Characterizations and Correlations of Wall Shear Stress in Aneurysmal Flow
Characterizations and Correlations of Wall Shear Stress in Aneurysmal Flow
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DOI：
10.1115/1.4032056
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发表时间：
2016-01-01
影响因子：
1.7
通讯作者：
Shadden, Shawn C.
中科院分区：
文献类型：
--
作者：
Arzani, Amirhossein;Shadden, Shawn C.
壁面切应力（WSS）是研究最多的血流动力学参数之一，用于将血流与各种疾病相关联。血流的脉动性质，沿着患病动脉的复杂几何形状，产生复杂的时间和空间WSS模式。此外，WSS是一种载体，这进一步使其量化和解释复杂化。本研究的目的是调查复杂血流中WSS幅度、角度和矢量在空间和时间上的变化。选择腹主动脉瘤（AAA）作为探索WSS量化的背景。在6个AAA中进行了患者特异性计算流体动力学（CFD）模拟。引入了新的WSS参数，并探讨了这些参数与传统WSS参数之间的逐点相关性。WSS幅度与WSS幅度的时空梯度呈正相关。这激发了相对WSS梯度的定义。WSS向量梯度与幅度梯度高度相关。混合WSS的空间梯度和混合WSS的时间梯度，提出了同样占WSS的角度和幅度的变化，在单一的措施。WSS在调节近壁传输中发挥的重要作用，以及一些WSS参数之间的高度相关性，促使人们进一步关注WSS表征中使用的传统方法。
Wall shear stress (WSS) is one of the most studied hemodynamic parameters, used in correlating blood flow to various diseases. The pulsatile nature of blood flow, along with the complex geometries of diseased arteries, produces complicated temporal and spatial WSS patterns. Moreover, WSS is a vector, which further complicates its quantification and interpretation. The goal of this study is to investigate WSS magnitude, angle, and vector changes in space and time in complex blood flow. Abdominal aortic aneurysm (AAA) was chosen as a setting to explore WSS quantification. Patient-specific computational fluid dynamics (CFD) simulations were performed in six AAAs. New WSS parameters are introduced, and the pointwise correlation among these, and more traditional WSS parameters, was explored. WSS magnitude had positive correlation with spatial/ temporal gradients of WSS magnitude. This motivated the definition of relative WSS gradients. WSS vectorial gradients were highly correlated with magnitude gradients. A mix WSS spatial gradient and a mix WSS temporal gradient are proposed to equally account for variations in the WSS angle and magnitude in single measures. The important role that WSS plays in regulating near wall transport, and the high correlation among some of the WSS parameters motivates further attention in revisiting the traditional approaches used in WSS characterizations.