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Partial volume correction of brain perfusion estimates using the inherent signal data of time-resolved arterial spin labeling.

机译:使用时间分辨动脉自旋标记的固有信号数据进行脑灌注估计的部分体积校正。

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摘要

Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume. Copyright © 2014 John Wiley & Sons, Ltd.
机译:基于动脉自旋标记(ASL)的定量灌注MRI受部分体积效应(PVE)的影响,该体积效应是由于不同隔室之间的体素信号交叉污染而引起的。为了解决这个问题,已经提出了几种部分体积校正(PVC)方法。以前的大多数方法都依赖于高分辨率T1加权形态图像体积的分割,该图像与低分辨率ASL数据共同配准,从而使结果对分割和配准中的错误敏感。在这项工作中,我们仅使用通过QUASAR序列获得的低分辨率ASL数据,提出了一种用于部分体积估计和校正的方法。该方法包括无空间先验的基于T1的分割方法,以及基于线性回归的改进的PVC方法。因此,所提出的方法避免了关于脑室空间分布的先前假设,同时还避免了不同图像体积之间的共容性。基于数字体模的仿真以及10位志愿者的体内测量被用于评估所提出的分割方法的性能。仿真结果表明,可以将QUASAR数据用于稳健的部分体积估算,这已通过体内实验得到证实。所提出的PVC方法产生了可能的灌注图,与基于高分辨率形态学扫描分割的参考方法相当。校正后的灰质(GM)灌注比未校正的值高47%,表明数据中存在大量PVE。虽然参考方法无法完全消除灌注估计值对体积分数的依赖性,但新方法产生的GM灌注值与GM体积分数无关。对于拟议的PVC方法,校正后的灌注值的受试者内部变异系数最低。如这项工作所示,将低分辨率的部分体积估算与ASL灌注估算结合起来是可行的,并且为将灌注与组织体积解耦提供了有希望的工具。版权所有©2014 John Wiley&Sons,Ltd.

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