guangdong

Sponsors (1)

Lead Sponsor	Collaborator
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	the predictive model's area under curve(AUC)	To assess the predictive accuracy of the radiomic-based and clinical-based model by using operating characteristic curve (ROC) analysis and calculating the area under the curves (AUC).	follow up for 2 year for individuals