The Improvement Effect of Real-time Artificial Intelligence Assisted Identification of Bleeding Points on Hemostasis Efficiency in Endoscopic Submucosal Dissection

Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18-80
SponsorQilu Hospital of Shandong University

About this trial

The goal of this clinical trial is to learn if an artificial intelligence (AI) system that identifies bleeding points in real time can help stop bleeding faster during endoscopic submucosal dissection (ESD) - a minimally invasive surgery for early digestive tract cancer or precancerous lesions. It will also learn about the AI system's effect on surgery-related problems (like perforation or delayed bleeding) and total surgery time.

The main questions it aims to answer are:

1. Does the AI system shorten the time it takes to stop each bleed during ESD? 2. How does the AI system affect the rate of surgery-related problems and total surgery time?

Researchers will compare two groups to see if the AI system improves hemostasis efficiency:

1. AI group: During ESD, the AI system will real-time spot and mark bleeding points. Doctors will use these marks to stop bleeding. 2. Control group: Doctors will use the same equipment but without the AI system - they will find and stop bleeding using their own experience.

Participants will:

1. Have ESD surgery for esophageal, stomach, or colorectal lesions that need this treatment; 2. Be randomly assigned to either the AI group or the control group; 3. Attend follow-up checks in 14 days after surgery to check for complications; 4. Have their surgery videos reviewed by experts to record hemostasis time and total surgery time.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Aged 18-80 years;

Lesions meet the indications for ESD treatment of the esophagus, stomach, or colorectum according to relevant guidelines;

Anticoagulant drugs have been suspended according to relevant guidelines;

Patients with American Society of Anesthesiologists (ASA) classification Grade I or II;

Disqualifiers

Patients with severe cardiopulmonary diseases, coagulation dysfunction or other severe comorbidities that may increase surgical risks;

Patients undergoing dialysis treatment;

Pregnant or lactating women;

Deemed unsuitable for participation in this study by the principal investigator or other researchers.

Trial design

Design model

Parallel

Treatments tested in this trial

  • AI real-time assistance in endoscopic submucosal dissection (ESD) for bleeding spot identification and marking

    Device

    Patients undergo ESD with real-time AI assistance. During the operation, the pre-trained and validated AI system continuously analyzes endoscopic images to automatically identify and mark active bleeding points in real time. Endoscopists perform hemostatic operations (e.g., coagulation with hemostatic forceps or electrosurgical knives) based on the AI-generated marks to target bleeding sites promptly.

Treatment groups

160 Participants
are divided into 2 treatment groups
Group A: AI-assisted GroupExperimental treatment 1 intervention
Group B: Conventional treatment groupNo intervention 0 interventions

Trial outcomes

Primary outcomes

1

Average single hemostasis time

Time frame
Periprocedural

Secondary outcomes

1

Incidence of postoperative complications

Complications include intraoperative and postoperative perforation, damage to the muscularis propria, etc

Time frame
14 days post-procedure
2

Total operation duration

Time frame
Periprocedural
3

Psychological stress experienced by the endoscopist

Be evaluated subjectively on a five point scale

Time frame
Periprocedural

Other outcomes

Locations

This trial has no locations.

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Qilu Hospital of Shandong University

Lead sponsor

Qianfoshan Hospital

Collaborator

Shandong Provincial Hospital

Collaborator

This trial is not recruiting at the moment. You can still explore other options: