Research on Endoscopic Precision Biopsy.

NCT05261932 | Unknown

• 1 other identifier: 12021C1011
• Study Type: observational
• Target: 40
• Locations: 1 country
• Sites: 1

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.

Conditions

Colorectal Adenoma

Keywords

AI system; Colonoscope; Guided Biopsy

Outcome Measures

Primary Outcomes (3)

• The accuracy of AI

  Concordance rate between biopsy and postoperative pathology

  June 2023

• The accuracy of expert with or without AI

  Concordance rate between expert experience and postoperative pathology

  June 2023

• The accuracy of non-expert with or without AI

  Concordance rate between non-expert experience and postoperative pathology

  June 2023

Study Arms (2)

The accuracy of expert with or with-out AI

Procedure: AI-assisted guided biopsy

The accuracy non-expert with or with-out AI

Procedure: AI-assisted guided biopsy

Interventions

AI-assisted guided biopsy PROCEDURE

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 accuracy of expert with or with-out AI

Eligibility Criteria

• Age: 30 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

This study has been reviewed by the hospital ethics committee. The enrolled subjects were found to have advanced colorectal adenomas during colonoscopy, and already had the pathological results of AI-assisted guided biopsy. The patients were hospitalized for complete resection with EMR and ESD and were willing to participate in this study.

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Beijing Tsinghua Chang Gung Hospital: lead

Study Sites (1)

Beijing Tsinghua Changgung Hospital

Beijing, Beijing Municipality, 102218, China

RECRUITING

Study Officials

• Ruigang Wang

  Beijing Tsinghua Changgeng Hospital

  STUDY CHAIR

Central Study Contacts

Ruigang Wang

CONTACT

wrga02147@btch.edu.cn

Xuan Jiang

CONTACT

+86 (010)56119096; jxa01998@btch.edu.cn

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 17, 2022
• First Posted: March 2, 2022
• Study Start: November 26, 2021
• Primary Completion: June 1, 2023
• Study Completion: November 30, 2023
• Last Updated: March 2, 2022

Record last verified: 2022-02

Locations

CN (1)