AI-assisted Endoscopy Report System In Improving Reporting Quality

A Single-center Study of an AI-assisted Endoscopy Report System In Improving Reporting Quality

In this study, we proposed a prospective study about the effectiveness of artificial intelligence system for endoscopy report quality in endoscopists. The subjects would be divided into two groups. For the collected endoscopic videos, group A would complete the endoscopy report with the assistance of the artificial intelligence system. The artificial intelligence assistant system can automatically capture images, prompt abnormal lesions and the parts covered by the examination (the upper gastrointestinal tract is divided into 26 parts). Group B would complete the endoscopy report without special prompts. After a period of forgetting, the two groups switched, that is, group A without AI assistance and group B with AI assistance to complete the endoscopy report. Then, the completeness of the report lesion, the accuracy of the lesion location, the completeness of the lesion and the standard part in the captured images, and so on were compared with or without AI assistance.

Study Overview

• Status: Recruiting
• Conditions: Artificial Intelligence; Endoscopy
• 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
  • Wuhan, China, 430060
    • Recruiting
    • Renmin Hospital of Wuhan University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 70 years (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion Criteria:

1. Males or females who are over 18 years old;
2. After qualified medical education and obtained the Certificate of Chinese medical practitioner;

Exclusion Criteria:

1. Doctors without qualified medical education and didn't obtaine the Certificate of Chinese medical practitioner;
2. 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
• Masking: NONE

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
EXPERIMENTAL: with Artificial intelligence assistant system; Endoscopists would complete the endoscopy report with the assistance of the artificial intelligence system.	Diagnostic test: Artificial intelligence assistant system; The artificial intelligence assistant system can automatically capture images, prompt abnormal lesions and the parts covered by the examination (the stomach is divided into 26 parts).
NO_INTERVENTION: without Artificial intelligence assistant system; Endoscopists would complete the endoscopy report without special prompts.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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
Accuracy of lesion location	Accuracy of lesion location with or without AI-assisted. Calculation method = number of lesion with correct location / total number of lesions x 100%	one month
Integrity of lesion in captured images	Lesion integrity in captured images with or without AI-assisted. Calculation method = number of lesions in captured images / total number of lesions x 100%	one month
Integrity of standard part in captured images	Lesion integrity in captured images with or without AI-assisted. Calculation method = number of standard parts in captured images / the actual number of standard parts covered by the examination x 100%	one month

Collaborators and Investigators

• Sponsor: Renmin Hospital of Wuhan University

Study record dates

Study Major Dates

• Study Start (ACTUAL): November 1, 2021
• Primary Completion (ANTICIPATED): December 1, 2022
• Study Completion (ANTICIPATED): December 1, 2022

Study Registration Dates

• First Submitted: July 27, 2022
• First Submitted That Met QC Criteria: July 27, 2022
• First Posted (ACTUAL): July 29, 2022

Study Record Updates

• Last Update Posted (ACTUAL): August 10, 2022
• Last Update Submitted That Met QC Criteria: August 8, 2022
• Last Verified: July 1, 2022

More Information

Terms related to this study

• Other Study ID Numbers: EA-21-010

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