DCE-MRI在脑胶质瘤分级诊断中的动脉输入函数选择分析

Effects of artery input function in dynamic contrast enhanced MRI for determining grades of gliomas

目的 :评价从不同动脉获取的动脉输入函数(Artery input function,AIF)对动态对比增强磁共振成像(DCE-MRI)定量参数准确估算的影响。材料和方法:回顾性分析28例经病理学证实的Ⅰ~Ⅳ级胶质瘤患者的DCE-MRI图像,用非线性最小二乘拟合方法和药代动力学双室模型计算与肿瘤分级相关的定量参数体积转移常数(Ktrans)和血管外细胞外空间容积分数(Ve);分析和比较分别从大脑前动脉(ACA)、大脑中动脉(MCA)和大脑后动脉(PCA)测得AIF计算的定量参数用于脑胶质瘤分级的准确性。结果:基于PCA测得的AIF计算的Ktrans和Ve值显著高于基于ACA和MCA测得的AIF计算的Ktrans和Ve值(P<0.05);基于ACA、MCA和PCA测得的AIF计算的Ktrans和Ve值均可区别低级别和高级别胶质瘤(P<0.05);基于ACA及MCA测得的AIF计算的Ktrans值可用于区分Ⅱ级和Ⅲ级脑胶质瘤(P<0.05)。结论:基于ACA、MCA和PCA测得AIF计算的定量参数Ktrans和Ve值均可用于脑胶质瘤分级诊断,基于MCA可作为获取AIF的最佳选择。

Objective: To evaluate the effect of artery input function(AIF) located in different arteries on the quantitative dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI) parameters. Methods: Retrospective analysis of DCE-MRI perfusion data was performed on 28 patients with histologically confirmed Ⅰ~Ⅳ grades of gliomas. Tracer kinetic parameters Ktransand Vewere calculated using a pharmacokinetic two-compartment model and nonlinear least square fitting method with different AIFs from anterior cerebral artery(ACA), middle cerebral artery(MCA) and posterior cerebral artery(PCA) in the ipsilateral and contralateral hemispheres relative to the tumor, respectively. The measurements were statistically analyzed using test with a value of P<0.05 regarded as statistically significant. Results: Ktransand Vecalculated from PCA were significant higher than those from ACA and MCA(P<0.05). Although there existed significant different in Ktransand Vecalculated based on AIF from any one artery between low and high grade(P<0.05), for distinguishing grade Ⅱ and Ⅲ, only Ktransfrom ACA and MCA have a P value less than 0.05(P=0.014). Conclusion: It is practical to use an AIF from any one artery for pharmacokinetic modeling of DCE-MRI data, but the best choice for AIF is MCA.