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AI-assisted Endoscopic Ultrasound Grading of Early Esophageal Cancer Invasion Depth: A Multicenter, Prospective, Randomized Cohort Study

NCT ID: NCT07251114

Last Updated: 2025-11-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

200 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-11-20

Study Completion Date

2028-12-31

Brief Summary

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This study mainly uses an artificial intelligence system to assist in the classification of the depth of invasion of early esophageal squamous cell carcinoma under ultrasound endoscopy, providing a basis for preoperative T staging and diagnosis and treatment decisions.

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Detailed Description

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For patients with early esophageal squamous cell carcinoma and precancerous lesions who met the inclusion and exclusion criteria and voluntarily participated in this project, they were randomly divided into the AI group and the conventional group by central randomization, with 100 cases in each group（anticipated）. Randomization method: The personnel responsible for randomization at the center (who do not participate in the inclusion of subjects) log in to the central randomization system to obtain a randomization number, and finally form a randomization allocation table. Blinding implementation: The observation group and control group determined on the random allocation table were marked as A and B respectively, and then the operating physician implemented protocol A or B. Main indicators: Grading judgment of infiltration depth, pathological consistency

Conditions

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Esophageal Cancer Stage Early Esophageal Cancer

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Use artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

SINGLE

Participants

Study Groups

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AI Group

Use artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound

Group Type EXPERIMENTAL

Artificial Intelligence system

Intervention Type DEVICE

Use artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound

Control group

Routine diagnosis

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Artificial Intelligence system

Use artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound

Intervention Type DEVICE

Other Intervention Names

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Artificial Intelligence

Eligibility Criteria

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Inclusion Criteria

* Satisfy ①⑧⑨ and one of the following conditions simultaneously: ②③④⑤⑥⑦ ① Age over 18 years old, ② Esophageal ulcer, ③ low-grade intraepithelial neoplasia, ④ high-grade intraepithelial neoplasia, ⑤ patients with esophageal squamous cell carcinoma, ⑥ white patches of esophageal mucosa, ⑦ esophageal polyps, ⑧ with endoscopic examination records and detailed pathological records, ⑨ agree to participate in the study;

Exclusion Criteria

* ① Patients who have undergone esophageal cancer surgery, ② those with a history of radiotherapy and chemotherapy for esophageal cancer, ③ patients with missing data.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Fujian Provincial Hospital

OTHER

Sponsor Role lead

Responsible Party

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Wei Liang

Digestive Endoscopy Center

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Wei Liang, MD

Role: PRINCIPAL_INVESTIGATOR

Fujian Provincial Hospital

Locations

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Fujian provincial hospital

Fuzhou, Fujian, China

Site Status RECRUITING

Affiliated Hospital of Putian University

Putian, Fujian, China

Site Status NOT_YET_RECRUITING

Putian First Hospital

Putian, Fujian, China

Site Status NOT_YET_RECRUITING

Putian Hospital of Traditional Chinese Medicine

Putian, Fujian, China

Site Status NOT_YET_RECRUITING

Xianyou County General Hospital

Putian, Fujian, China

Site Status NOT_YET_RECRUITING

Countries

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China

Central Contacts

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Wei Liang, MD

Role: CONTACT

[email protected]
+86 -18120888996

Yanqin Xu, MD

Role: CONTACT

[email protected]
+86-13599382136

Facility Contacts

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Wei Liang, MD

Role: primary

[email protected]
+86-18120888996

Yanqin Xu, MD

Role: backup

[email protected]
+86-13599382138

Huifeng Wu, MD

Role: primary

[email protected]
+86-13706067949

Junwei Xie, MD

Role: primary

[email protected]
+86-15105949153

Fangfang Pan, MD

Role: primary

[email protected]
86-15105938179

Huijing Wu, MD

Role: primary

[email protected]
+86-15205032044

Other Identifiers

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K2025-02-067

Identifier Type: -

Identifier Source: org_study_id

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