AI-assisted Colonoscopy Report System In Improving Reporting Quality

NCT ID: NCT05829590

Last Updated: 2023-04-25

Basic Information

• Recruitment Status: UNKNOWN
• Clinical Phase: NA
• Total Enrollment: 10 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2023-05-15
• Study Completion Date: 2023-07-31

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

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: CROSSOVER
• Primary Study Purpose: DEVICE_FEASIBILITY
• Blinding Strategy: NONE

Study Groups

with Artificial intelligence assistant system

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

Group Type: EXPERIMENTAL

Artificial intelligence assistant system

Intervention Type: DIAGNOSTIC_TEST

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

without Artificial intelligence assistant system

Endoscopists would complete the colonoscopy report without special prompts.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

Artificial intelligence assistant system

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

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

Patients:

1. Male or female ≥18 years old;

2. Able to read, understand and sign an informed consent;

3. 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;

4. Patients requiring colonoscopy.

Doctors:

1. Males or females who are over 18 years old;

2. After qualified medical education and obtaining the Physician's Practice License.

Exclusion Criteria

Patients:

1. Have drug or alcohol abuse or mental disorder in the last 5 years;

2. Pregnant or lactating women;

3. Patients with known multiple polyp syndrome;

4. patients with known inflammatory bowel disease;

5. known intestinal stenosis or space-occupying tumor;

6. known colon obstruction or perforation;

7. patients with a history of colorectal surgery;

8. Patients with a previous history of allergy to pre-used spasmolysis;

9. Unable to perform biopsy due to coagulation disorders or oral anticoagulants;

10. High-risk diseases or other special conditions that the investigator considers the subject unsuitable for participation in the clinical trial.

Doctors:

1. The researcher believes that the subjects are not suitable for participating in clinical trials.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 70 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Renmin Hospital of Wuhan University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Renmin Hospital of Wuhan Univercity

Wuhan, Hubei, China

Countries

China

Central Contacts

Honggang Yu, MD

Role: CONTACT

yuhonggang1969@163.com

13871281899

Other Identifiers

EA-23-002

Identifier Type: -

Identifier Source: org_study_id