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Review
. 2021 Nov 15;13(11):1599-1615.
doi: 10.4251/wjgo.v13.i11.1599.

Radiomics in hepatocellular carcinoma: A state-of-the-art review

Shan Yao  1 , Zheng Ye  1 , Yi Wei  1 , Han-Yu Jiang  1 , Bin Song  2
Affiliations
Review

Radiomics in hepatocellular carcinoma: A state-of-the-art review

Shan Yao et al. World J Gastrointest Oncol. .

Abstract

Hepatocellular carcinoma (HCC) is the most common cancer and the second major contributor to cancer-related mortality. Radiomics, a burgeoning technology that can provide invisible high-dimensional quantitative and mineable data derived from routine-acquired images, has enormous potential for HCC management from diagnosis to prognosis as well as providing contributions to the rapidly developing deep learning methodology. This article aims to review the radiomics approach and its current state-of-the-art clinical application scenario in HCC. The limitations, challenges, and thoughts on future directions are also summarized.

Keywords: Artificial intelligence; Deep learning; Hepatocellular carcinoma; Medical imaging; Predictive modeling; Radiomics.

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Conflict of interest statement

Conflict-of-interest statement: All authors declare no potential conflict of interests related to this publication.

Figures

Figure 1
Figure 1
General workflow of radiomics and deep learning in hepatocellular carcinoma.
Figure 2
Figure 2
Summary of the clinical application scenario, limitations, challenges, and further work of state-of-the-art radiomics and deep learning in hepatocellular carcinoma.
See this image and copyright information in PMC

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References

    1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69:7–34. - PubMed
    1. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66:115–132. - PubMed
    1. Villanueva A. Hepatocellular Carcinoma. N Engl J Med. 2019;380:1450–1462. - PubMed
    1. Yang JD, Heimbach JK. New advances in the diagnosis and management of hepatocellular carcinoma. BMJ. 2020;371:m3544. - PubMed
    1. Roberts LR, Sirlin CB, Zaiem F, Almasri J, Prokop LJ, Heimbach JK, Murad MH, Mohammed K. Imaging for the diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis. Hepatology. 2018;67:401–421. - PubMed
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