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Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network: Part I: methodology and baseline flow.

机译:在解剖学上精确的大型人类血管网络中通过皮层内小动脉调节脑血流量的模拟研究:第一部分:方法和基线流量。

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Hemodynamically based functional neuroimaging techniques, such as BOLD fMRI and PET, provide indirect measures of neuronal activity. The quantitative relationship between neuronal activity and the measured signals is not yet precisely known, with uncertainties remaining about the relative contribution by their metabolic and hemodynamic components. Empirical observations have demonstrated the importance of the latter component and suggested that micro-vascular anatomy has a potential influence. The recent development of a 3D computer-assisted method for micro-vascular cerebral network analysis has produced a large quantitative library on the microcirculation of the human cerebral cortex (Cassot et al., 2006), which can be used to investigate the hemodynamic component of brain activation through fluid dynamic modeling. For this purpose, we perform the first simulations of blood flow in an anatomically accurate large human intra-cortical vascular network (~10000 segments), using a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation. This model predicts blood pressure, blood flow and hematocrit distributions, as well as volumes of functional vascular territories, and regional flow at voxel and network scales. First, the influence of the prescribed boundary conditions (BCs) on the baseline flow structure is investigated, highlighting relevant lower- and upper-bound BCs. Independent of these BCs, large heterogeneities of baseline flow from vessel to vessel and from voxel to voxel, are demonstrated. These heterogeneities are controlled by the architecture of the intra-cortical vascular network. In particular, a correlation between the blood flow and the proportion of vascular volume occupied by arterioles or venules, at voxel scale, is highlighted. Then, the extent of venous contamination downstream to the sites of neuronal activation is investigated, demonstrating a linear relationship between the catchment surface of the activated area and the diameter of the intra-cortical draining vein.
机译:基于血液动力学的功能性神经影像学技术,例如BOLD fMRI和PET,提供了神经元活动的间接测量。神经元活动与所测信号之间的定量关系尚不清楚,关于它们的代谢和血液动力学成分的相对贡献尚不确定。经验观察已经证明了后者的重要性,并暗示微血管解剖学具有潜在的影响。用于微血管脑网络分析的3D计算机辅助方法的最新发展已经产生了有关人类大脑皮层微循环的大型定量库(Cassot et al。,2006),可用于研究脑血管的血液动力学成分通过流体动力学建模激活大脑。为此,我们使用一维非线性模型,考虑了微循环中血流的复杂流变特性,在解剖学上精确的大型人类皮层内血管网络(约10000个片段)中执行了血流的首次模拟。该模型可预测血压,血流量和血细胞比容分布,以及功能性血管区域的体积以及体素和网络规模的区域流量。首先,研究了规定的边界条件(BCs)对基线流量结构的影响,突出了相关的上下边界BCs。不受这些BC的影响,显示了从血管到血管以及从体素到体素的基线流动的较大异质性。这些异质性由皮质内血管网络的结构控制。特别地,在体素标度上,突出显示了血流与小动脉或小静脉占据的血管体积比例之间的相关性。然后,研究了神经元激活部位下游的静脉污染程度,证明了激活区域的集水表面与皮质内引流静脉的直径之间存在线性关系。

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