Suppr超能文献

使用伪连续动脉自旋标记磁共振成像在多个标记后延迟时间进行三维全脑灌注定量:同时考虑动脉通过时间和脉冲响应函数。

Three-dimensional whole-brain perfusion quantification using pseudo-continuous arterial spin labeling MRI at multiple post-labeling delays: accounting for both arterial transit time and impulse response function.

作者信息

Qin Qin, Huang Alan J, Hua Jun, Desmond John E, Stevens Robert D, van Zijl Peter C M

机构信息

Russell H. Morgan Department of Radiology and Radiological Science Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.

出版信息

NMR Biomed. 2014 Feb;27(2):116-28. doi: 10.1002/nbm.3040. Epub 2013 Oct 16.

Abstract

Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective impulse response function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T(1,eff). The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T(1,eff) values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T(1,eff) values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T(1,eff) and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46 ± 14 mL/100 g/min) and ATT (1.4 ± 0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T(1,eff) values (1.9 ± 0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.

摘要

在全脑覆盖的情况下,测量脑血流量(CBF)在采集和定量分析方面都具有挑战性。为了拟合基于动脉自旋标记的灌注动力学曲线,引入了一个经验性的三参数模型,该模型表征了有效脉冲响应函数(IRF),从而能够确定CBF、动脉传输时间(ATT)和T(1,eff)。通过蒙特卡罗模拟,将所提出模型的准确性和精密度与更复杂的四参数或五参数模型进行了比较。在10名正常志愿者身上,使用临床3-T扫描仪,采用三维多激发梯度和自旋回波序列,在多个标记后延迟时间采集伪连续动脉自旋标记图像,以采样动力学曲线。使用三参数模型和包含两个、四个或五个未知参数的其他模型进行体素拟合。对于两参数模型,分别假设T(1,eff)值接近组织和血液的值。进行标准统计分析以比较这些拟合模型在不同脑区的情况。拟合结果表明:(i)使用两参数模型估计的CBF值对假设的T(1,eff)值有明显依赖性;(ii)在所提出的具有显式IRF拟合的模型中,三参数模型在拟合优度和模型复杂性之间实现了最佳平衡;(iii)使用固定血液T1值作为T(1,eff)的两参数模型和三参数模型都提供了合理的拟合结果。使用所提出的三参数模型,不同脑区平均估计的CBF(46±14 mL/100 g/min)和ATT(1.4±0.3 s)值接近文献报道;估计的T(1,eff)值(1.9±0.4 s)高于组织T1值,可能反映了微血管动脉血腔的贡献。

相似文献

3
Time-efficient measurement of multi-phase arterial spin labeling MR signal in white matter.
NMR Biomed. 2016 Nov;29(11):1519-1525. doi: 10.1002/nbm.3603. Epub 2016 Sep 5.
4
Cerebral blood flow quantification in swine using pseudo-continuous arterial spin labeling.
J Magn Reson Imaging. 2013 Nov;38(5):1111-8. doi: 10.1002/jmri.24066. Epub 2013 Sep 16.
7
Volumetric measurement of perfusion and arterial transit delay using hadamard encoded continuous arterial spin labeling.
Magn Reson Med. 2013 Apr;69(4):1014-22. doi: 10.1002/mrm.24335. Epub 2012 May 22.
10
Use of 3D pseudo-continuous arterial spin labeling to characterize sex and age differences in cerebral blood flow.
Neuroradiology. 2016 Sep;58(9):943-8. doi: 10.1007/s00234-016-1713-y. Epub 2016 Jul 5.

引用本文的文献

7
Multidelay ASL of the pediatric brain.
Br J Radiol. 2022 Jun 1;95(1134):20220034. doi: 10.1259/bjr.20220034. Epub 2022 May 12.
9
Age-dependent cerebrospinal fluid-tissue water exchange detected by magnetization transfer indirect spin labeling MRI.
Magn Reson Med. 2022 May;87(5):2287-2298. doi: 10.1002/mrm.29137. Epub 2021 Dec 27.
10
Cerebrospinal fluid-tissue exchange revealed by phase alternate labeling with null recovery MRI.
Magn Reson Med. 2022 Mar;87(3):1207-1217. doi: 10.1002/mrm.29092. Epub 2021 Nov 19.

本文引用的文献

1
Point spread functions of the T2 decay in k-space trajectories with long echo train.
Magn Reson Imaging. 2012 Oct;30(8):1134-42. doi: 10.1016/j.mri.2012.04.017. Epub 2012 Jul 18.
2
Modeling dispersion in arterial spin labeling: validation using dynamic angiographic measurements.
Magn Reson Med. 2013 Feb;69(2):563-70. doi: 10.1002/mrm.24260. Epub 2012 Apr 5.
4
Statistical comparison of dynamic contrast-enhanced MRI pharmacokinetic models in human breast cancer.
Magn Reson Med. 2012 Jul;68(1):261-71. doi: 10.1002/mrm.23205. Epub 2011 Nov 29.
5
Reduced resolution transit delay prescan for quantitative continuous arterial spin labeling perfusion imaging.
Magn Reson Med. 2012 May;67(5):1252-65. doi: 10.1002/mrm.23103. Epub 2011 Nov 14.
6
Optimization of background suppression for arterial spin labeling perfusion imaging.
MAGMA. 2012 Apr;25(2):127-33. doi: 10.1007/s10334-011-0286-3. Epub 2011 Oct 19.
7
A two-stage approach for measuring vascular water exchange and arterial transit time by diffusion-weighted perfusion MRI.
Magn Reson Med. 2012 May;67(5):1275-84. doi: 10.1002/mrm.23104. Epub 2011 Aug 19.
8
Measurement of absolute arterial cerebral blood volume in human brain without using a contrast agent.
NMR Biomed. 2011 Dec;24(10):1313-25. doi: 10.1002/nbm.1693. Epub 2011 May 24.
9
Fast measurement of blood T1 in the human jugular vein at 3 Tesla.
Magn Reson Med. 2011 May;65(5):1297-304. doi: 10.1002/mrm.22723. Epub 2010 Nov 30.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验