Chinese Medical Sciences Journal ›› 2019, Vol. 34 ›› Issue (1): 24-32.doi: 10.24920/003562

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  1. 1 中国医学科学院 北京协和医学院 北京协和医院 放射科 北京 100730
    2 中国医学科学院 北京协和医学院 北京协和医院 病理科,北京 100730
  • 收稿日期:2019-01-21 修回日期:2019-03-11 出版日期:2019-03-30 发布日期:2019-04-08
  • 通讯作者: 王萱,金征宇;

Value of Texture Analysis on Gadoxetic Acid-enhanced MR for Detecting Liver Fibrosis in a Rat Model

Xu Jia1,Wang Xuan1,*(),Jin Zhengyu1,*(),You Yan2,Wang Qin1,Wang Shitian1,Xue Huadan1   

  1. 1 Department of Radiology,Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China
    2 Department of Pathology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China
  • Received:2019-01-21 Revised:2019-03-11 Published:2019-03-30 Online:2019-04-08
  • Contact: Wang Xuan,Jin Zhengyu;


目的 对钆塞酸二钠增强磁共振T1 mapping成像以及T1加权成像(T1W)、T2加权成像(T2W)、表观扩散系数(ADC)图像进行纹理分析,探讨其在大鼠模型中定量评价肝纤维化的价值。

方法 采用四氯化碳腹腔注射法构建大鼠肝纤维化模型,打药时长4~12周(n=30),在对照组中(n=10)注射等量生理盐水。磁共振扫描序列包括T2W,弥散加权成像,注射对比剂前后的T1W和T1 mapping系列图像。利用METAVIR分级将肝纤维化分为正常(F0),轻度肝纤维化(F1~2)和重度肝纤维化(F3~4)。纹理特征参数包括平均灰度强度,标准差,熵,正象素均值、偏斜和峰度。采用非参数Mann-Whitney U检验比较各个序列的上述各项纹理参数在F0与F ≥ 1间、以及F0~2与F3~4间的差异。利用受试者工作特征曲线(ROC)分析纹理参数在区分正常肝组织和肝纤维化、F0~2和F3~4的诊断准确性,并获得ROC曲线下面积(AUC)以评价纹理参数的诊断价值。

结果 20只大鼠完成磁共振T1 mapping扫描,其病理结果为正常(F0,n=6),轻度肝纤维化(F1~2,n=5) 和重度肝纤维化(F3~4,n=9)。在打药前T1 mapping图像中,在各个空间尺度因子(spatial scaling factor,SSF)下,F≥1组的熵值均显著大于F0组(P= 0.015,0.015,0.015,0.013,0.015,0.018,分别对应于SSF = 0,2,3,4,5,6);在SSF 4,5,6下,F≥1组的平均灰度强度显著高于F0组(P= 0.004,0.006,0.013)。在区分正常和肝纤维化组时,打药前T1 mapping图像的熵和平均灰度强度在大多数SSF下,展现出中等诊断价值。

结论 部分钆塞酸二钠增强磁共振图像的纹理参数,特别是打药前T1 mapping图像的熵,对于肝纤维化的诊断具有一定价值。

关键词: 肝纤维化, 磁共振成像, 纹理分析, 熵, T1 mapping


Objective To explore the ability of texture analysis of gadoxetic acid-enhanced magnetic resonance imaging (MRI) T1 mapping images, as well as T1-weighted (T1W), T2-weighted (T2W) and apparent diffusion coefficient (ADC) maps for distinguishing between varying degrees of hepatic fibrosis in an experimental rat model.

Methods Liver fibrosis in rats was induced by carbon tetrachloride intraperitoneal injection for 4-12 weeks (n=30). In the control group (n=10) normal saline was applied. The MRI protocol contained T2W, diffusion weighted imaging, pre-and post-contrast image series of T1W and T1 mapping images. METAVIR score was used to grade liver fibrosis as normal (F0), mild fibrosis (F1-2), and advanced fibrosis (F3-4). Texture parameters including mean gray-level intensity (Mean), standard deviation (SD), Entropy, mean of positive pixels (MPP), Skewness, and Kurtosis were obtained. Nonparametric Mann-Whitney U test was used to compare the average value of each texture parameter in each sequence for assessing the difference between F0 and F≥1 as well as F0-2 and F3-4. Receiver operating characteristic (ROC) curves were obtained to assess the diagnosing accuracy of the parameters for differentiating no liver fibrosis from liver fibrosis and rats with liver fibrosis grading F0-2 from those with grading F3-4. The area under ROC curve (AUC) was calculated to evaluate the diagnostic efficiency of texture parameters.

Results Finally, 20 rats completed MR T1 mapping image scan. The pathologic staging of these 20 rats was no fibrosis (F0, n=6), mild fibrosis (F1-2, n=5) and advanced fibrosis (F3-4, n=9). On pre-contrast T1 mapping image, Entropy was seen to be statistically significant higher in the F≥1 group than that in the F0 group at each spatial scaling factor (SSF) setting (P=0.015, 0.015, 0.015, 0.013, 0.015 and 0.018 respectively to SSF=0, 2, 3, 4, 5, 6), and Mean of the F≥1 rats was statistically significant higher than that of the F0 rats at SSF 4, 5, 6 (P=0.004, 0.006, and 0.013, respectively). Entropy and Mean showed a moderate diagnostic performance in most SSF settings of T1 mapping pre-contrast images for differentiation of normal liver from liver fibrosis.

Conclusion Certain texture features of gadoxetic acid-enhanced MR images, especially the Entropy of non-contrast T1 mapping image, was found to be a useful biomarker for the diagnosis of liver fibrosis.

Key words: liver fibrosis, magnetic resonance imaging, texture analysis, Entropy, T1 mapping

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