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Advances in artificial intelligence-based research on microvascular invasion in primary hepatocellular carcinoma
LIU Yang  JIANG Yanli  FAN Fengxian  YANG Wenxia  LI Darui  LIU Guangyao  ZHANG Jing 

LIU Y, JIANG Y L, FAN F X, et al. Advances in artificial intelligence-based research on microvascular invasion in primary hepatocellular carcinoma[J]. Chin J Magn Reson Imaging, 2023, 14(9): 159-164. DOI:10.12015/issn.1674-8034.2023.09.029.


[Abstract] Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system with a high degree of malignancy and poor prognosis. Microvascular invasion (MVI) usually refers to a cluster of cancer cells in the vascular cavity covered by endocrine cells under the microscope. Currently, MVI is generally considered to correlate closely with the recurrence and metastasis of HCC. Therefore, it is essential to predict MVI accurately before surgery. However, there is still no accepted and effective method to accurately predict MVI. With the rise and development of artificial intelligence, radiomics and deep learning are increasingly used to develop individualized predictive models. Radiomics and deep learning technologies can enable deep mining of imaging information to provide more objective and comprehensive information, which can be combined with clinical information to build comprehensive models. These models can accurately assess of HCC MVI risk and help doctors develop individualized treatment strategies. This paper aims to make a comprehensive analysis of relevant studies on MVI assessment by radiomics techniques at home and abroad to enhance the understanding and attention of radiologists and clinicians on MVI and to provide helpful guidance for the accurate assessment and treatment planning of clinical MVI, as well as the prognosis judgment of HCC patients, to improve the diagnosis and treatment results of HCC patients, increase the survival rate, and provide a basis for the realization of the big data medical environment guided by this will provide a basis for individualized and precise treatment under the guidance of big data medical environment.
[Keywords] hepatocellular carcinoma；microvascular invasion；radiomics；preoperative prediction；deep learning

LIU Yang1, 2   JIANG Yanli1, 3   FAN Fengxian1, 3   YANG Wenxia1, 2   LI Darui1, 2   LIU Guangyao1   ZHANG Jing1, 2, 3*  

1 Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China

2 Second Clinical School, Lanzhou University, Lanzhou 730030, China

3 Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China

Corresponding author: Zhang J, E-mail: ery_zhangjing@lzu.edu.cn

Conflicts of interest   None.

ACKNOWLEDGMENTS Science and Technology Plan Project of Gansu Province (No. 21JR11RA122, 21JR7RA438).
Received  2023-04-09
Accepted  2023-07-21
DOI: 10.12015/issn.1674-8034.2023.09.029
LIU Y, JIANG Y L, FAN F X, et al. Advances in artificial intelligence-based research on microvascular invasion in primary hepatocellular carcinoma[J]. Chin J Magn Reson Imaging, 2023, 14(9): 159-164. DOI:10.12015/issn.1674-8034.2023.09.029.

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