Evaluation of the Clinical Effectiveness of Upper Gastrointestinal Endoscopy Reporting System

Study Overview
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Brief Summary
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The objective of this study is to assess the effectiveness of an AI-based reporting system for upper gastrointestinal endoscopy. The primary question that this study aims to address is whether the reporting system can enhance the completeness and accuracy of endoscopic reports when assisted by AI, as drafted by endoscopists. Patients will be randomly assigned to either the experimental group or the control group. In the experimental group, physicians will draft EGD reports with the assistance of the AI-based reporting system, while in the control group, physicians will use the conventional reporting system to draft EGD reports. At the same time, the AI-based reporting system will automatically generate a report of the EGD examination.

Official Title
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A Single-center, Prospective, Parallel Randomized Controlled Study Evaluating the Clinical Effectiveness of an Intelligent Graphic Report System for Upper Gastrointestinal Endoscopy

Conditions
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Endoscopy, Gastrointestinal, Artificial Intelligence

Intervention / Treatment
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* Diagnostic Test: AI-based reporting system


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Aged 18 years Aim to undergo screening, surveillance, and diagnosis Undergo sedated EGD Able to read, understand, and sign informed consent Exclusion Criteria: EGD contraindications Not suitable for sedated endoscopy after anaesthesia evaluation Biopsy contraindications Active upper gastrointestinal bleeding or emergency oesophagogastroduodenoscopy (EGD) Pregnancy Upper gastrointestinal surgery or residual stomach Not suitable for recruitment after investigator evaluation because of other high-risk conditions

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Experimental group<br>Physicians draft EGD reports with the assistance of the AI-based reporting system. | Diagnostic Test: AI-based reporting system<br>* AI-based reporting system is a software platform for real-time analysis and records of abnormalities and landmarks during endoscopy.<br>|
| No Intervention: Control group<br>Physicians use the conventional reporting system to draft EGD reports. At the same time, the AI-based reporting system will automatically generate a report of the EGD examination. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Completeness of reporting lesions | Calculation method = number of report lesions / total number of lesions x 100% | one month | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Completeness of report drafting on lesion features | Calculation method = number of drafted features of lesions / total number of features required to be drafted x 100% | one month | 
| Accuracy of report drafting on lesion features | Calculation method = number of accurately drafted features of lesions / total number of drafted features x 100% | one month | 
| Reporting time | The time that endoscopists draft reports | one month | 
| Completeness of reporting lesions of AI system | Calculation method = number of report lesions / total number of lesions x 100% | one month | 
| Accuracy of report drafting on lesion features of AI system | Calculation method = number of accurately drafted features of lesions / total number of drafted features x 100% | one month | 
| Physician satisfaction survey | Use 5-point Likert scale to assess physician satisfaction, acceptance, and trust in using the intelligent graphic report system to draft endoscopic reports. | one month |