AI-assisted Colonoscopy Report System In Improving Reporting Quality

Speech and Image Recognition Based System in Improving Reporting Quality During Colonoscopy

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Artificial Intelligence; Colonoscopy
• Intervention / Treatment: Diagnostic test: Artificial intelligence assistant system

• Study Type: Interventional
• Enrollment (Anticipated): 10
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Honggang Yu, MD; Phone Number: 13871281899; Email: yuhonggang1969@163.com

Study Locations

• China
  • Hubei
    • Wuhan, Hubei, China, 430060
      • Renmin Hospital of Wuhan Univercity

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

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.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Device Feasibility
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: with Artificial intelligence assistant system; Endoscopists would complete the colonoscopy report with the assistance of the artificial intelligence system.	Diagnostic test: 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.
No Intervention: without Artificial intelligence assistant system; Endoscopists would complete the colonoscopy report without special prompts.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
The integrity of capturing anatomical landmarks	The integrity in captured bowel landmrak images with or without AI-assisted. Calculation method = number of anatomical landmarks in captured images / total number of anatomical landmarks x 100%	One month

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
The integrity of report lesion	Report lesion integrity with or without AI-assisted. Calculation method = number of report lesions / total number of lesions x 100%	One month
The completeness of structured description	The completeness of structured description with or without AI-assisted. Calculation method = number of structured descriptions / total number of structured descriptions need to record x 100%	One month
Accuracy of lesion reporting	Accuracy of lesion report with or without AI-assisted. Calculation method = number of lesions with correct description / total number of lesions descriptionx 100%	One month
The time for reporting	The time for reporting with or without AI-assisted	One month
The satisfaction with the reporting system	The satisfaction with the reporting system with or without AI-assisted	One month

Collaborators and Investigators

• Sponsor: Renmin Hospital of Wuhan University

Study record dates

Study Major Dates

• Study Start (Anticipated): May 15, 2023
• Primary Completion (Anticipated): June 15, 2023
• Study Completion (Anticipated): July 31, 2023

Study Registration Dates

• First Submitted: April 2, 2023
• First Submitted That Met QC Criteria: April 13, 2023
• First Posted (Actual): April 25, 2023

Study Record Updates

• Last Update Posted (Actual): April 25, 2023
• Last Update Submitted That Met QC Criteria: April 13, 2023
• Last Verified: March 1, 2023

More Information

Terms related to this study

• Other Study ID Numbers: EA-23-002

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No