Clinical Application of an AI-based Dissection Trajectory Prediction System (ADTPS) in Endoscopic Submucosal Dissection

NCT07757906 | Not Yet Recruiting

• 1 other identifier: 2026SDU-QILU-4
• Study Type: interventional
• Target: 160
• Locations: 0 countries
• Sites: N/A

Brief Summary

In this prospective paired diagnostic study and single-center, randomized controlled trial, patients with early esophageal squamous neoplasia or high-grade intraepithelial neoplasia meeting the inclusion and exclusion criteria will be enrolled in a paired diagnostic cohort (60 patients) and subsequently randomly assigned (1:1) to receive endoscopic submucosal dissection (ESD) with AI-based Dissection Trajectory Prediction System (ADTPS) guidance or conventional ESD (without AI). Clinical data and operator workload scores (NASA-TLX) are collected during the procedure, and postoperative follow-up assessments are performed at days 1, 3, 7, and 14. The study aims to analyze the impact of ADTPS on the mean single-dissection time and operator workload in patients undergoing ESD by comparing the efficacy differences between the experimental and control groups. Additionally, the study investigates the effects of ADTPS on other postoperative complications including R0 resection rate, muscularis propria injury, intraoperative bleeding, perforation (acute and delayed), and total procedure time; conducts a comparative analysis of the safety and efficiency of AI-assisted versus conventional ESD; and develops effective clinical strategies for optimizing dissection trajectory and reducing complications in endoscopic submucosal dissection.

Conditions

Esophageal Squamous Cell Carcinoma (ESCC); High-Grade Intraepithelial Neoplasia; AI-Based Dissection Trajectory Prediction System

Keywords

Artificial intelligence; R0 resection; Procedural efficiency; NASA-TLX; Randomized controlled trial; Dissection trajectory prediction; Endoscopic submucosal dissection

Outcome Measures

Primary Outcomes (2)

• NASA-TLX Workload Score

  Immediately after the ESD procedure

• Mean Single Dissection Time

  During the ESD procedure

Secondary Outcomes (7)

• R0 Resection Rate

  At the time of pathological examination

• Muscularis Propria Injury Rate

  During the ESD procedure

• Intraoperative Bleeding Episodes

  During the ESD procedure

• Intraoperative Perforation Rate

  During the ESD procedure

• Delayed Bleeding Rate

  Within 14 days after procedure

Study Arms (2)

Conventional ESD without AI

ACTIVE COMPARATOR

Device: Conventional ESD Procedure

AI-assisted ESD with ADTPS

EXPERIMENTAL

Device: AI-based Dissection Trajectory Prediction System (ADTPS)

Interventions

AI-based Dissection Trajectory Prediction System (ADTPS) DEVICE

The ADTPS is an artificial intelligence software system that analyzes endoscopic images in real time during ESD. It automatically identifies lesion boundaries and generates a recommended dissection trajectory overlaid on the endoscopic view. The endoscopist follows the AI-generated trajectory to perform submucosal dissection. The system provides visual guidance only and does not alter the standard surgical workflow.

AI-assisted ESD with ADTPS

Conventional ESD Procedure DEVICE

The same endoscopic hardware platform is used, but the AI-based Dissection Trajectory Prediction System (ADTPS) is turned off. The endoscopist performs the ESD procedure based solely on clinical judgment and personal experience, following standard conventional ESD steps including marking, injection, circumferential incision, and submucosal dissection.

Conventional ESD without AI

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Chinese patients aged 18-80 years.
• Lesions meeting ESD indications for esophageal, gastric, or colorectal early cancer or high-grade intraepithelial neoplasia, as defined by:
• Non-invasive tumors regardless of size; or
• Differentiated-type intramucosal carcinoma without ulceration, regardless of size; or
• Differentiated-type intramucosal carcinoma with ulceration and a diameter ≤3 cm; or
• Undifferentiated-type intramucosal carcinoma without ulceration and a diameter ≤2 cm.
• Planned to undergo ESD treatment.
• No prior treatment for the lesion (including ESD, surgery, radiotherapy, chemotherapy, etc.).
• Platelet count \>100 × 10⁹/L and PT-INR \<1.5, with antiplatelet agents (aspirin, clopidogrel, etc.) discontinued for at least 5 days.
• American Society of Anesthesiologists (ASA) physical status grade I or II.
• Voluntarily signed informed consent.

You may not qualify if:

• Patients currently undergoing dialysis.
• Patients with severe cardiopulmonary disease or other severe comorbidities that may increase the risk of the ESD procedure.
• Pregnant or breastfeeding women.

Sponsors & Collaborators

• Qilu Hospital of Shandong University: lead

MeSH Terms

Conditions

Esophageal Squamous Cell Carcinoma

Condition Hierarchy (Ancestors)

Carcinoma, Squamous Cell; Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Squamous Cell; Esophageal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Head and Neck Neoplasms; Digestive System Diseases; Esophageal Diseases; Gastrointestinal Diseases

Central Study Contacts

Zhen Li

CONTACT

18560086106; qilulizhen@sdu.edu.cn

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, CARE PROVIDER
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 6, 2026
• First Posted: August 11, 2026
• Study Start: July 29, 2026
• Primary Completion (Estimated): July 28, 2027
• Study Completion (Estimated): October 1, 2027
• Last Updated: August 11, 2026

Record last verified: 2026-07

Data Sharing

• IPD Sharing: Will not share