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Research process in imaging prediction of post-hepatectomy liver failure
ZHANG Xiaoye  HE Yexin 

Cite this article as: ZHANG X Y, HE Y X. Research process in imaging prediction of post-hepatectomy liver failure[J]. Chin J Magn Reson Imaging, 2024, 15(11): 216-220. DOI:10.12015/issn.1674-8034.2024.11.034.


[Abstract] Hepatic resection is a preferred treatment for patients with primary and metastatic liver tumors. Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure remains the most serious cause of morbidity and mortality after surgery. This article reviews research advances in imaging to predict liver failure after hepatectomy, analyzing it from morphological, functional imaging, and artifactual intelligence perspectives, aiming to improve the understanding of PHLF and seeking to reduce its incidence.
[Keywords] hepatectomy;liver failure;imaging;artificial intelligence

ZHANG Xiaoye1   HE Yexin2  

1 Department of Medical Imaging, Shanxi Medical University, Taiyuan030012, China

2 The Radiology Department, Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan030012, China

Corresponding author: HE Y X, E-mail: heyexinty2000@sina.com

Conflicts of interest   None.

Received  2024-08-07
Accepted  2024-11-08
DOI: 10.12015/issn.1674-8034.2024.11.034
Cite this article as: ZHANG X Y, HE Y X. Research process in imaging prediction of post-hepatectomy liver failure[J]. Chin J Magn Reson Imaging, 2024, 15(11): 216-220. DOI:10.12015/issn.1674-8034.2024.11.034.

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