Chen Jean J, Smith Michael R, Frayne Richard
Department of Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada.
J Magn Reson Imaging. 2005 Sep;22(3):390-9. doi: 10.1002/jmri.20393.
To demonstrate the degree of the cerebral blood flow (CBF) estimation bias that could arise from distortion of the arterial input function (AIF) as a result of partial-volume effects (PVEs) in dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI).
A model of the volume fraction an artery occupies in a voxel was devised, and a mathematical relationship between the amount of PVE and the measured baseline MR signal intensity was derived. Based on this model, simulation studies were performed to assess the impact of PVE on CBF. Furthermore, the effectiveness of linear PVE compensation approaches on the concentration function was investigated.
Simulation results showed a nonlinear relationship between PVE and the resulting CBF measurement error. In addition to AIF underestimation, PVE also causes distortions of AIF frequency characteristics, leading to CBF errors varying with mean transit time (MTT). An uncorrected AIF measured at a voxel with a partial-volume fraction of <or=50% could produce a CBF overestimation of more than fourfold. Linear compensation of the concentration curves did not produce correct CBF estimates.
PVE can induce significant CBF estimation biases. In addition, the MTT dependence of CBF accuracy raises doubts of the validity of adopting a single cross-calibration factor (i.e., setting normal white matter to 22 mL minute(-1) (100 g)(-1)) to obtain CBF values with absolute units. The impact of PVE may be reduced by decreasing the maximum arterial signal drop in the perfusion images. To correct the AIF distortions introduced by PVE, the nonlinear relationship between the impact of PVE on MR signal intensity and contrast concentration function must be considered.
证明在动态磁敏感对比(DSC)磁共振成像(MRI)中,由于部分容积效应(PVE)导致动脉输入函数(AIF)失真而可能产生的脑血流量(CBF)估计偏差程度。
设计了一个动脉在体素中所占体积分数的模型,并推导了PVE量与测量的基线MR信号强度之间的数学关系。基于该模型,进行了模拟研究以评估PVE对CBF的影响。此外,还研究了线性PVE补偿方法对浓度函数的有效性。
模拟结果显示PVE与由此产生的CBF测量误差之间存在非线性关系。除了AIF低估外,PVE还会导致AIF频率特性失真,从而导致CBF误差随平均通过时间(MTT)而变化。在部分容积分数≤50%的体素处测量的未校正AIF可能会导致CBF高估超过四倍。浓度曲线的线性补偿无法产生正确的CBF估计值。
PVE可引起显著的CBF估计偏差。此外,CBF准确性对MTT的依赖性使人怀疑采用单一交叉校准因子(即将正常白质设置为22 mL·分钟⁻¹·(100 g)⁻¹)以获得具有绝对单位的CBF值的有效性。通过降低灌注图像中最大动脉信号下降幅度,可以减少PVE的影响。为了校正PVE引入的AIF失真,必须考虑PVE对MR信号强度和对比浓度函数影响之间的非线性关系。