Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom.
Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom.
Magn Reson Med. 2021 Oct;86(4):2208-2219. doi: 10.1002/mrm.28839. Epub 2021 May 19.
Previously, multi- post-labeling delays (PLD) pseudo-continuous arterial spin labeling (pCASL) protocols have been optimized for the estimation accuracy of the cerebral blood flow (CBF) with/without the arterial transit time (ATT) under a standard kinetic model and a normal ATT range. This study aims to examine the estimation errors of these protocols under the effects of macrovascular contamination, flow dispersion, and prolonged arrival times, all of which might differ substantially in elderly or pathological groups.
Simulated data for four protocols with varying degrees of arterial blood volume (aBV), flow dispersion, and ATTs were fitted with different kinetic models, both with and without explicit correction for macrovascular signal contamination (MVC), to obtain CBF and ATT estimates. Sensitivity to MVC was defined and calculated when aBV > 0.5%. A previously acquired dataset was retrospectively analyzed to compare with simulation.
All protocols showed underestimation of CBF and ATT in the prolonged ATT range. With MVC, the protocol optimized for CBF only (CBFopt) had the lowest sensitivity value to MVC, 33.47% and 60.21% error per 1% aBV in simulation and in vivo, respectively, among multi-PLD protocols. All multi-PLD protocols showed a significant decrease in estimation error when an extended kinetic model was used. Increasing flow dispersion at short ATTs caused increasing CBF and ATT overestimation in all protocols.
CBFopt was the least sensitive protocol to prolonged ATT and MVC for CBF estimation while maintaining reasonably good performance in estimating ATT. Explicitly including a macrovascular component in the kinetic model was shown to be a feasible approach in controlling for MVC.
之前，多期标记延迟（PLD）伪连续动脉自旋标记（pCASL）方案已经针对标准动力学模型和正常 ATT 范围内的 ATT 下的脑血流（CBF）的估计准确性进行了优化。本研究旨在检查在大动脉污染、流动分散和延长到达时间的影响下这些方案的估计误差，所有这些在老年或病理组中可能有很大的不同。
对具有不同程度的动脉血容量（aBV）、流动分散和 ATT 的四种方案的模拟数据进行拟合，分别采用不同的动力学模型，包括和不包括对大动脉信号污染（MVC）的显式校正，以获得 CBF 和 ATT 估计值。当 aBV > 0.5%时，定义并计算了对 MVC 的敏感性。回顾性分析了先前获得的数据集，以便与模拟进行比较。
所有方案在延长的 ATT 范围内都显示出 CBF 和 ATT 的低估。有 MVC 时，仅针对 CBF 优化的方案（CBFopt）在模拟和体内的 MVC 中具有最低的敏感性值，分别为 33.47%和 60.21%的误差/每 1%的 aBV，在多期 PLD 方案中。当使用扩展的动力学模型时，所有多期 PLD 方案的估计误差都有显著降低。在所有方案中，在短 ATT 下增加流动分散会导致 CBF 和 ATT 的过度估计。
CBFopt 是针对 CBF 估计的延长 ATT 和 MVC 最不敏感的方案，同时在估计 ATT 时保持相当好的性能。在动力学模型中显式包括大动脉成分被证明是控制 MVC 的一种可行方法。
