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NCT Number: NCT07495137

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

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.

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Key information

Conditions

Endoscopic Submucosal Dissection Endoscopic Submucosal Dissection (ESD)

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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;
  • Patients who voluntarily sign the informed consent form.

Exclusion criteria

  • 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.

Treatment and study plan

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.

Primary outcomes

  1. Average single hemostasis time

    Time frame: Periprocedural

Secondary outcomes

  1. Incidence of postoperative complications

    Time frame: 14 days post-procedure

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

  2. Total operation duration

    Time frame: Periprocedural

  3. Psychological stress experienced by the endoscopist

    Time frame: Periprocedural

    Be evaluated subjectively on a five point scale

Study contacts

Contact information is provided by the study sponsor or research team.

Zhen Li

CONTACT

[email protected]

+86-18560086106

Sponsors and collaborators

Lead sponsor

Qilu Hospital of Shandong University

Other

Collaborators

  • Qianfoshan Hospital
  • Shandong Provincial Hospital

Registry information

Official study title

The Improvement Effect of Real-time Artificial Intelligence Assisted Identification of Bleeding Points on Hemostasis Efficiency in Endoscopic Submucosal Dissection (ESD): a Multicenter, Randomized Controlled Trial

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Mar 27, 2026
Registry last updated
Mar 27, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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