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

NCT07251114 — Not applicable, Recruiting, 200 participants, Fujian Provincial Hospital

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RegistryNCT07251114
StatusRecruiting
PhaseNot applicable
Study typeInterventional; randomized, parallel, masking: single, diagnostic
Enrollment200 (Estimated)
SponsorFujian Provincial Hospital (Other)
ConditionsEsophageal Cancer Stage, Early Esophageal Cancer
InterventionsArtificial Intelligence system (Device)
Datesstart 2025-11-20 (estimated), primary completion 2027-10-31 (estimated), completion 2028-12-31 (estimated), first posted 2025-11-26, last updated 2025-11-26
Locations5 sites in China

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-Summary

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

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

+Arms and interventions

ArmTypeInterventionsDescription
AI GroupExperimentalDevice: Artificial Intelligence systemUse artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound
Control groupNo interventionRoutine diagnosis
  • Artificial Intelligence system (Device), also known as Artificial Intelligence: Use artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound

+Outcome measures

Primary outcomes

  • The accuracy of grading judgment of infiltration depth [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

  • survival rate [Three years]: 3-year survival rate
  • Progression Free-Survival [1 year]: The period from the start of treatment to tumor progression or death for any reason

+Eligibility

Sex: All, ages: 18 Years to any

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.

+Locations (5)

FacilityCityCountryStatus
Fujian provincial hospitalFuzhou, FujianChinaRecruiting
Affiliated Hospital of Putian UniversityPutian, FujianChinaNot yet recruiting
Putian First HospitalPutian, FujianChinaNot yet recruiting
Putian Hospital of Traditional Chinese MedicinePutian, FujianChinaNot yet recruiting
Xianyou County General HospitalPutian, FujianChinaNot yet recruiting

+Investigators

  • Wei Liang, MD, Principal investigator, Fujian Provincial Hospital