Microvascular invasion-negative hepatocellular carcinoma: Prognostic value of qualitative and quantitative Gd-EOB-DTPA MRI analysis.


Journal

European journal of radiology
ISSN: 1872-7727
Titre abrégé: Eur J Radiol
Pays: Ireland
ID NLM: 8106411

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 16 08 2023
revised: 27 09 2023
accepted: 06 10 2023
medline: 30 10 2023
pubmed: 14 10 2023
entrez: 13 10 2023
Statut: ppublish

Résumé

The purpose of this study was to establish a model for predicting the prognosis of patients with microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) based on qualitative and quantitative analyses of Gd-EOB-DTPA magnetic resonance imaging (MRI). Consecutive patients with MVI-negative HCC who underwent preoperative Gd-EOB-DTPA MRI between January 2015 and December 2019 were retrospectively enrolled.In total, 122 patients were randomly assigned to the training and validation groups at a ratio of 7:3. Univariate and multivariate logistic regression analyses were performed to identify significant clinical parameters and MRI features, including quantitative and qualitative parameters associated with prognosis, which were incorporated into a predictive nomogram. The end-point of this study was recurrence-free survival. Outcomes were compared between groups using the Kaplan-Meier method with the log-rank test. During a median follow-up period of 58.86 months, 38 patients (31.15 %) experienced recurrence. Multivariate analysis revealed that lower relative enhancement ratio (RER), hepatobiliary phase hypointensity without arterial phase hyperenhancement, Liver Imaging Reporting and Data System category, mild-moderate T2 hyperintensity, and higher aspartate aminotransferase levels were risk factors associated with prognosis and then incorporated into the prognostic model. C-indices for training and validation groups were 0.732 and 0.692, respectively. The most appropriate cut-off value for RER was 1.197. Patients with RER ≤ 1.197 had significantly higher postoperative recurrence rates than those with RER > 1.197 (p = 0.004). The model integrating qualitative and quantitative imaging parameters and clinical parameters satisfactorily predicted the prognosis of patients with MVI-negative HCC.

Identifiants

pubmed: 37832198
pii: S0720-048X(23)00460-6
doi: 10.1016/j.ejrad.2023.111146
pii:
doi:

Substances chimiques

gadolinium ethoxybenzyl DTPA 0
Contrast Media 0
Gadolinium DTPA K2I13DR72L

Types de publication

Randomized Controlled Trial Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

111146

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Leyao Wang (L)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

Meng Liang (M)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

Bing Feng (B)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

Dengfeng Li (D)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

Rong Cong (R)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

Zhaowei Chen (Z)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.

Sicong Wang (S)

Sicong Wang, Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing 100176, China.

Xiaohong Ma (X)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China. Electronic address: maxiaohong@cicams.ac.cn.

Xinming Zhao (X)

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China. Electronic address: zhaoxinming@cicams.ac.cn.

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Classifications MeSH