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NCT Number: NCT07251114

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

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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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Fujian provincial hospital, Fuzhou, Fujian, China

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About this study

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

Who can participate

Healthy volunteers accepted: No

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

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.

Treatment and study plan

artificial intelligence system

Device

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

Other names: Artificial Intelligence

Primary outcomes

  1. The accuracy of grading judgment of infiltration depth

    Time frame: 2 years

    By comparing with the postoperative pathology, the accuracy of the preoperative T grading with the assistance of the artificial intelligence grading system was verified

Secondary outcomes

  1. survival rate

    Time frame: Three years

    3-year survival rate

  2. Progression Free-Survival

    Time frame: 1 year

    The period from the start of treatment to tumor progression or death for any reason

Study contacts

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

Wei Liang, MD

CONTACT

[email protected]

+86 -18120888996

Yanqin Xu, MD

CONTACT

[email protected]

+86-13599382136

Sponsors and collaborators

Lead sponsor

Fujian Provincial Hospital

Other

Registry information

Important dates

Study start
2025
Primary completion
2027
Study completion
2028
First posted
Nov 26, 2025
Registry last updated
Nov 26, 2025

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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