Comparison of microvascular permeability measurements, K(trans), determined with conventional steady-state T1-weighted and first-pass T2*-weighted MR imaging methods in gliomas and meningiomas.
Comparison of microvascular permeability measurements, K(trans), determined with conventional steady-state T1-weighted and first-pass T2*-weighted MR imaging methods in gliomas and meningiomas.
复制标题
DOI：
--
复制
发表时间：
2006-02
期刊：
影响因子：
--
通讯作者：
S. Cha;L. Yang;G. Johnson;A. Lai;M.-H. Chen;T. Tihan;M. Wendland;W. Dillon
中科院分区：
文献类型：
--
作者：
S. Cha;L. Yang;G. Johnson;A. Lai;M.-H. Chen;T. Tihan;M. Wendland;W. Dillon
背景和目的目前广泛接受的定量脑肿瘤微血管通透性K（transs）的MR方法是稳态T1加权梯度回波法（ssT 1）。最近，首次通过T2* 加权（fpT 2 *）方法已被用于推导相对脑血容量（rCBV）和K（transs）。我们假设，K（反式）来自ssT 1和fpT 2 * 方法将在胶质瘤和脑膜瘤不同的相关性，因为每个肿瘤血管网络的形态和功能状态的独特差异。方法27例新诊断胶质瘤（WHO分级I-IV级; n = 20）或脑膜瘤（n = 7）患者在手术前接受常规解剖MR成像和12次动态ssT 1采集，随后在服用gadopentate dimeglumine前后进行60次动态fpT 2 * 成像。3个血流动力学变量fpT 2 * rCBV，fpT 2 * K（反式）和ssT 1 K（反式）在解剖学上相同的位置进行计算，并与胶质瘤分级相关。将胶质瘤和脑膜瘤的fpT 2 * K（transs）值与ssT 1 K（transs）值进行比较。结果Kruskal-Wallis检验显示，所有3个血流动力学变量在2级、3级和4级胶质瘤中均显示出明显的分布。只有K（反）值，而不是rCBV，可以区分4级和低级别胶质瘤使用Wilcoxon秩和检验。fpT 2 * K（transs）对胶质瘤的ssT 1 K（transs）具有高度预测性，估计回归系数为0.49（P < .001）。然而，对于脑膜瘤，fpT 2 * K（反式）值与ssT 1 K（反式）值相关性较差（r = 0.26; P = 0.74）。结论与rCBV相比，ssT 1和fpT 2 * 的K（transs）值更能预测胶质瘤的分级。胶质瘤中fpT 2 * K（transs）与ssT 1 K（transs）高度相关，而脑膜瘤中fpT 2 * K（transs）与ssT 1 K（transs）不相关。
BACKGROUND AND PURPOSE The widely accepted MR method for quantitating brain tumor microvascular permeability, K(trans), is the steady-state T1-weighted gradient-echo method (ssT1). Recently the first-pass T2*-weighted (fpT2*) method has been used to derive both relative cerebral blood volume (rCBV) and K(trans). We hypothesized that K(trans) derived from the ssT1 and the fpT2* methods will correlate differently in gliomas and meningiomas because of the unique differences in morphologic and functional status of each tumor vascular network. METHODS Before surgery, 27 patients with newly diagnosed gliomas (WHO grade I-IV; n = 20) or meningiomas (n = 7) underwent conventional anatomic MR imaging and 12 dynamic ssT1 acquisitions followed by 60 dynamic fpT2* images before and after gadopentate dimeglumine administration. The 3 hemodynamic variables-fpT2* rCBV, fpT2* K(trans), and ssT1 K(trans)-were calculated in anatomically identical locations and correlated with glioma grade. The fpT2* K(trans) values were compared with ssT1 K(trans) for gliomas and meningiomas. RESULTS All 3 hemodynamic variables displayed distinct distributions among grades 2, 3, and 4 gliomas by using the Kruskal-Wallis test. Only K(trans) values, and not rCBV, could differentiate between grade 4 and lower-grade gliomas by using the Wilcoxon rank sum test. The fpT2* K(trans) was highly predictive of ssT1 K(trans) for gliomas, with an estimated regression coefficient of 0.49 (P < .001). For meningiomas, however, fpT2* K(trans) values correlated poorly with ssT1 K(trans) values (r = 0.26; P = .74). CONCLUSION Compared with rCBV, K(trans) values derived from either ssT1 or fpT2* were more predictive of glioma grade. The fpT2* K(trans) was highly correlated with ssT1 K(trans) in gliomas but not in meningiomas.