AI-assisted Colonoscopy Report System In Improving Reporting Quality

NCT05829590 | Unknown

• 1 other identifier: EA-23-002
• Study Type: interventional
• Target: 10
• Locations: 1 country
• Sites: 1

Brief Summary

In this study, the investigators proposed a prospective study about the effectiveness of speech and image recognition-based system in improving reporting quality during colonoscopy for colonoscopy report quality in endoscopists. The participants would be divided into two groups. For the collected colonoscopy videos, group A would record their observations with the assistance of the artificial intelligence system. The artificial intelligence assistant system can automatically capture bowel segment images and prompt abnormal lesions. Group B would complete the endoscopy report without special prompts. After a period of washout period, the two groups switched, that is, group A without AI assistance and group B with AI assistance to complete the colonoscopy report. Then, the completeness of the colonoscopy report, the completeness of capturing anatomical landmarks and detected lesions, the completeness of structured description, the accuracy of lesion reporting, the time for reporting and the satisfaction with the reporting system are compared with or without AI assistance.

Conditions

Artificial Intelligence; Colonoscopy

Outcome Measures

Primary Outcomes (1)

• The integrity of colonoscopy report

  Report integrity with or without AI-assisted. Calculation method = number of information recorded / total number of information need to record x 100%

  One month

Secondary Outcomes (1)

• The integrity of capturing anatomical landmarks

  One month

Other Outcomes (5)

• The integrity of report lesion

  One month

• The completeness of structured description

  One month

• Accuracy of lesion reporting

  One month

Study Arms (2)

with Artificial intelligence assistant system

EXPERIMENTAL

Endoscopists would complete the colonoscopy report with the assistance of the artificial intelligence system.

Diagnostic Test: Artificial intelligence assistant system

without Artificial intelligence assistant system

NO INTERVENTION

Endoscopists would complete the colonoscopy report without special prompts.

Interventions

Artificial intelligence assistant system DIAGNOSTIC_TEST

The artificial intelligence assistant system can automatically capture bowel segment images and prompt abnormal lesions based on speech recognition and deep learning.

with Artificial intelligence assistant system

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patients:
• Male or female ≥18 years old;
• Able to read, understand and sign an informed consent;
• The investigator believes that the subjects can understand the process of the clinical study, are willing and able to complete all study procedures and follow-up visits, and cooperate with the study procedures;
• Patients requiring colonoscopy.
• Doctors:
• Males or females who are over 18 years old;
• After qualified medical education and obtaining the Physician's Practice License.

You may not qualify if:

• Patients:
• Have drug or alcohol abuse or mental disorder in the last 5 years;
• Pregnant or lactating women;
• Patients with known multiple polyp syndrome;
• patients with known inflammatory bowel disease;
• known intestinal stenosis or space-occupying tumor;
• known colon obstruction or perforation;
• patients with a history of colorectal surgery;
• Patients with a previous history of allergy to pre-used spasmolysis;
• Unable to perform biopsy due to coagulation disorders or oral anticoagulants;
• High-risk diseases or other special conditions that the investigator considers the subject unsuitable for participation in the clinical trial.
• Doctors:
• \. The researcher believes that the subjects are not suitable for participating in clinical trials.

Sponsors & Collaborators

• Renmin Hospital of Wuhan University: lead

Study Sites (1)

Renmin Hospital of Wuhan Univercity

Wuhan, Hubei, 430060, China

Location

Central Study Contacts

Honggang Yu, MD

CONTACT

13871281899; yuhonggang1969@163.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: DEVICE FEASIBILITY
• Intervention Model: CROSSOVER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 2, 2023
• First Posted: April 25, 2023
• Study Start: May 15, 2023
• Primary Completion: June 15, 2023
• Study Completion: July 31, 2023
• Last Updated: April 25, 2023

Record last verified: 2023-03

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)