AI-assisted Colonoscopy Report System In Improving Reporting Quality

Wuhan University

Status: Not yet enrolling

Conditions: Artificial Intelligence; Colonoscopy

Treatments: Diagnostic Test: Artificial intelligence assistant system

Study type: Interventional

Funder types: Other

Identifiers

NCT05829590

EA-23-002

Details and patient eligibility

About

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.

Enrollment: 10 estimated patients

Sex: All

Ages: 18 to 70 years old

Volunteers: Accepts Healthy Volunteers

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.

Trial design

Primary purpose: Device Feasibility

Allocation: Randomized

Interventional model: Crossover Assignment

Masking: None (Open label)

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10 participants in 2 patient groups

with Artificial intelligence assistant system

Experimental group

Description:

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

Treatment:

Diagnostic Test: Artificial intelligence assistant system

without Artificial intelligence assistant system

No Intervention group

Description:

Endoscopists would complete the colonoscopy report without special prompts.