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目的:研究磁共振22 b值e DWI(b值范围0~5 000 s/mm2)体素内不相干运动(intravoxel incoherent motion,IVIM)成像与T1动态对比增强磁共振成像(dynamic contrast enhanced MRI,DCE-MRI)评价脑胶质瘤微循环灌注的相关性。方法:92例手术病理证实的成人胶质瘤患者术前进行MRI、e DWI和T1 DCE-MRI。所有胶质瘤分为低级别组(low-grade glioma,LGG)(Ⅱ级)、高级别组(high-grade gliomas,HGG)(Ⅲ+Ⅳ级);胶质母细胞瘤组(glioblastoma multiforme,GBM)(Ⅳ级)、其他级别组(other-grade gliomas,OGG)(Ⅱ+Ⅲ级)。工作站进行e DWI和DCE-MRI后处理,抽取IVIM双指数模型灌注相关的Dfast和PF两个参数,以及DCE-MRI拟合的血管与血管外细胞外间隙(extravascular extracellular space,EES)转运常数(volume transfer constant,Ktrans)、容积分数(extravascular extracellular space volume fraction,Ve)、EES反向容积转运常数(Kep)和血浆容积分数(fraction of plasma volume,Vp)4个参数,选取肿瘤最大层面实性区域勾画感兴趣区,测定以上参数的平均值。Dfast、PF分别与Ktrans、Ve、Vp和Kep进行Spearman相关性分析,并比较LGG与HGG、GBM与OGG组之间的差异。受试者工作操作特性(receiver operating characteristic,ROC)曲线分析不同参数对胶质瘤分级的能力。结果:Dfast与Ve、Vp呈中等相关(ρ=0.460和0.412,P<0.01),与Ktrans相关性稍弱(ρ=0.396,P<0.01),与Kep没有相关性;PF与Vp、Ktrans和Ve呈弱负相关(ρ=-0.345、-0.323和-0.249,P均<0.05),与Kep不相关。除Kep外,其余参数在LGG与HGG、GBM与OGG之间均有显著性差异(P均<0.01)。ROC曲线分析各参数鉴别HGG与LGG的能力(AUC,95%CI):Ktrans的AUC值最高,为0.808(0.717,0.899)。ROC曲线分析各参数鉴别GBM与OGG的能力(AUC,95%CI):Dfast最高,为0.802(0.703,0.902)。结论:胶质瘤IVIM灌注相关参数与DCE-MRI密切相关,Dfast是无需外源性造影剂示踪的活体评价脑胶质瘤灌注的潜在标记物。
OBJECTIVE: To investigate the relationship between intra-arterial incoherent motion (IVIM) imaging of 22 b value e DWI (b value range of 0-5000 s / mm 2) and dynamic contrast enhanced MRI (TIA) DCE-MRI) to evaluate the correlation between microcirculation perfusion of glioma. Methods: Totally 92 adult patients with pathologically confirmed adult glioma underwent MRI, e DWI and T1 DCE-MRI before operation. All gliomas were divided into low-grade glioma (LGG) (grade Ⅱ), high-grade gliomas (grade Ⅲ + Ⅳ), glioblastoma multiforme GBM) (grade IV), other-grade gliomas (grade OGG) (grade II + III). The workstation performed e DWI and DCE-MRI post-processing, extracted two parameters of Dfast and PF related to perfusion of IVIM double index model, and DCE-MRI fitted vascular and extravascular extracellular space (EES) transport constants volume transfer constant (Ktrans), extravascular extracellular space volume fraction (Ve), Kep and fraction of plasma volume (Vp) Regions of interest outlined, determination of the average of the above parameters. Spearman correlation analysis was performed between Dfast and PF with Ktrans, Ve, Vp and Kep respectively, and the differences between LGG and HGG, GBM and OGG groups were compared. Receiver operating characteristic (ROC) curve was used to analyze the ability of different parameters to grade glioma. Results: Dfast was moderately correlated with Ve and Vp (ρ = 0.460 and 0.412, P <0.01), but slightly correlated with Ktrans (ρ = 0.396, P <0.01) Ve showed weak negative correlation (ρ = -0.345, -0.323 and -0.249, P <0.05), but not Kep. Except Kep, the other parameters were significantly different between LGG and HGG, GBM and OGG (all P <0.01). ROC curve analysis of the parameters of the ability to identify HGG and LGG (AUC, 95% CI): Ktrans AUC highest value of 0.808 (0.717,0.899). ROC curve analysis of the ability to identify GBM and OGG parameters (AUC, 95% CI): Dfast highest, 0.802 (0.703,0.902). CONCLUSIONS: The parameters related to glioma IVIM perfusion are closely related to DCE-MRI, and Dfast is a potential biomarker for glioma perfusion in vivo without exogenous contrast media tracing.