Literature DB >> 33120240

Computational quantitative measures of Gd-EOB-DTPA enhanced MRI hepatobiliary phase images can predict microvascular invasion of small HCC.

Xinxin Wang1, Ziqian Zhang1, Xueyan Zhou2, Yuning Zhang1, Jiamin Zhou1, Shuli Tang3, Yang Liu4, Yang Zhou5.   

Abstract

PURPOSE: This study was designed to preoperatively predict microvascular invasion (MVI) of solitary small hepatocellular carcinoma (sHCC) by quantitative analysis of Gd-EOB-DTPA enhanced hepatobiliary phase (HBP) magnetic resonance imaging (MRI).
METHOD: Sixty-one patients, 19 with and 42 without histologically confirmed MVI following hepatic resection for solitary sHCC (≤ 3 cm), were preoperatively examined with Gd-EOB-DTPA-enhanced MRI. The regions of interest (ROIs) of the hepatic lesions were manually delineated on the maximum cross-sectional area in the HBP images and used to calculate the lesion boundary index (LBI) and marginal gray changes (MGC). Histogram analysis was performed to measure standard deviations (STD) and coefficients of variation (CV). Correlations between quantitative parameters and MVI were evaluated and differences between MVI positive and negative groups were assessed.
RESULTS: The average LBI (0.85 ± 0.07) and MGC (0.48 ± 0.27) values of the negative group were significantly higher (p < 0.05) than the corresponding LBI (0.72 ± 0.07) and MGC (0.28 ± 0.18) values of the positive group. STDs and CVs in the negative group were significantly smaller (p < 0.05) than those of the positive group. Receiver operating characteristic (ROC) analysis revealed that LBI had the best predictive value with an AUC, sensitivity, and specificity of 0.91, 87 %, and 80 %, respectively.
CONCLUSIONS: Quantitative analysis of HBP images is useful for predicting MVI and beneficial to clinicians in making decisions before treatment.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Gd-EOB-DTPA; Magnetic resonance imaging; Microvascular invasion; Quantitative analysis; sHCC

Mesh:

Substances:

Year:  2020        PMID: 33120240     DOI: 10.1016/j.ejrad.2020.109361

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  2 in total

1.  Radiomic analysis based on multi-phase magnetic resonance imaging to predict preoperatively microvascular invasion in hepatocellular carcinoma.

Authors:  Yue-Ming Li; Yue-Min Zhu; Lan-Mei Gao; Ze-Wen Han; Xiao-Jie Chen; Chuan Yan; Rong-Ping Ye; Dai-Rong Cao
Journal:  World J Gastroenterol       Date:  2022-06-28       Impact factor: 5.374

2.  Preoperative Assessment of Abdominal Adipose Tissue to Predict Microvascular Invasion in Small Hepatocellular Carcinoma.

Authors:  Zongqian Wu; Hong Lu; Qiao Xie; Jie Cheng; Kuansheng Ma; Xiaofei Hu; Liang Tan; Huarong Zhang; Chen Liu; Xiaoming Li; Ping Cai
Journal:  J Clin Transl Hepatol       Date:  2021-07-07
  2 in total

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