Opportunities and challenges of liver cancer imaging: Achievements and prospects over the past decade in China

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CHEN Yidi JIANG Hanyu CHEN Jie QU Yali YE Zheng WEI Yi WEI Hong SHENG Liuji SONG Bin

Cite this article as: Chen YD, Jiang HY, Chen J, et al. Opportunities and challenges of liver cancer imaging: Achievements and prospects over the past decade in China[J]. Chin J Magn Reson Imaging, 2022, 13(10): 71-78. DOI:10.12015/issn.1674-8034.2022.10.010.

Abstract

[Abstract] Primary liver cancer is a prevalent and lethal malignancy in China, constituting a major public health problem. Noninvasive imaging techniques play an important role throughout the entire clinical workflow of liver cancer. Remarkable achievements have been made by Chinese scholars in liver cancer imaging research over the past decade. The rapid advancements in artificial intelligence (AI), ultra-high magnetic field and hyperpolarized MRI, spectral CT provide reliable technical support for screening, diagnosis, and treatment decision-making of liver cancer patients. Furthermore, the fusion of multi-omics techniques (radiomics, genomics, and proteomics) further reveals the correlations between key clinical, radiological, pathological, and molecular alterations in liver cancer. This paper summarizes major achievements by Chinese scholars in liver cancer imaging over the last ten years, primarily focusing on MRI-based Liver Imaging Reporting and Data System (LI-RADS) modification, hepatobiliary contrast agent application, advancements in diffusion-MRI, functional MRI and CT technologies, and radiomics and AI. We also reflect on limitations of existing works in this field.In the future, it is necessary to carry out targeted research design according to the characteristics of domestic patients and population features, establish multi-center study cohort covering a wide range of populations and strong representation, and build homogeneous and high-quality national imagedatabaseof liver cancer. Furthermore, we should pay attention to the development and application of new imaging technology, scholars can use AI combined with radiomics, genomics and proteomics to in-depth study the pathological characteristics, gene phenotype and prognosis of liver cancer, deeply participate in the whole process of clinical management of liver cancer patients, provide technical support for precision medicine, and help achieve the strategic goal of national health.

[Keywords] primary liver cancer；hepatocellular carcinoma；genetic characteristics；immunophenotype；molecular subtype；efficacy；prognosis；medical imaging；medical imaging technology；magnetic resonance imaging；computed tomography；radiomics；artificial intelligence；deep learning；precision medicine；review

Contributor Information

CHEN Yidi¹ JIANG Hanyu¹ CHEN Jie¹ QU Yali¹ YE Zheng¹ WEI Yi¹ WEI Hong¹ SHENG Liuji¹ SONG Bin^{1,
2*}

¹ Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China

² Department of Radiology, Sanya People's Hospital, Sanya 572022, China

Song B, E-mail: cjr.songbin@vip.163.com

Conflicts of interest None.

Publication Information

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 82101997, 81971571); Science and Technology Plan Project of Sichuan Province (No. 2022YFS0071, 2021YFS0021, 2021YFS0141); 1·3·5 Project for Disciplines of Excellence, West China Hospital, Sichuan University (No. ZYGD22004).

Received 2022-09-09

Accepted 2022-10-14

DOI: 10.12015/issn.1674-8034.2022.10.010

Text

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