Diagnosis Predictive Modle for Dense Density Breast Tissu... | NCT04535466

Studies
Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics

NCT04535466

Sponsor

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

Status

Unknown status

Last Update Posted

Sep 2, 2020Actual

Enrollment

1,000Estimated

Phase

Not provided

Conditions

Breast Diseases
Artificial Intelligence
Dense Breast Density
Predictive Cancer Model

Interventions

Not provided

Countries

China

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Aug 2020

Overall Recruitment Status or Expanded Access Status

Unknown status

Last Known Status

Recruiting

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Sep 1, 2020Estimated

Primary Completion Date

Sep 1, 2020Estimated

Completion Date

Sep 1, 2020Estimated

First Submitted Date

Aug 21, 2020

First Submission Date that Met QC Criteria

Aug 31, 2020

First Posted Date

Sep 2, 2020Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Aug 31, 2020

Last Update Posted Date

Sep 2, 2020Actual

Sponsor/Collaborators Module

Responsible Party, by Official Title

Yaping yang, Clinical Professor, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityPrincipal Investigator

Lead Sponsor

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityOTHER

Collaborators

Not provided

Oversight Module

Has Data Monitoring Committee (DMC)

Not provided

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief 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.

Detailed Description

Not provided

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Yes

Target Follow-Up Duration

2 Years

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

1,000Estimated

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
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

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

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

Accepts Healthy Volunteers

Sex

Female

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

80 Years

Standard Ages

AdultOlder Adult

Study Population

Female patients aged 18-80 were included in our study who were diagnosed and treated at Sun Yat-sen memorial hospital .

Sampling Method

Non-Probability Sample

Contacts/Locations Module

Central Contacts

Name	Role	Phone	Extension	Email
Yaping Yang, Doctor	Contact	86020-34071145		yangyap2@mail.sysu.edu.cn

Overall Officials

Not provided

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Breast tumor center of Sun Yat-sen Memorial Hospital	Recruiting	Guangzhou	Guangdong	510120	China

Condition Browse Module

MeSH Terms

ID	Term
D001941	Breast Diseases

Ancestor Terms

ID	Term
D012871	Skin Diseases
D017437	Skin and Connective Tissue Diseases

Browse Leaves

Not provided

Browse Branches

Not provided