Hydraulic resistance of three-dimensional pial perivascular spaces in the brain.
Hydraulic resistance of three-dimensional pial perivascular spaces in the brain.
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DOI：
10.1186/s12987-023-00505-5
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发表时间：
2024-01-11
影响因子：
7.3
通讯作者：
Thomas, John H.
中科院分区：
文献类型：
--
作者：
Boster, Kimberly A. S.;Sun, Jiatong;Shang, Jessica K.;Kelley, Douglas H.;Thomas, John H.
关键词：
血管周围间隙（PVS）在大脑周围携带脑脊液（CSF），促进健康废物的清除。在体内测量这些流量是困难的，而且往往是不可能的，因为PVS很小，所以准确的建模对于理解脑清除率至关重要。在PVS中建模流动的最重要参数是其液压阻力，定义为压降与体积流量的比率，其取决于其尺寸和形状。特别地，每单位长度的局部电阻沿着PVS变化，并且取决于局部横截面的变化。使用小鼠软脑膜PVS的分段三维图像，我们进行流体动力学模拟以计算每单位长度的阻力。我们应用扩展的润滑理论来阐明计算的阻力和假设均匀流动的预期阻力之间的差异。我们测试了四种不同的近似方法和一种新的校正因子，以确定如何以低计算成本准确估计每单位长度的电阻。为了评估假设单向流动的影响，我们还考虑了横截面积沿其长度沿着正弦变化的圆形管道。我们发现，建模PVS作为一系列的短管道均匀流动，并在每个数值求解的流量，在低成本下产生良好的阻力估计。如果面积相对于轴向位置的二阶导数小于2，则误差通常小于15%，并且可以通过我们的校正因子进一步减小。为了以更低的成本进行估计，我们发现，圆形管道的众所周知的阻力可以通过形状因子来缩放，而不是数值求解阻力。只要截面的纵横比小于0.7，附加误差小于10%。忽略离轴速度分量会低估平均阻力，但可以通过简单的校正因子来减小误差。这些结果可以提高未来全脑和局部CSF流动模型的准确性，从而更好地预测清除率，例如，随着年龄，大脑状态和病理条件的变化而变化。
Perivascular spaces (PVSs) carry cerebrospinal fluid (CSF) around the brain, facilitating healthy waste clearance. Measuring those flows in vivo is difficult, and often impossible, because PVSs are small, so accurate modeling is essential for understanding brain clearance. The most important parameter for modeling flow in a PVS is its hydraulic resistance, defined as the ratio of pressure drop to volume flow rate, which depends on its size and shape. In particular, the local resistance per unit length varies along a PVS and depends on variations in the local cross section. Using segmented, three-dimensional images of pial PVSs in mice, we performed fluid dynamical simulations to calculate the resistance per unit length. We applied extended lubrication theory to elucidate the difference between the calculated resistance and the expected resistance assuming a uniform flow. We tested four different approximation methods, and a novel correction factor to determine how to accurately estimate resistance per unit length with low computational cost. To assess the impact of assuming unidirectional flow, we also considered a circular duct whose cross-sectional area varied sinusoidally along its length. We found that modeling a PVS as a series of short ducts with uniform flow, and numerically solving for the flow in each, yields good resistance estimates at low cost. If the second derivative of area with respect to axial location is less than 2, error is typically less than 15%, and can be reduced further with our correction factor. To make estimates with even lower cost, we found that instead of solving for the resistance numerically, the well-known resistance of a circular duct could be scaled by a shape factor. As long as the aspect ratio of the cross section was less than 0.7, the additional error was less than 10%. Neglecting off-axis velocity components underestimates the average resistance, but the error can be reduced with a simple correction factor. These results could increase the accuracy of future models of brain-wide and local CSF flow, enabling better prediction of clearance, for example, as it varies with age, brain state, and pathological conditions.
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影响因子：
5.8
作者：
Bohr, Tomas;Hjorth, Poul G.;Holst, Sebastian C.;Hrabetova, Sabina;Kiviniemi, Vesa;Lilius, Tuomas;Lundgaard, Iben;Mardal, Kent-Andre;Martens, Erik A.;Mori, Yuki;Nagerl, U. Valentin;Nicholson, Charles;Tannenbaum, Allen;Thomas, John H.;Tithof, Jeffrey;Benveniste, Helene;Iliff, Jeffrey J.;Kelley, Douglas H.;Nedergaard, Maiken
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Nedergaard, Maiken
影响因子：
3.9
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通讯作者：
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影响因子：
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影响因子：
17.1
作者：
Iliff JJ;Wang M;Liao Y;Plogg BA;Peng W;Gundersen GA;Benveniste H;Vates GE;Deane R;Goldman SA;Nagelhus EA;Nedergaard M
通讯作者：
Nedergaard M
影响因子：
3.9
作者：
Rivas, Fatima Min;Liu, Jia;Kelley, Douglas H.
通讯作者：
Kelley, Douglas H.