Early Esophageal Cancer

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.

With the development of endoscopy, more and more patients with superficial esophageal squamous cell carcinoma (ESCC) receive endoscopic resection rather than traditional surgery. However, there is still no complete consensus on the risk factors for lymph node metastasis (LNM) and recurrence of ESCC after endoscopic resection. The existing curative resection criteria are strict to a certain extent, and a considerable number of patients are overtreated according to the current standard of additional treatment. Thus, we aim to conduct a multi-center retrospective and prospective study to construct a large cohort of ESCC based on the previously established multi-center collaborative research network and clinical big data, analyze the risk factors of LNM and recurrence in patients with early esophageal squamous cell carcinoma after ESD, establish an accurate and simple risk prediction model, and evaluate the discrimination efficiency of this model.