已发表论文

肝细胞癌切除术后预测临床显著性术后肝衰竭的功能性肝脏影像学评分

 

Authors Zheng X, Zhang Y, Huang H, Luo N

Received 10 December 2024

Accepted for publication 3 July 2025

Published 18 July 2025 Volume 2025:12 Pages 1483—1493

DOI https://doi.org/10.2147/JHC.S511240

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 4

Editor who approved publication: Dr David Gerber

Xihua Zheng,* Yumin Zhang,* Huiying Huang, Ningbin Luo

Departments of Radiology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Ningbin Luo, Departments of Radiology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China, Fax +860734-5312000, Email luoningbin2012@hotmail.com

Purpose: To develop a model based on Functional Liver Imaging Score (FLIS) to estimate the risk of clinically significant post-hepatectomy liver failure (PHLF) for hepatocellular carcinoma (HCC) after resection.
Patients and Methods: This retrospective study analyzed 885 patients with HCC who undergoing liver resection at our medical center between January 2017 and December 2021. Patients were randomly (7:3) assigned to development (n=620) or internal validation (n=265) cohorts. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors for clinically significant PHLF, defined as grade B or C PHLF by the International Study Group of Liver Surgery. Predictive performance was assessed by the area under receiver operator characteristic curves (AUC).
Results: Clinically significant PHLF occurred in 7.7% of the development cohort and 7.2% of the internal validation cohort. Multivariate analysis identified FLIS, major resection and ALBI score as independent predictors of clinically significant PHLF, and a model combining these three variables predicted failure in the development cohort (AUC 0.746, 95% CI 0.673– 0.820) and internal validation cohort (AUC 0.717, 95% CI 0.595– 0.838). The same model also predicted mortality within 90 days after surgery in the development cohort (AUC 0.704, 95% CI 0.575– 0.832) and internal validation cohort (AUC 0.717, 95% CI 0.586– 0.848). In both cohorts, overall survival rate was significantly lower among patients whom the model placed at high risk of clinically significant PHLF than among those at low risk.
Conclusion: The combination of FLIS and other easily acquired clinical data may reliably predict clinically significant PHLF and mortality in hepatocellular carcinoma.
Plain Language Summary: Functional liver imaging score derived from gadoxetic acid-enhanced MRI can effectively and conveniently evaluate liver function. In this study, functional liver imaging score, major resection and ALBI score were significantly associated with clinically significant post-hepatectomy liver failure for hepatocellular carcinoma after resection. A model combining these factors reliably predicted clinically significant post-hepatectomy liver failure and 90-day mortality in our cohort.

Keywords: hepatocellular carcinoma, hepatectomy, post-hepatectomy liver failure, functional liver imaging scores, magnetic resonance imaging, prognosis