Artificial Intelligence to Optimize Early-stage Hepatocellular CarcinomaTreatment Based on Multi-modal Image
This study intends to establish two prognostic models based on contrast-enhanced ultrasound (CEUS) and dynamic enhanced magnetic resonance (DE-MRI) multimodal images: prognostic model of liver cancer patients after hepatectomy and prognostic model of liver cancer patients after radiofrequency ablation. Combined with artificial intelligence imaging omics, traditional imaging omics and clinical information, to predict and compare the prognosis of two different treatment methods for early liver cancer, so as to realize the individual selection of treatment methods for early liver cancer patients
• Primary single hepatocellular carcinoma confirmed by histology or cytology, with a maximum diameter ≤5.0 cm;
⁃ Good liver function, Child-Pugh grade A;
‣ No serious dysfunction of heart, lung, kidney and other important organs ④ Liver resection or radiofrequency ablation was performed in our hospital, and the study protocol and follow-up procedure were followed.