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使用动脉自旋标记测量动脉和组织对功能挑战的反应。

Measuring arterial and tissue responses to functional challenges using arterial spin labeling.

机构信息

Department of Neuroradiology, National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore.

出版信息

Neuroimage. 2010 Jan 1;49(1):478-87. doi: 10.1016/j.neuroimage.2009.07.040. Epub 2009 Jul 25.

DOI:10.1016/j.neuroimage.2009.07.040
PMID:19635576
Abstract

The measurement of cerebral blood flow (CBF) in functional MRI studies that aim for non-invasive, quantitative and reliable measurements is a challenge. Here, we tested the feasibility of a recently developed, model-free CBF technique to study vascular dynamics upon functional challenges. Multiple inversion time-point signals were measured from arterial and tissue compartments, allowing for the calculation of CBF through a process of deconvolution. Using graded visual stimulation known to produce increasing hemodynamic responses, we recorded significant and graded DeltaCBF and Deltatau(m) (microvascular arrival time change) that were highly comparable to those estimated by a standard 3-parameter fit based on the general kinetic model, though the absolute values had weaker agreement. Estimated arterial blood volumes (excluding substantial arteriolar contribution) did not show significant change with visual stimulation. Bolus arrival times in the microvascular compartment shortened more as compared to the arrival times from the arterial compartment during visual stimulation, suggesting larger involvement of the microvasculature in local neuronal response. While there are limitations, the model-free analysis method has the potential to offer useful vascular information in fMRI studies.

摘要

在旨在进行非侵入性、定量和可靠测量的功能磁共振成像研究中,测量脑血流 (CBF) 是一项挑战。在这里,我们测试了一种最近开发的、无模型的 CBF 技术在功能挑战下研究血管动力学的可行性。从动脉和组织隔室测量多个反转时间点信号,通过解卷积过程计算 CBF。使用已知产生逐渐增加的血液动力学反应的分级视觉刺激,我们记录了显著的、分级的 DeltaCBF 和 Deltatau(m)(微血管到达时间变化),与基于一般动力学模型的标准 3-参数拟合估计的高度可比,尽管绝对值的一致性较弱。估计的动脉血容量(不包括大量的小动脉贡献)在视觉刺激时没有显示出显著变化。与动脉隔室的到达时间相比,在微脉管隔室中的示踪剂到达时间在视觉刺激期间缩短,表明微脉管系统在局部神经元反应中具有更大的参与度。虽然存在局限性,但无模型分析方法有可能在 fMRI 研究中提供有用的血管信息。

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