Artificial intelligence for enhancing decision-making in multidisciplinary tumor boards for HCC in China

Abstract

Hepatocellular carcinoma (HCC) exhibits high incidence and mortality rates in China, posing a significant public health burden. Established risk factors, including hepatitis B virus, hepatitis C virus, aflatoxin B1 exposure, alcohol consumption, and smoking, shape the unique epidemiological profile of HCC in China and exacerbate its marked tumor heterogeneity. This complexity leads to highly intricate prognostic assessment, management strategies, and predictive approaches across diverse patient populations. The updated “Guidelines for Diagnosis and Treatment of Primary Liver Cancer (2024 Edition)” reflect significant advancements in screening, diagnosis, staging, treatment, and follow-up, with particular emphasis on management strategies tailored to the Chinese context. The multidisciplinary tumor board (MDTB) serves as a cornerstone of modern oncology care. By integrating expertise from diverse medical specialties, the MDTB is crucial for developing individualized treatment plans for complex HCC cases. However, current MDTB practice faces significant challenges, primarily stemming from the rapid evolution of treatment options and the swift advancement of emerging technologies, particularly artificial intelligence (AI). This necessitates continuous learning among MDTB members to effectively integrate cutting-edge therapies and tools. This review focuses on the disease characteristics of HCC in China and the unmet needs within its clinical management. It delves into how AI technologies can enhance the capabilities of MDTBs, aiming to elucidate the transformative potential and persisting challenges of AI-driven multidisciplinary care models for HCC in China.