Research on Endoscopic Precision Biopsy.

• Conditions: Colorectal Adenoma
• Interventions: Procedure: AI-assisted guided biopsy

• Registration Number: NCT05261932
• Lead Sponsor: Beijing Tsinghua Chang Gung Hospital

Brief Summary

Colorectal adenoma is a common disease and frequently-occurring disease in gastroenterology. With the continuous progress of colonoscopy equipment and the gradual improvement of endoscopic accessories, especially the development of chromo-endoscopy and magnifying endoscopy. The observation of the surface structure and capillary morphology of colorectal adenomas can realize optical biopsy. Currently, most clinical endoscopic diagnosis of colorectal diseases is biopsy under colonoscopy, and further treatment options are determined based on the pathological results of the biopsy. The problem is that the pathological diagnosis of some preoperative biopsy is not completely consistent with the pathological diagnosis of postoperative large specimens. Previous studies have found that the pathological diagnosis accuracy rate of preoperative biopsy is only 66-75%, so there is a certain degree of subjectivity in relying solely on colonoscopy white light biopsy. Based on the previous work, the research team has initially established an intelligent recognition model for colorectal adenoma classification (low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia), and formed a colorectal adenoma of a certain size with annotated endoscopic image data set. Using the YOLO-V4 algorithm, under the Darknet framework, to train an artificial intelligence (AI) system which specifically for adenoma recognition and diagnosis, its accuracy rate has reached more than 90%. This study intends to increase the sample size based on the previous work, and further improve the accuracy of the classification and diagnosis of the AI system, so as to guide the endoscopist to perform targeted biopsy and improve the accuracy of preoperative biopsy.

Detailed Description

Not available

Study Timeline

• Study Start: 2021-11-26
• Status Verified: 2022-02
• Study First Submitted: 2022-02-17
• Study First Submitted QC: 2022-02-28
• Last Update Submitted: 2022-02-28
• Study First Posted: 2022-03-02
• Last Update Posted: 2022-03-02
• Primary Completion: 2023-06-01
• Study Completion: 2023-11-30

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 40

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 & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
The accuracy non-expert with or with-out AI	AI-assisted guided biopsy	-
The accuracy of expert with or with-out AI	AI-assisted guided biopsy	-

Primary Outcome Measures

Name	Time	Method
The accuracy of expert with or without AI	June 2023	Concordance rate between expert experience and postoperative pathology
The accuracy of non-expert with or without AI	June 2023	Concordance rate between non-expert experience and postoperative pathology
The accuracy of AI	June 2023	Concordance rate between biopsy and postoperative pathology

Trial Locations

Locations (1)

Beijing Tsinghua Changgung Hospital; 🇨🇳 Beijing, Beijing, China