Practical application of microsphere samples for benchmarking a quantitative phase imaging system. Issue 10 (20th December 2020)

• Record Type: Journal Article
• Authors: Kwee, Edward; Peterson, Alexander; Halter, Michael; Elliott, John
• Is Part Of: Cytometry. Volume 99:Issue 10(2021)
• Page Start: 1022
• Page End: 1032
• Publication Date: 2020-12-20
• Subjects: HEK293 -- microspheres -- quantitative phase imaging -- reference materials; Flow cytometry -- Periodicals; Imaging systems in biology -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnostic imaging -- Periodicals; 571.605
• DOI: 10.1002/cyto.a.24291
• Languages: English
• ISSNs: 1552-4922

Abstract

Abstract: Quantitative phase imaging (QPI) provides an approach for monitoring the dry mass of individual cells by measuring the optical pathlength of visible light as it passes through cells. A distinct advantage of QPI is that the measurements result in optical path length quantities that are, in principle, instrument independent. Reference materials that induce a well‐defined optical pathlength shift and are compatible with QPI imaging systems will be valuable in assuring the accuracy of such measurements on different instruments. In this study, we evaluate seven combinations of microspheres embedded in index refraction matching media as candidate reference materials for benchmarking the performance of a QPI system and as calibration standards for the optical pathlength measurement. Poly(methyl metharylate) microspheres and mineral oil were used to evaluate the range of illumination apertures, signal‐to‐noise ratios, and focus positions that allow an accurate quantitative optical pathlength measurement. The microsphere‐based reference material can be used to verify settings on an instrument that are suitable for obtaining an accurate pathlength measurement from biological cells. The microsphere/media reference material is applied to QPI‐based dry mass measurements of a population of HEK293 cells to benchmark and provide evidence that the QPI image data are accurate.