Journal of Hepatocellular Carcinoma (Jul 2024)
Research Progress in Predicting Hepatocellular Carcinoma with Portal Vein Tumour Thrombus in the Era of Artificial Intelligence
Abstract
Yaduo Li,1,* Ningning Fan,1,* Xu He,2,* Jianjun Zhu,3,* Jie Zhang,1 Ligong Lu1,2 1Medical Imaging Department, Zhuhai Clinical Medical College of Jinan University (Zhuhai People’s Hospital), Zhuhai, People’s Republic of China; 2Department of Interventional Medicine, Guangzhou First People’s Hospital, Guangzhou, People’s Republic of China; 3R&D Department, Hanglok-Tech Co., Ltd., Hengqin, People’s Republic of China; Center of Interventional Radiology & Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ligong Lu, Zhuhai Clinical Medical College of Jinan University (Zhuhai People’s Hospital), Zhuhai, Guangdong, 519000, People’s Republic of China & Guangzhou First People’s Hospital, Guangzhou, Guangdong, 510180, People’s Republic of China, Tel +020-81048888, Email [email protected] Jie Zhang, Zhuhai Clinical Medical College of Jinan University (Zhuhai People’s Hospital), Zhuhai, Guangdong, 519000, People’s Republic of China, Tel +86-756-15916221984, Email [email protected]: Hepatocellular Carcinoma (HCC) is a condition associated with significant morbidity and mortality. The presence of Portal Vein Tumour Thrombus (PVTT) typically signifies advanced disease stages and poor prognosis. Artificial intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), has emerged as a promising tool for extracting quantitative data from medical images. AI is increasingly integrated into the imaging omics workflow and has become integral to various medical disciplines. This paper provides a comprehensive review of the mechanisms underlying the formation and progression of PVTT, as well as its impact on clinical management and prognosis. Additionally, it outlines the advancements in AI for predicting the diagnosis of HCC and the development of PVTT. The limitations of existing studies are critically evaluated, and potential future research directions in the realm of imaging for the diagnostic prediction of HCC and PVTT are discussed, with the ultimate goal of enhancing survival outcomes for PVTT patients.Keywords: hepatocellular carcinoma, portal vein tumour thrombus, imaging omics, prediction, artificial intelligence
