Differentiating mild and substantial hepatic fibrosis from healthy controls: a comparison of diffusion kurtosis imaging and conventional diffusion-weighted imaging

医学 有效扩散系数 接收机工作特性 峰度 肝纤维化 磁共振弥散成像 纤维化 核医学 肝纤维化 曲线下面积 胃肠病学 病理 磁共振成像 内科学 放射科 统计 数学
作者
Shuangshuang Xie,Qing Li,Yue Cheng,Li Zhou,Shuang Xia,Jia Li,Wen Shen
出处
期刊:Acta Radiologica [SAGE]
卷期号:61 (8): 1012-1020 被引量:6
标识
DOI:10.1177/0284185119889566
摘要

Background Early and accurate detection of liver fibrosis are important for clinical treatment. Purpose To compare the diagnostic accuracy of liver diffusion kurtosis imaging (DKI) and conventional diffusion-weighted imaging (cDWI) in differentiating patients with mild and substantial fibrosis from normal individuals. Material and Methods Twenty-seven healthy volunteers with no fibrosis (S0) and 45 patients with mild (S1) or substantial (S2) liver fibrosis underwent DWI with multiple b-values. Liver mean apparent diffusion (MD) and mean kurtosis (MK) values derived from DKI and apparent diffusion coefficient (ADC) derived from cDWI were measured and compared. Their discriminative abilities were analyzed and compared by receiver operating characteristic (ROC) curve analysis. Results Significant differences in MD and ADC values were found between groups ( P < 0.05). MD value was statistically different between S0 and S1 ( P = 0.028) and S0 and S2 ( P = 0.005). ADC value was statistically different between S0 and S2 ( P = 0.012). MK value was similar between groups ( P = 0.646). MD and ADC values significantly correlated with fibrosis stages ( r s = −0.668, −0.341; P < 0.01). MK values had no correlation with fibrosis stages ( r s = 0.180; P = 0.130). The area under ROC curves (AUC) for MD and ADC was 0.937 and 0.707 for characterization of S1–2 and 0.817 and 0.658 for S2, respectively. MD performed better than ADC for characterization of S1–2 and S2 ( P < 0.05). Conclusion Differentiating patients with mild or substantial fibrosis from normal individuals is feasible using DKI, which performs better than cDWI.

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