Multi-mode diagnostic strategies for liver cancer

doi:10.3877/cma.j.issn.2095-3232.2026.03.006

Abstract

Abstract:

Liver cancer is one of the main malignant tumors worldwide. Early diagnosis and treatment are of significance for improving the survival rate of patients. In recent years, medical imaging, tumor markers and artificial intelligence (AI) technologies have played a critical role in the diagnosis and management of liver cancer. Imaging technologies, such as ultrasound, CT, MRI and radionuclide imaging, have been widely applied in the screening, diagnosis, grading and treatment evaluation of liver cancer. Tumor markers, such as AFP, AFP-L3 and PIVKA-Ⅱ, are important tools in the diagnosis of liver cancer, which are known as "triple detections of liver cancer". AI technologies, especially deep learning and neural network model, can effectively analyze medical imaging data and assist physicians to make more accurate diagnosis. Integrated application of these technologies is expected to further enhance early diagnosis rate and the overall survival of liver cancer patients.

Key words: Primary liver cancer, Carcinoma,hepatocellular, Imaging examinations, Tumor markers, Artificial intelligence

Yachao Shi, Liumu Wei, Xiaoge Dong, Haining Fan, Lichao Hou, Kaihao Du, Zhanjin Wang, Weiwei Xue, Haigang Liu, Zhan Wang. Multi-mode diagnostic strategies for liver cancer[J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2026, 15(03): 326-336.

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