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Review
. 2024 Jul 17:11:1429-1438.
doi: 10.2147/JHC.S474922. eCollection 2024.

Research Progress in Predicting Hepatocellular Carcinoma with Portal Vein Tumour Thrombus in the Era of Artificial Intelligence

Yaduo Li #  1 , Ningning Fan #  1 , Xu He #  2 , Jianjun Zhu #  3 , Jie Zhang  1 , Ligong Lu  1   2
Affiliations
Review

Research Progress in Predicting Hepatocellular Carcinoma with Portal Vein Tumour Thrombus in the Era of Artificial Intelligence

Yaduo Li et al. J Hepatocell Carcinoma. .

Abstract

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: artificial intelligence; hepatocellular carcinoma; imaging omics; portal vein tumour thrombus; prediction.

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Conflict of interest statement

Yaduo Li, Ningning Fan, Xu He and Jianjun Zhu are co-first authors for this study. The authors report no conflicts of interest in this work.

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Grants and funding

This work was supported by National Natural Science Foundation of China (82372064), Opening foundation of Hubei key laboratory of molecular imaging (2022fzyx014),The Clinical Research Promotion Project of Zhuhai People’s Hospital (2023LCTS-10) and the Science and Technology Program of Zhuhai (2220004000110).

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