Pabna University of Science and Technology, Pabna, 6600, Bangladesh.
Research Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University, Kita 20, Nishi 10, Kita-ku, Sapporo, 001-0020, Japan.
Sci Rep. 2023 Aug 2;13(1):12566. doi: 10.1038/s41598-023-39635-z.
Collective migration of cells is a fundamental behavior in biology. For the quantitative understanding of collective cell migration, live-cell imaging techniques have been used using e.g., phase contrast or fluorescence images. Particle tracking velocimetry (PTV) is a common recipe to quantify cell motility with those image data. However, the precise tracking of cells is not always feasible. Particle image velocimetry (PIV) is an alternative to PTV, corresponding to Eulerian picture of fluid dynamics, which derives the average velocity vector of an aggregate of cells. However, the accuracy of PIV in capturing the underlying cell motility and what values of the parameters should be chosen is not necessarily well characterized, especially for cells that do not adhere to a viscous flow. Here, we investigate the accuracy of PIV by generating images of simulated cells by the Vicsek model using trajectory data of agents at different noise levels. It was found, using an alignment score, that the direction of the PIV vectors coincides with the direction of nearby agents with appropriate choices of PIV parameters. PIV is found to accurately measure the underlying motion of individual agents for a wide range of noise level, and its condition is addressed.
细胞的集体迁移是生物学中的一种基本行为。为了定量理解集体细胞迁移，人们使用了活细胞成像技术，例如相差或荧光图像。粒子跟踪测速（PTV）是一种常用的方法，可以使用这些图像数据来量化细胞的迁移率。然而，精确跟踪细胞并不总是可行的。粒子图像测速（PIV）是 PTV 的一种替代方法，对应于流体动力学的欧拉图像，它可以得出细胞聚集体的平均速度矢量。然而，PIV 在捕捉潜在细胞迁移率方面的准确性以及应该选择哪些参数值并不一定得到很好的描述，特别是对于那些不粘附于粘性流的细胞。在这里，我们通过使用不同噪声水平下的代理轨迹数据生成模拟细胞的 Vicsek 模型图像，来研究 PIV 的准确性。我们发现，使用对齐分数，在适当选择 PIV 参数的情况下，PIV 矢量的方向与附近代理的方向一致。研究发现，PIV 可以在很宽的噪声水平范围内准确地测量单个代理的基础运动，并且解决了其条件问题。
