[Multivariate saturation treatment for pancreatic neuroendocrine neoplasms with liver metastasis]

Pancreatic neuroendocrine neoplasms (pNENs) are relatively rare clinical diseases, accounting for about 4%-5% of all primary pancreatic tumors, and 60% of patients had had distant metastases when pNENs were diagnosed, with liver being the most frequently involved metastatic organ. Currently, treatment options for pNENs with liver metastasis include surgery, local embolization and ablation, chemotherapy, targeted therapy represented by everolimus and bevacizumab, somatostatin receptor therapy and immunotherapy. However, how to accurately evaluate the condition of patients at different stages of the disease, choose the above-mentioned treatment methods and optimize the treatment effect is a hot and difficult research topic. As a new tumor treatment concept in the era of intelligent medicine recently proposed by the author, the concept of multivariate saturation treatment used artificial intelligence technology to integrate existing tumor treatment methods, combined with the individual heterogeneity of patients; used the deep learning technology of artificial intelligence to accurately assess disease stages and predict the possible response of the corresponding treatment; used the robotic surgery platform to adopt the most suitable surgical method for the patient, which was dynamically adjusted at different stages of tumor treatment to maximize and optimize the treatment effect. Multivariate saturation treatment can provide the possibility to achieve the optimal prognosis of the patient.