4.7 Article

Posttreatment High-Grade Glioma: Usefulness of Peak Height Position with Semiquantitative MR Perfusion Histogram Analysis in an Entire Contrast-enhanced Lesion for Predicting Volume Fraction of Recurrence

期刊

RADIOLOGY
卷 256, 期 3, 页码 906-915

出版社

RADIOLOGICAL SOC NORTH AMERICA
DOI: 10.1148/radiol.10091461

关键词

-

向作者/读者索取更多资源

Purpose: To determine whether semiquantitative histogram analysis of the normalized cerebral blood volume (CBV) for an entire contrast material-enhanced lesion could be used to predict the volume fraction of posttreatment high-grade glioma recurrence compared with posttreatment change. Materials and Methods: The institutional review board approved this retrospective study. Informed consent was obtained. Thirty-nine patients with pathologically proved predominant tumor recurrence (tumor recurrence group, tumor fraction >= 50% [n = 14]), mixed tumor and posttreatment change (mixed group, tumor fraction >= 20% and, 50% [n = 10]), and predominant posttreatment change (treatment change group, tumor fraction <20% [n = 15]) were evaluated. Histogram parameters of normalized CBV-histogram width, peak height position (PHP), and maximum value (MV)-were measured in entire contrast-enhanced lesions and used as discriminative indexes. Ordered logistic regression was used to determine independent factors for predicting the diseases of posttreatment contrast-enhanced lesions. Leave-one-out cross-validation was used to determine diagnostic accuracy. Results: PHP was an independent predictive factor (P = .003) for differentiating contrast-enhanced lesions in patients with posttreatment gliomas. According to receiver operating characteristic curve analyses, PHP provided sensitivity of 90.2% and specificity of 91.1% for differentiating tumor recurrence from mixed and treatment change groups at an optimum threshold of 1.7 by using leave-one-out cross-validation. MV helped distinguish treatment change group from tumor recurrence and mixed groups at an optimum threshold of 2.6 (sensitivity, 96.5%; specificity, 93.1%). Conclusion: PHP can be used to predict the volume fraction of posttreatment high-grade glioma recurrence. (C) RSNA, 2010

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据