AI-assisted Endoscopic Ultrasound Grading of Early Esophageal Cancer Invasion Depth: A Multicenter, Prospective, Randomized Cohort Study
Status: Recruiting
Location: See all (5) locations...
Intervention Type: Device
Study Type: Interventional
Study Phase: Not Applicable
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.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Healthy Volunteers: f
View:
• 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;
Locations
Other Locations
China
Fujian provincial hospital
RECRUITING
Fuzhou
Affiliated Hospital of Putian University
NOT_YET_RECRUITING
Putian
Putian First Hospital
NOT_YET_RECRUITING
Putian
Putian Hospital of Traditional Chinese Medicine
NOT_YET_RECRUITING
Putian
Xianyou County General Hospital
NOT_YET_RECRUITING
Putian
Contact Information
Primary
Wei Liang, MD
fjsllw@163.com
+86 -18120888996
Backup
Yanqin Xu, MD
454202013@QQ.COM
+86-13599382136
Time Frame
Start Date: 2025-11-20
Estimated Completion Date: 2028-12-31
Participants
Target number of participants: 200
Treatments
Experimental: AI Group
Use artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound
No_intervention: Control group
Routine diagnosis
Related Therapeutic Areas
Sponsors
Leads: Fujian Provincial Hospital