Differentiation of Tumor Progression from Pseudoprogression in Patients with Posttreatment Glioblastoma Using Multiparametric Histogram Analysis
Differentiation of Tumor Progression from Pseudoprogression in Patients with Posttreatment Glioblastoma Using Multiparametric Histogram Analysis
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DOI：
10.3174/ajnr.a3876
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发表时间：
2014-07-01
影响因子：
3.5
通讯作者：
Nam, D. -H.
中科院分区：
文献类型：
--
作者：
Cha, J.;Kim, S. T.;Nam, D. -H.
背景和目的：多参数成像可以显示肿瘤行为的不同方面，并有助于区分肿瘤复发与治疗相关变化。我们的目的是区分肿瘤的进展与胶质母细胞瘤患者的假性进展，通过使用多参数直方图分析2个连续的MR成像研究与相对脑血容量和ADC values.MATERIALS和方法：35个连续的胶质母细胞瘤患者与新的或增加的大小增强病变后，伴随放化疗治疗手术切除术后被纳入。将初次和随访时MRI增强区的相对脑血容量和ADC值制成组合直方图，并制作减影直方图。比较各组直方图参数。肿瘤进展的诊断准确性的基础上的直方图参数的初始和后续的MR成像和减影直方图进行了比较，并与总survival.RESULTS：24 pseudoprogression和11肿瘤进展进行了测定。基于减影直方图模式与多参数方法的诊断比基于单参数方法的诊断更准确（受试者工作特征曲线下面积为0.877 vs 0.801），灵敏度为81.8%，特异性为100%。采用多参数方法（相对脑血容量X ADC）在减影直方图上的高模式相对脑血容量是真实肿瘤进展（P < .001）和较差生存期（P = .003）的最佳预测因子。结论：治疗后胶质母细胞瘤的多参数直方图分析有助于预测真实肿瘤进展和较差生存期。
BACKGROUND AND PURPOSE: The multiparametric imaging can show us different aspects of tumor behavior and may help differentiation of tumor recurrence from treatment related change. Our aim was to differentiate tumor progression from pseudoprogression in patients with glioblastoma by using multiparametric histogram analysis of 2 consecutive MR imaging studies with relative cerebral blood volume and ADC values.MATERIALS AND METHODS: Thirty-five consecutive patients with glioblastoma with new or increased size of enhancing lesions after concomitant chemoradiation therapy following surgical resection were included. Combined histograms were made by using the relative cerebral blood volume and ADC values of enhancing areas for initial and follow-up MR imaging, and subtracted histograms were also prepared. The histogram parameters between groups were compared. The diagnostic accuracy of tumor progression based on the histogram parameters of initial and follow-up MR imaging and subtracted histograms was compared and correlated with overall survival.RESULTS: Twenty-four pseudoprogressions and 11 tumor progressions were determined. Diagnosis based on the subtracted histogram mode with a multiparametric approach was more accurate than the diagnosis based on the uniparametric approach (area under the receiver operating characteristic curve of 0.877 versus 0.801), with 81.8% sensitivity and 100% specificity. A high mode of relative cerebral blood volume on the subtracted histogram by using a multiparametric approach (relative cerebral blood volume X ADC) was the best predictor of true tumor progression (P < .001) and worse survival (P = .003).CONCLUSIONS: Multiparametric histogram analysis of posttreatment glioblastoma was useful to predict true tumor progression and worse survival.