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.
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;
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.
Parallel
Artificial Intelligence system
DeviceUse artificial intelligence to assist in the determination of the invasion depth of early esophageal squamous cell carcinoma under endoscopic ultrasound
The accuracy of grading judgment of infiltration depth
By comparing with the postoperative pathology, the accuracy of the preoperative T grading with the assistance of the artificial intelligence grading system was verified
survival rate
3-year survival rate
Progression Free-Survival
The period from the start of treatment to tumor progression or death for any reason
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