Prabhakarpandian Balabhaskar, Pant Kapil, Scott Robert C, Pattillo Christopher B, Irimia Daniel, Kiani Mohammad F, Sundaram Shivshankar
Biomedical Technology, CFD Research Corporation, 215 Wynn Dr., Huntsville, AL 35805, USA.
Biomed Microdevices. 2008 Aug;10(4):585-95. doi: 10.1007/s10544-008-9170-y.
We have developed a methodology to study particle adhesion in the microvascular environment using microfluidic, image-derived microvascular networks on a chip accompanied by Computational Fluid Dynamics (CFD) analysis of fluid flow and particle adhesion. Microfluidic networks, obtained from digitization of in vivo microvascular topology were prototyped using soft-lithography techniques to obtain semicircular cross sectional microvascular networks in polydimethylsiloxane (PDMS). Dye perfusion studies indicated the presence of well-perfused as well as stagnant regions in a given network. Furthermore, microparticle adhesion to antibody coated networks was found to be spatially non-uniform as well. These findings were broadly corroborated in the CFD analyses. Detailed information on shear rates and particle fluxes in the entire network, obtained from the CFD models, were used to show global adhesion trends to be qualitatively consistent with current knowledge obtained using flow chambers. However, in comparison with a flow chamber, this method represents and incorporates elements of size and complex morphology of the microvasculature. Particle adhesion was found to be significantly localized near the bifurcations in comparison with the straight sections over the entire network, an effect not observable with flow chambers. In addition, the microvascular network chips are resource effective by providing data on particle adhesion over physiologically relevant shear range from even a single experiment. The microfluidic microvascular networks developed in this study can be readily used to gain fundamental insights into the processes leading to particle adhesion in the microvasculature.
我们开发了一种方法，用于研究微血管环境中的颗粒黏附，该方法使用芯片上基于图像衍生的微流控微血管网络，并结合流体流动和颗粒黏附的计算流体动力学（CFD）分析。通过对体内微血管拓扑结构进行数字化处理获得微流控网络，利用软光刻技术制作原型，以在聚二甲基硅氧烷（PDMS）中获得半圆形横截面的微血管网络。染料灌注研究表明，在给定网络中存在灌注良好以及停滞的区域。此外，还发现微粒对抗体包被网络的黏附在空间上也是不均匀的。这些发现得到了CFD分析的广泛证实。从CFD模型中获得的关于整个网络中剪切速率和颗粒通量的详细信息，用于表明总体黏附趋势在定性上与使用流动腔获得的现有知识一致。然而，与流动腔相比，该方法体现并纳入了微血管的尺寸和复杂形态等要素。与整个网络中的直管段相比，发现在分支附近颗粒黏附明显局部化，这是流动腔中无法观察到的效应。此外，微血管网络芯片通过从单个实验中提供生理相关剪切范围内的颗粒黏附数据，具有资源高效性。本研究中开发的微流控微血管网络可很容易地用于深入了解导致微血管中颗粒黏附的过程。
