Automated Processing of Dynamic Contrast-Enhanced MRI: Correlation of Advanced Pharmacokinetic Metrics with Tumor Grade in Pediatric Brain Tumors

动态增强磁共振成像的自动化处理:高级药代动力学指标与儿童脑肿瘤分级的相关性

阅读:2

Abstract

BACKGROUND AND PURPOSE: Pharmacokinetic parameters from dynamic contrast-enhanced MR imaging have proved useful for differentiating brain tumor grades in adults. In this study, we retrospectively reviewed dynamic contrast-enhanced perfusion data from children with newly diagnosed brain tumors and analyzed the pharmacokinetic parameters correlating with tumor grade. MATERIALS AND METHODS: Dynamic contrast-enhanced MR imaging data from 38 patients were analyzed by using commercially available software. Subjects were categorized into 2 groups based on pathologic analyses consisting of low-grade (World Health Organization I and II) and high-grade (World Health Organization III and IV) tumors. Pharmacokinetic parameters were compared between the 2 groups by using linear regression models. For parameters that were statistically distinct between the 2 groups, sensitivity and specificity were also estimated. RESULTS: Eighteen tumors were classified as low-grade, and 20, as high-grade. Transfer constant from the blood plasma into the extracellular extravascular space (K(trans)), rate constant from extracellular extravascular space back into blood plasma (K(ep)), and extracellular extravascular volume fraction (V(e)) were all significantly correlated with tumor grade; high-grade tumors showed higher K(trans), higher K(ep), and lower V(e). Although all 3 parameters had high specificity (range, 82%-100%), K(ep) had the highest specificity for both grades. Optimal sensitivity was achieved for V(e), with a combined sensitivity of 76% (compared with 71% for K(trans) and K(ep)). CONCLUSIONS: Pharmacokinetic parameters derived from dynamic contrast-enhanced MR imaging can effectively discriminate low- and high-grade pediatric brain tumors.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。