梅东东,罗燕,龚静山,彭全洲,成志强.基于全肿瘤ADC图纹理特征诊断脑胶质瘤分级[J].中国医学影像技术,2019,35(7):976~980 |
基于全肿瘤ADC图纹理特征诊断脑胶质瘤分级 |
Whole tumor ADC-derived texture features in grading of brain glioma |
投稿时间:2018-11-26 修订日期:2019-05-15 |
DOI:10.13929/j.1003-3289.201811139 |
中文关键词: 神经胶质瘤 表观扩散系数 放射组学 磁共振成像 |
英文关键词:glioma apparent diffusion coefficient radiomics magnetic resonance imaging |
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中文摘要: |
目的 探讨基于全肿瘤ADC图的纹理特征鉴别高级别胶质瘤(HGG)与低级别胶质瘤(LGG)的价值。方法 收集66例经病理证实的脑胶质瘤患者,HGG 41例和LGG 25例。基于术前ADC图,提取107个全肿瘤纹理特征,比较HGG与LGG患者107个纹理特征和临床特征的差异;将差异有统计学意义的变量纳入Logistic回归分析模型,筛选出HGG的独立危险因素,并绘制ROC曲线,评价其诊断HGG的效能。结果 单因素分析显示LGG与HGG患者性别、年龄和3个纹理特征(表面体积比、总能量和区域熵)差异有统计学意义。Logistic回归分析显示年龄(P=0.002,优势比=1.090)和区域熵(P=0.003,优势比=2.984)为HGG的独立危险因素。联合年龄和区域熵诊断HGG的ROC曲线下面积为0.844,敏感度为75.6%,特异度为88.0%。结论 基于全肿瘤ADC图纹理特征有助于判断脑胶质瘤级别,联合临床特征诊断效能较高。 |
英文摘要: |
Objective To investigate the value of whole tumor texture features derived from ADC mapping in distinguishing high grade glioma (HGG) from low grade glioma (LGG) of brain. Methods Totally 66 patients with pathologic proven brain glioma were enrolled, including 41 HGGs and 25 LGGs. Then 107 texture features were derived from whole tumor ADC mapping. The texture features and clinical characteristics were compared, and the variates with statistical significance at univariate analysis were entered into Logistic analysis to find out the independent risk factors for HGG. ROC curves were constructed to determine the diagnostic performance of HGG. Results The univariate analysis revealed that the gender and age of patients as well as 3 texture features were different between HGGs and LGGs. Logistic analysis showed that age (P=0.002, OR=1.090) and ZoneEntropy (P=0.003, OR=2.984) were independent risk factors for HGG. Combining age and ZoneEntropy, the AUC of identifying HGG was 0.844, with a sensitivity of 75.6% and a specificity of 88.0%. Conclusion The whole tumor ADC-derived texture features are useful for grading of brain glioma grade. Combining texture features with clinical characteristics can obtain high diagnostic performance. |
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