Research on Endoscopic Precision Biopsy. (REPB)
Research on Endoscopic Precision Biopsy Guided by AI System
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Ruigang Wang
- Email: wrga02147@btch.edu.cn
Study Contact Backup
- Name: Xuan Jiang
- Phone Number: +86 (010)56119096
- Email: jxa01998@btch.edu.cn
Study Locations
-
-
Beijing
-
Beijing, Beijing, China, 102218
- Recruiting
- Beijing Tsinghua Changgung Hospital
-
Contact:
- Ruigang Wang
- Email: wrga02147@btch.edu.cn
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Age between 30-75;
- Those who have no mental abnormality and can conduct questionnaire surveys;
- BBPS ≥ 6;
- Colorectal advanced adenoma, and admitted for complete resection with EMR and ESD;
- Provide the relevant information required by this study and sign the informed consent.
Exclusion Criteria:
- Those who cannot provide the relevant information required by this research;
- Patients with inflammatory bowel disease;
- Those with a history of liver cirrhosis, uncontrolled hypertension, history of myocardial infarction, cardiac insufficiency, renal insufficiency, respiratory failure, diabetic ketosis and electrolyte imbalance and other serious diseases;
- Those who cannot stop antiplatelet drugs or anticoagulant drugs;
- Those who have not completed full colonoscopy;
- Pregnant women.
Study Plan
How is the study designed?
Design Details
- Observational Models: Case-Control
- Time Perspectives: Prospective
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
The accuracy of expert with or with-out AI
|
The surface of the adenoma was classified and identified by the AI system, and different areas of the adenoma were marked by distribution to guide the endoscopist for biopsy to obtain the poorly differentiated portion of the lesion.
|
|
The accuracy non-expert with or with-out AI
|
The surface of the adenoma was classified and identified by the AI system, and different areas of the adenoma were marked by distribution to guide the endoscopist for biopsy to obtain the poorly differentiated portion of the lesion.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
The accuracy of AI
Time Frame: June 2023
|
Concordance rate between biopsy and postoperative pathology
|
June 2023
|
|
The accuracy of expert with or without AI
Time Frame: June 2023
|
Concordance rate between expert experience and postoperative pathology
|
June 2023
|
|
The accuracy of non-expert with or without AI
Time Frame: June 2023
|
Concordance rate between non-expert experience and postoperative pathology
|
June 2023
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Study Chair: Ruigang Wang, Beijing Tsinghua Changgeng Hospital
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Anticipated)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 12021C1011
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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