Predicting post-hepatectomy liver failure with T1 mapping-based whole-liver histogram analysis on gadoxetic acid-enhanced MRI: comparison with the indocyanine green clearance test and albumin-bilirubin scoring system

被引:0
|
作者
Li, Jun [1 ]
Li, Yi [1 ]
Chen, Yuan-Yuan [1 ]
Wang, Xiao-Ying [2 ]
Fu, Cai-Xia [3 ]
Grimm, Robert [4 ]
Ding, Ying [1 ]
Zeng, Meng-Su [1 ]
机构
[1] Fudan Univ, Zhongshan Hosp, Dept Radiol, Shanghai, Peoples R China
[2] Fudan Univ, Zhongshan Hosp, Dept Liver Oncol, Shanghai, Peoples R China
[3] Siemens Shenzhen Magnet Resonance Ltd, Shenzhen, Peoples R China
[4] Siemens Healthineers AG, MR Applicat Predev, Erlangen, Germany
基金
美国国家科学基金会;
关键词
Liver failure; Gadolinium ethoxybenzyl DTPA; Magnetic resonance imaging; Indocyanine green; Risk assessment; HUMAN SERUM-ALBUMIN; CONTRAST AGENT; HEPATOCELLULAR-CARCINOMA; DTPA; FIBROSIS;
D O I
10.1007/s00330-024-11238-w
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objectives To explore the value of T1 mapping-based whole-liver histogram analysis on gadoxetic acid-enhanced MRI for predicting post-hepatectomy liver failure (PHLF). Methods Consecutive patients from March 2016 to March 2018 who underwent gadoxetic acid-enhanced MRI in our hospital were retrospectively analyzed, and 37 patients were enrolled. Whole-liver T1 mapping-based histogram analysis was performed. The indocyanine green (ICG) clearance tests were performed, and albumin-bilirubin (ALBI) scores were calculated. Univariate and multivariate binary logistic analyses were performed to identify independent predictors for PHLF. Diagnostic performance was evaluated with ROC analysis. Histogram-extracted parameters were also associated with the ICG test and ALBI scoring system. Results In enrolled 37 patients (age 57.19 +/- 12.28 years), 28 were male. 35.1% (13/37) of patients developed PHLF. For univariate analysis, pre-contrast T1 relaxation time (T1pre) mean, T1pre 95th percentile, the standard deviation (SD) of T1 relaxation time in hepatobiliary phase (T1HBP SD), T1HBP 95th percentile, T1HBP kurtosis, and ICG percentage retained at 15 min (ICG-R15) showed significant differences between the PHLF and non-PHLF groups (all p < 0.05), whereas the ALBI scores showed no significant differences between the two groups (p = 0.937). Multivariate analysis showed that a higher T1HBP 95th percentile was the independent predictor for PHLF (p < 0.05; odds ratio (OR) = 1.014). In addition, most of the histogram-extracted parameters showed significant correlations to the ICG test. Conclusions T1 mapping-based whole-liver histogram analysis on gadoxetic acid-enhanced MRI is valuable for PHLF prediction and risk stratification, which outperformed the ICG clearance test and ALBI scoring system.
引用
收藏
页数:12
相关论文
共 4 条
  • [1] Predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma: nomograms based on deep learning analysis of gadoxetic acid-enhanced MRI
    Jeong, Boryeong
    Heo, Subin
    Lee, Seung Soo
    Kim, Seon-Ok
    Shin, Yong Moon
    Kim, Kang Mo
    Ha, Tae-Yong
    Jung, Dong-Hwan
    EUROPEAN RADIOLOGY, 2024, : 2769 - 2782
  • [2] A radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma
    Li, Changfeng
    Wang, Qiang
    Zou, Mengda
    Cai, Ping
    Li, Xuesong
    Feng, Kai
    Zhang, Leida
    Sparrelid, Ernesto
    Brismar, Torkel B.
    Ma, Kuansheng
    FRONTIERS IN ONCOLOGY, 2023, 13
  • [3] Predicting post-hepatectomy liver failure in patient with hepatocellular carcinoma: nomograms based on deep learning-analyzed gadoxetic acid-enhanced hepatobiliary phase images
    Jeong, Boryeong
    Lee, Seung Soo
    Heo, Subin
    Kim, Seon-Ok
    JOURNAL OF HEPATOLOGY, 2024, 80 : S437 - S437
  • [4] Quantitative analysis of gadoxetic acid-enhanced MRI for the differential diagnosis of focal liver lesions: Comparison between estimated intralesional gadoxetic acid retention by T1 mapping and conventional processing methods
    Morisaka, Hiroyuki
    Seno, Daiki
    Sakurai, Yasuo
    Sano, Katsuhiro
    Akamine, Yuta
    Ichikawa, Tomoaki
    Okada, Yoshitaka
    EUROPEAN JOURNAL OF RADIOLOGY, 2021, 138