利用肿瘤全域表观扩散系数信号强度直方图鉴别Ⅱ级与Ⅲ级胶质瘤

摘要

目的 评估基于肿瘤全域的表观扩散系数(apparent diffusion coefficient,ADC)信号强度直方图对于鉴别世界卫生组织(World Health Organization,WHO)Ⅱ级与Ⅲ级胶质瘤的价值,并探求二者之间鉴别诊断的影像标志物.材料与方法 回顾性分析经手术及病理证实的13例Ⅱ级胶质瘤与20例Ⅲ级胶质瘤的术前磁共振成像(magnetic resonance imaging,MRI)资料,在包含肿瘤实质或瘤周水肿的每一层ADC信号强度图上勾画感兴趣区(region of interest,ROI),得到3D ROI的ADC信号强度直方图信息及其所有参数,包括最小值、最大值、平均值、第10百分位数、第25百分位数、第50百分位数、第75百分位数、第90百分位数、值域、体素数、标准差、方差、平均差、偏度、峰度及一致性,进行组间比较,并利用受试者操作特性曲线(receiver operating characteristic,ROC)来确定直方图参数对于二者的诊断能力.结果 最小值(P=0.04)、第10百分位数(P=0.03)、体素数(P=0.003)、标准差(P=0.022)、偏度(P=0.017)在Ⅱ级与Ⅲ级胶质瘤间差异具有统计学意义.利用ROC曲线分析结果,以体素数5.65×106为阈值鉴别Ⅱ级与Ⅲ级胶质瘤的曲线下面积(area under the curve,AUC)最大,诊断能力最佳(AUC=0.856),敏感性及特异性分别为81.5%、80.0%,而偏度、标准差的诊断能力次之(AUC=0.75、0.738).结论 基于肿瘤全域感兴趣区的ADC信号强度直方图可以为Ⅱ级与Ⅲ级胶质瘤的鉴别诊断提供更多信息,体素数、偏度以及标准差具有良好的诊断价值.%Objective: To evaluate the differential diagnostic value of histogram analysis of ADC signal intensity based on entire region of grade Ⅱ and Ⅲ tumor, and then to investigate a potential imaging biomarker to differentiate them. Materials and Methods: Thirteen patients with grade Ⅱ glioma and 20 patients with grade Ⅲglioma were enrolled in this retrospective study, and all tumors were pathologically confirmed. ROIs containing the entire tumor and peripheral edema were drawn in each slice of the ADC signal intensity maps. Obtained the 3D ROI ADC signal strength histogram information and all its parameters. Histogram related parameters including min intensity, max intensity, mean value, the 10th, 25th, 50th, 75th and 90th percentiles, range, voxel number, standard deviation, variance, mean deviation, skewness, kurtosis and uniformity were recorded. The obtained parameters were compared between groups. Receiver operating characteristic (ROC) curve was constructed to assess the ability of parameters between grade Ⅱ and Ⅲ glioma. Results: Min Intensity (P=0.04), 10th percentiles (P=0.03), voxel number (P=0.003), standard deviation (P=0.022), skewness (P=0.017) showed significant difference between two groups. When optimal cut point of voxel number was 5.46×106 for diagnosis of grade Ⅱ and Ⅲ, the area under the ROC curve was maximum, which was 0.856, the sensitivity and specificity was 81.5%, 80.0%. When optimal cut point of skewness was -1.414, the area under the ROC curve was 0.750, the sensitivity and specificity was 100.0%, 60.0%. When optimal cut point of standard deviation was 14.602, the area under the ROC curve was 0.738, the sensitivity and specificity was 100.0%, 55.0%. Conclusion: Histogram analysis of ADC signal intensity based on entire tumor could provide more information in differentiation of grade Ⅱ and Ⅲ glioma. Voxel number, standard deviation and skewness showed superior diagnostic value.