A general linear relaxometry model of R1 using imaging data.
A general linear relaxometry model of R1 using imaging data.
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DOI：
10.1002/mrm.25210
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发表时间：
2015-03
影响因子：
3.3
通讯作者：
Weiskopf, Nikolaus
中科院分区：
文献类型：
--
作者：
Callaghan, Martina F.;Helms, Gunther;Lutti, Antoine;Mohammadi, Siawoosh;Weiskopf, Nikolaus
关键词：
体内测量的纵向松弛率（R1）取决于组织的局部微观结构特性，例如大分子、铁和水含量。在这里，我们使用全脑多参数体内数据和通用线性松弛测量模型来描述 R1 对这些成分的依赖性。我们探讨了a）全脑有一组固定模型系数的有效性和b）大群体中模型系数的稳定性。磁化转移（MT）图和有效横向弛豫率（R2*）分别用作大分子和铁含量的替代。这些参数的空间变化反映了底层组织微观结构的变化。将线性模型应用于整个大脑，包括灰质/白质和深部大脑结构，以确定全局模型系数。然后使用这些系数计算综合 R1 值，并与测量的 R1 图进行比较。该模型的有效性通过合成 R1 值与测量 R1 值之间的对应性以及大型队列中模型系数的高稳定性得到证明。一组全局系数可用于关联整个大脑的 R1、MT 和 R2*。我们的人口研究证明了该模型的稳健性和稳定性。 Magn Reson Med，2014。© 2014 作者。医学中的磁共振由 Wiley periodicals, Inc. 出版。Magn Reson Med 73:1309–1314, 2015。© 2014 Wiley periodicals, Inc.
The longitudinal relaxation rate (R1) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort. Maps of magnetization transfer (MT) and effective transverse relaxation rate (R2*) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R1 values were then calculated using these coefficients and compared with the measured R1 maps. The model's validity was demonstrated by correspondence between the synthetic and measured R1 values and by high stability of the model coefficients across a large cohort. A single set of global coefficients can be used to relate R1, MT, and R2* across the whole brain. Our population study demonstrates the robustness and stability of the model. Magn Reson Med, 2014. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. Magn Reson Med 73:1309–1314, 2015. © 2014 Wiley Periodicals, Inc.
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