■探讨高级MR成像中的多参数对神经胶质瘤患者Ki-67标记指数(LI)的预测价值。
■回顾性评估了109例经组织学证实的神经胶质瘤患者。这些患者接受了高级MR成像,包括动态磁化率加权对比增强MR成像(DSC),磁共振波谱成像(MRS),弥散加权成像(DWI)和弥散张量成像(DTI),治疗前。提取了21个参数,包括最大值,相对脑血流量(rCBF)的最小值和平均值,相对脑血容量(rCBV),相对平均渡越时间(rMTT),相对表观扩散系数(rADC),分别为相对分数各向异性(rFA)和相对平均扩散系数(rMD),和胆碱(Cho)/肌酸(Cr)的比例,Cho/N-乙酰天冬氨酸(NAA)和NAA/Cr。进行逐步回归以建立多变量模型来预测Ki-67LI。采用Pearson相关分析探讨影像学参数与胶质瘤分级的相关性。单因素方差分析(ANOVA)用于探讨II级胶质瘤之间成像参数的差异,III,和IV。
■多元回归表明,五个参数的模型,包括rCBVmax(RC=0.282),rCBFmax(RC=0.151),rADCmin(RC=-0.14),rFAmax(RC=0.325)和Cho/Cr比率(RC=0.157)预测Ki-67LI的均方根(RMS)误差为0。0679(R2=0.8025)。该模型的回归检验表明,不存在多重共线性问题(方差膨胀因子:rCBVmax,3.22;rCBFmax,3.14;rADCmin,1.96;rFAmax,2.51;Cho/Cr比,1.64),该模型的函数形式是合适的(F检验:p=0.682)。Pearson相关分析结果表明,rCBFmax,rFAmax,Cho/Cr和Cho/NAA比值与Ki-67LI和胶质瘤分级呈正相关,rADCmin和rMDmin与Ki-67LI和胶质瘤分级呈负相关。
■结合来自DSC的多个参数,DTI,DWI和MRS可以准确预测胶质瘤患者的Ki-67LI。
UNASSIGNED: To investigate the predictive value of multi-parameters derived from advanced MR imaging for Ki-67 labeling index (LI) in glioma patients.
UNASSIGNED: One hundred and nine patients with histologically confirmed gliomas were evaluated retrospectively. These patients underwent advanced MR imaging, including dynamic susceptibility-weighted contrast enhanced MR imaging (DSC), MR spectroscopy imaging (MRS), diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI), before treatment. Twenty-one parameters were extracted, including the maximum, minimum and mean values of relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), relative mean transit time (rMTT), relative apparent diffusion coefficient (rADC), relative fractional anisotropy (rFA) and relative mean diffusivity (rMD) respectively, and ration of choline (Cho)/creatine (Cr), Cho/N-acetylaspartate (NAA) and NAA/Cr. Stepwise multivariate regression was performed to build multivariate models to predict Ki-67 LI. Pearson correlation analysis was used to investigate the correlation between imaging parameters and the grade of glioma. One-way analysis of variance (ANOVA) was used to explore the differences of the imaging parameters among the gliomas of grade II, III, and IV.
UNASSIGNED: The multivariate regression showed that the model of five parameters, including rCBVmax (RC=0.282), rCBFmax (RC=0.151), rADCmin (RC= -0.14), rFAmax (RC=0.325) and Cho/Cr ratio (RC=0.157) predicted the Ki-67 LI with a root mean square (RMS) error of 0. 0679 (R2 = 0.8025).The regression check of this model showed that there were no multicollinearity problem (variance inflation factor: rCBVmax, 3.22; rCBFmax, 3.14; rADCmin, 1.96; rFAmax, 2.51; Cho/Cr ratio, 1.64), and the functional form of this model was appropriate (F test: p=0.682). The results of Pearson correlation analysis showed that the rCBVmax, rCBFmax, rFAmax, the ratio of Cho/Cr and Cho/NAA were positively correlated with Ki-67 LI and the grade of glioma, while the rADCmin and rMDmin were negatively correlated with Ki-67 LI and the grade of glioma.
UNASSIGNED: Combining multiple parameters derived from DSC, DTI, DWI and MRS can precisely predict the Ki-67 LI in glioma patients.