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3D Whole-Brain Perfusion Quantification using Pseudo-ContinuousArterial Spin Labeling MRI at Multiple Post-Labeling Delays: Accounting for BothArterial Transit Time and Impulse Response Function

机译:使用伪连续的3D全脑灌注定量多次贴标延迟后的动脉自旋标记MRI:兼顾两者动脉过境时间和冲动反应功能

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摘要

Measurement of cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit the ASL-based perfusion kinetic curves, an empirical 3-parameter model that characterizes the effective impulse response function (IRF) is introduced, which allows determination of CBF, arterial transit time (ATT), and T1,eff. The accuracy and precision of the proposed model is compared with more complicated models with 4 or 5 parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling (PCASL) images were acquired on a clinical 3 Tesla scanner in 10 normal volunteers using a 3D multi-shot gradient- and spin-echo (GRASE) scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the 3-parameter model and other models that contain 2, 4 or 5 unknown parameters. For the 2-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicate that: 1) the estimated CBF values using the 2-parameter model show appreciable dependence on the assumed T1,eff values; 2) the proposed 3-parameter model achievesthe optimal balance between the goodness of fit and the model complexity whencompared among the models with explicit IRF fitting; 3) both the 2-parametermodel using fixed blood T1 values for T1,eff and the3-parameter model provide reasonable fitting results. Using the proposed3-parameter model, the estimated CBF values (46±14 mL/100g/min) and ATTvalues (ATT = 1.4±0.3 s) averaged from different brain regionsare close to the literature reports; the estimated T1,eff values(T1,eff = 1.9±0.4 s) are higher than the tissueT1 values, possibly reflecting a contribution from themicrovascular arterial blood compartment.
机译:在采集和定量分析方面,具有全脑覆盖范围的脑血流量(CBF)的测量具有挑战性。为了拟合基于ASL的灌注动力学曲线,引入了表征有效脉冲响应函数(IRF)的经验3参数模型,该模型可以确定CBF,动脉渡越时间(ATT)和T1,eff。通过蒙特卡洛模拟,将所提出模型的准确性和精度与具有4个或5个参数的更复杂模型进行比较。伪连续动脉自旋标记(PCASL)图像是使用3D多重梯度梯度和自旋回波(GRASE)方案在10个正常志愿者的临床3 Tesla扫描仪上以多个标记后延迟采集的,以采集动力学曲线。使用3参数模型和其他包含2、4或5个未知参数的模型进行体素方向拟合。对于2参数模型,分别假设接近组织和血液的T1,eff值。进行了标准统计分析,以比较各个大脑区域的这些拟合模型。拟合结果表明:1)使用2参数模型估算的CBF值显示出对假设的T1,eff值的明显依赖; 2)提出的3参数模型实现了拟合优度与模型复杂度之间的最佳平衡在具有明确IRF拟合的模型之间进行比较; 3)两个参数使用固定血液T1值的T1,eff和3参数模型提供合理的拟合结果。使用建议3参数模型,估计的CBF值(46±14 mL / 100g / min)和ATT不同大脑区域的平均值(ATT = 1.4±0.3 s)接近文献报道;估计的T1,eff值(T1,eff = 1.9±0.4 s)高于组织T1值,可能反映了微血管动脉血室。

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