Bioprocess Measurements Group, National Institute of Standards and Technology, Gaithersburg, Maryland 20899.
Bioprocess Measurements Group, National Institute of Standards and Technology, Gaithersburg, Maryland 20899.
J Pharm Sci. 2018 May;107(5):1383-1391. doi: 10.1016/j.xphs.2017.12.016. Epub 2017 Dec 23.
Nanoparticle tracking analysis (NTA) obtains particle size by analysis of particle diffusion through a time series of micrographs and particle count by a count of imaged particles. The number of observed particles imaged is controlled by the scattering cross-section of the particles and by camera settings such as sensitivity and shutter speed. Appropriate camera settings are defined as those that image, track, and analyze a sufficient number of particles for statistical repeatability. Here, we test if image attributes, features captured within the image itself, can provide measurable guidelines to assess the accuracy for particle size and count measurements using NTA. The results show that particle sizing is a robust process independent of image attributes for model systems. However, particle count is sensitive to camera settings. Using open-source software analysis, it was found that a median pixel area, 4 pixels, results in a particle concentration within 20% of the expected value. The distribution of these illuminated pixel areas can also provide clues about the polydispersity of particle solutions prior to using a particle tracking analysis. Using the median pixel area serves as an operator-independent means to assess the quality of the NTA measurement for count.
纳米颗粒跟踪分析 (NTA) 通过分析颗粒在一系列显微镜图像中的扩散情况来获得颗粒大小，并通过对成像颗粒进行计数来获得颗粒数量。所成像的观察到的颗粒数量受到颗粒的散射截面以及相机设置（如灵敏度和快门速度）的控制。适当的相机设置是指那些可以成像、跟踪和分析足够数量的颗粒以实现统计可重复性的设置。在这里，我们测试了图像属性（图像本身所捕获的特征）是否可以提供可衡量的指南，以评估使用 NTA 进行粒径和计数测量的准确性。结果表明，对于模型系统，颗粒尺寸测量是一个独立于图像属性的稳健过程。然而，颗粒计数对相机设置敏感。使用开源软件分析，发现中位数像素面积为 4 像素时，颗粒浓度与预期值相差在 20%以内。这些照明像素区域的分布也可以为使用颗粒跟踪分析之前的颗粒溶液多分散性提供线索。使用中位数像素面积可以作为一种操作员独立的手段来评估计数的 NTA 测量质量。
