Esophageal Squamous Cell Carcinoma (ESCC)NCT07757906
Clinical Application of an AI-based Dissection Trajectory Prediction System (ADTPS) in Endoscopic Submucosal Dissection
A study testing AI-based Dissection Trajectory Prediction System (ADTPS) and Conventional ESD Procedure in people with Esophageal Squamous Cell Carcinoma (ESCC) and High-Grade Intraepithelial Neoplasia, run by Qilu Hospital of Shandong University at 1 site in China.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Esophageal Squamous Cell Carcinoma (ESCC), High-Grade Intraepithelial Neoplasia, AI-Based Dissection Trajectory Prediction System
- What is being tested?
- AI-based Dissection Trajectory Prediction System (ADTPS) and Conventional ESD Procedure
- Type of treatment
- Injection or infusion, Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 220 participants
- Where
- 1 siteChina
- Study dates
- 29 Jul 2026to 1 Oct 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
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- Voluntarily signed informed consent.
- 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.
Who cannot join
- 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.
- RCT
- 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.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Clinical Application of an AI-based Dissection Trajectory Prediction System (ADTPS) in Endoscopic Submucosal Dissection: A Prospective Paired Diagnostic Study and a Randomized Controlled Clinical Trial
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
- Being tested
- AI-based Dissection Trajectory Prediction System (ADTPS), Conventional ESD Procedure
- Keywords
- Artificial intelligence, R0 resection, Procedural efficiency, NASA-TLX, Randomized controlled trial, Dissection trajectory prediction, Endoscopic submucosal dissection
- Medical subject headings
- Esophageal Squamous Cell Carcinoma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
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.
Conventional ESD ProcedureDevice
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.
| Study group | Role | What they receive |
|---|---|---|
| Conventional ESD without AI | Active comparator | Not described Receives: Device: Conventional ESD Procedure |
| AI-assisted ESD with ADTPS | Experimental | Not described Receives: Device: AI-based Dissection Trajectory Prediction System (ADTPS) |
What is being measured
The primary outcome is the main question the study is designed to answer.
NASA-TLX Workload Score
Measured: Immediately after the ESD procedure
Mean Single Dissection Time
Measured: During the ESD procedure
Secondary outcomes (7)
R0 Resection Rate
Measured: At the time of pathological examination
Muscularis Propria Injury Rate
Measured: During the ESD procedure
Intraoperative Bleeding Episodes
Measured: During the ESD procedure
Intraoperative Perforation Rate
Measured: During the ESD procedure
Delayed Bleeding Rate
Measured: Within 14 days after procedure
Delayed Perforation Rate
Measured: Within 14 days after procedure
Total Procedure Time
Measured: During the ESD procedure
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Aug 2026
- Study start29 Jul 2026
- Primary completion28 Jul 2027 (estimated)
- Study completion1 Oct 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Esophageal Squamous Cell Carcinoma (ESCC)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Care provider
- Enrolment
- 220 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Qilu Hospital of Shandong University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07757906
- Sponsor's protocol ID
- 2026SDU-QILU-4
- Status last verified
- Jul 2026
- First submitted
- 6 Aug 2026
- Last updated
- 15 Oct 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Application of an AI-based Dissection Trajectory Prediction System (ADTPS) in Endoscopic Submucosal Dissection: A Prospective Paired Diagnostic Study and a Randomized Controlled Clinical Trial
- ClinicalTrials.gov ID
- NCT07757906
- Acronym / sponsor ID
- 2026SDU-QILU-4
- 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
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 220 participants (estimated)
- Lead sponsor
- Qilu Hospital of Shandong UniversityUniversity, hospital or other
- Study start
- 29 Jul 2026 (actual)
- Primary completion
- 28 Jul 2027 (estimated)
- Study completion
- 1 Oct 2027 (estimated)
- First posted
- 11 Aug 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, care provider)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Conventional ESD without AI | Active comparator | Device: Conventional ESD Procedure |
| AI-assisted ESD with ADTPS | Experimental | Device: AI-based Dissection Trajectory Prediction System (ADTPS) |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (14 listed)
- 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.
Key exclusion criteria (7 listed)
- 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.
- RCT
- Patients currently undergoing dialysis.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-based Dissection Trajectory Prediction System (ADTPS)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. | Device | AI-assisted ESD with ADTPS |
| Conventional ESD ProcedureThe 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. | Device | Conventional ESD without AI |
Primary outcome
NASA-TLX Workload Score
Time frame: Immediately after the ESD procedure
Mean Single Dissection Time
Time frame: During the ESD procedure
7 secondary outcomes
R0 Resection Rate
Time frame: At the time of pathological examination
Muscularis Propria Injury Rate
Time frame: During the ESD procedure
Intraoperative Bleeding Episodes
Time frame: During the ESD procedure
Intraoperative Perforation Rate
Time frame: During the ESD procedure
Delayed Bleeding Rate
Time frame: Within 14 days after procedure
Delayed Perforation Rate
Time frame: Within 14 days after procedure
Total Procedure Time
Time frame: During the ESD procedure
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-based Dissection Trajectory Prediction System (ADTPS) and Conventional ESD Procedure in people with Esophageal Squamous Cell Carcinoma (ESCC) and High-Grade Intraepithelial Neoplasia, run by Qilu Hospital of Shandong University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 14 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 15 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
NASA-TLX Workload Score (time frame: Immediately after the ESD procedure). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Oct 2026.