Choi Jeong Min, Yu Jeong-Sik, Cho Eun-Suk, Kim Joo Hee, Chung Jae-Joon
From the Department of Radiology, Yonsei University College of Medicine, Gangnam Severance Hospital, Seoul, South Korea.
J Comput Assist Tomogr. 2020 Nov/Dec;44(6):901-910. doi: 10.1097/RCT.0000000000001087.
The aim of the study was to evaluate the performance of texture analysis for discriminating the histopathological grade of hepatocellular carcinoma (HCC) on magnetic resonance imaging.
Preoperative magnetic resonance imaging data from 101 patients with HCC, including T2-weighted imaging, arterial phase, and apparent diffusion coefficient mapping, were analyzed using texture analysis software (TexRAD). Differences among the histological groups were analyzed using the Mann-Whitney U test. The performance of texture features was evaluated using receiver operating characteristic analysis.
Entropy was the most significantly relevant texture feature for distinguishing each histological grade group of HCC (P < 0.05). In ROC analysis, entropy with spatial scale filter 3 (area under curve the receiver operating characteristic curve [AUC], 0.778), mean with coarse filter (spatial scale filter 5; AUC, 0.670), and skewness without filtration (AUC, 0.760) had the highest AUC value on T2-weighted imaging, arterial phase, and apparent diffusion coefficient maps, respectively.
Magnetic resonance imaging texture analysis demonstrated potential for predicting the histopathological grade of HCCs.
本研究旨在评估磁共振成像上纹理分析对鉴别肝细胞癌（HCC）组织病理学分级的性能。
使用纹理分析软件（TexRAD）分析101例HCC患者的术前磁共振成像数据，包括T2加权成像、动脉期和表观扩散系数图。使用曼-惠特尼U检验分析各组织学组之间的差异。使用受试者工作特征分析评估纹理特征的性能。
熵是区分HCC各组织学分级组最显著相关的纹理特征（P<0.05）。在ROC分析中，T2加权成像上空间尺度滤波器3的熵（受试者工作特征曲线下面积[AUC]，0.778）、粗滤波器（空间尺度滤波器5）的均值（AUC，0.670）以及未滤波的偏度（AUC，0.760）在动脉期和表观扩散系数图上分别具有最高的AUC值。
磁共振成像纹理分析显示出预测HCC组织病理学分级的潜力。
