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Using Image Attributes to Assure Accurate Particle Size and Count Using Nanoparticle Tracking Analysis



Adrian P. Defante, Wyatt N. Vreeland, Kurt D. Benkstein, Dean C. Ripple


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. These settings are recommended by the instrument manufacturer or determined through trial and error from an experienced operator to track However, the validity of these settings is hard to assess. 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. The pixel area from the scattered light captured by the camera from an illuminated particle can be correlated with particle counts using open source software analysis. A median pixel area, 4 pixels2, 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.
Journal of Pharmaceutical Sciences


nanoparticles, analysis, light scattering, particle sizing, physical characterization


Defante, A. , Vreeland, W. , Benkstein, K. and Ripple, D. (2017), Using Image Attributes to Assure Accurate Particle Size and Count Using Nanoparticle Tracking Analysis, Journal of Pharmaceutical Sciences, [online], (Accessed April 23, 2024)
Created December 23, 2017, Updated April 19, 2020