李颖;陈基明;高静;张爱娟;

• 1:皖南医学院弋矶山医院医学影像中心

摘要(Abstract)：

目的探讨CT平扫图像密度联合纹理特征参数在术前评估脑膜瘤质地中的价值。方法回顾性分析我院医学影像中心2013年1月至2019年7月间经手术病理证实的55例脑膜瘤患者的完整资料,根据术中脑膜瘤质地分为质软组(n=17)与质韧组(n=38)。在CT图像上瘤体最大截面手动勾画感兴趣区,测量病灶的CT值,提取纹理特征参数。利用最小冗余最大相关算法、最小绝对收缩和选择算子回归方法分析筛选纹理特征参数,采用多因素logistic回归分析建立预测脑膜瘤质地的模型,并绘制ROC曲线评价模型预测效能。结果质软组与质韧组间CT值差异具有统计学意义(t=-2.558、P=0.017),CT值预测脑膜瘤质地的曲线下面积(Area Under Curve, AUC)为0.813。基于CT平扫图像提取的1044个纹理特征参数中,共筛选出3个参数(偏度、45度惯性_步长8和全角高灰度游程优势_步长8_标准差),且在两组间差异具有统计学意义(t=-2.733、-2.492、-2.283;P=0.009、0.016、0.026),预测脑膜瘤质地AUC分别为0.731、0.650、0.584;纹理特征模型预测脑膜瘤质地的AUC为0.825;CT值联合纹理特征模型AUC为0.928。结论 CT值联合纹理特征模型具有较高预测脑膜瘤质地的效能,为术前预测脑膜瘤质地提供了一种新的定量分析方法。

关键词(KeyWords)： 脑膜瘤质地;纹理分析;体层摄影术;X线计算机

Abstract:

Keywords:

基金项目(Foundation):

作者(Authors): 李颖;陈基明;高静;张爱娟;

DOI: 10.13799/j.cnki.mdjyxyxb.2021.05.012

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