Xie Jingyi, Gallichan Daniel, Gunn Roger N, Jezzard Peter
Centre for Functional Magnetic Resonance Imaging of the Brain, Department of Clinical Neurology, University of Oxford, Oxford, UK.
Magn Reson Med. 2008 Apr;59(4):826-34. doi: 10.1002/mrm.21549.
Quantitative measurement of cerebral blood flow (CBF) using arterial spin labeling (ASL) MRI requires the acquisition of multiple inversion times (TIs) and the application of an appropriate kinetic model. The choice of these sampling times will have an impact on the precision of the estimated parameters. Here, optimal sampling schedule (OSS) design techniques, based on the Fisher Information approach, are applied in order to derive an optimal sampling scheme for pulsed arterial spin labeling (PASL) experiments. Such an approach should improve the precision of parameter estimation from experimental data, and provide a formal framework for optimally selecting a limited number of samples. In this study, we aimed to optimize the estimation precision of CBF and bolus arrival time from the PASL data. The performance of OSS was compared to a more standard evenly distributed sampling schedule (EDS) using both simulated and measured experimental data sets. It was found that OSS was able to significantly improve the precision of parameter estimation in PASL studies that sought to estimate either both CBF and bolus arrival time, or CBF alone.
使用动脉自旋标记（ASL）磁共振成像（MRI）对脑血流量（CBF）进行定量测量需要采集多个反转时间（TIs）并应用适当的动力学模型。这些采样时间的选择将对估计参数的精度产生影响。在此，基于费舍尔信息方法的最优采样计划（OSS）设计技术被应用于推导脉冲动脉自旋标记（PASL）实验的最优采样方案。这种方法应提高从实验数据估计参数的精度，并为最优选择有限数量的样本提供一个正式框架。在本研究中，我们旨在优化从PASL数据估计CBF和团注到达时间的精度。使用模拟和实测实验数据集，将OSS的性能与更标准的均匀分布采样计划（EDS）进行了比较。结果发现，在试图同时估计CBF和团注到达时间或仅估计CBF的PASL研究中，OSS能够显著提高参数估计的精度。
