Quantitative Phase Imaging Modality Research Articles

High-resolution cell imaging using white light phase shifting interferometry and iterative phase deconvolution.

An optimization algorithm is presented for the deconvolution of a complex field to improve the resolution and accuracy of quantitative phase imaging (QPI). A high-resolution phase map can be recovered by solving a constrained optimization problem of deconvolution using a complex gradient operator. The method is demonstrated on phase measurements of samples using a white light based phase shifting interferometry (WLPSI) method. The application of the algorithm on real and simulated objects shows a significant resolution and contrast improvement. Experiments performed on Escherichia coli bacterium have revealed its sub-cellular structures that were not visible in the raw WLPSI images obtained using a five phase shifting method. These features can give valuable insights into the structures and functioning of biological cells. The algorithm is simple in implementation and can be incorporated into other QPI modalities .

Multi‐ATOM: Ultrahigh‐throughput single‐cell quantitative phase imaging with subcellular resolution

A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost‐effective and label‐free cellular assays, which provides useful insights into understanding the biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single‐cell precision to define cell identities in a large and heterogeneous population of cells—hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multiplexed asymmetric‐detection time‐stretch optical microscopy (multi‐ATOM) that captures and processes quantitative label‐free single‐cell images at ultrahigh throughput without compromising subcellular resolution. We show that multi‐ATOM, based upon ultrafast phase‐gradient encoding, outperforms state‐of‐the‐art QPI in permitting robust phase retrieval at a QPI throughput of >10 000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi‐ATOM for large‐scale, label‐free, multivariate, cell‐type classification (e.g. breast cancer subtypes, and leukemic cells vs peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi‐ATOM could empower new strategies in large‐scale biophysical single‐cell analysis with applications in biology and enriching disease diagnostics.

Highly Sensitive Quantitative Imaging for Monitoring Single Cancer Cell Growth Kinetics and Drug Response

The detection and treatment of cancer has advanced significantly in the past several decades, with important improvements in our understanding of the fundamental molecular and genetic basis of the disease. Despite these advancements, drug-screening methodologies have remained essentially unchanged since the introduction of the in vitro human cell line screen in 1990. Although the existing methods provide information on the overall effects of compounds on cell viability, they are restricted by bulk measurements, large sample sizes, and lack capability to measure proliferation kinetics at the individual cell level. To truly understand the nature of cancer cell proliferation and to develop personalized adjuvant therapies, there is a need for new methodologies that provide quantitative information to monitor the effect of drugs on cell growth as well as morphological and phenotypic changes at the single cell level. Here we show that a quantitative phase imaging modality known as spatial light interference microscopy (SLIM) addresses these needs and provides additional advantages over existing proliferation assays. We demonstrate these capabilities through measurements on the effects of the hormone estradiol and the antiestrogen ICI182,780 (Faslodex) on the growth of MCF-7 breast cancer cells. Along with providing information on changes in the overall growth, SLIM provides additional biologically relevant information. For example, we find that exposure to estradiol results in rapidly growing cells with lower dry mass than the control population. Subsequently blocking the estrogen receptor with ICI results in slower growing cells, with lower dry masses than the control. This ability to measure changes in growth kinetics in response to environmental conditions provides new insight on growth regulation mechanisms. Our results establish the capabilities of SLIM as an advanced drug screening technology that provides information on changes in proliferation kinetics at the cellular level with greater sensitivity than any existing method.

Single-Bacterial Profiling and Identification Based on Quantitative Phase Imaging

Rapid identification of bacterial species is crucial in medicine and food hygiene. For instance, bacterial invasion-related syndromes such as sepsis, pneumonia, abscess, meningitis, gastroenteritis and food poisoning require rapid cures which are appropriate for the invaded bacterial species. However, conventional culture-based or molecular-assay technologies do not match this time requirement in general, mainly due to their limited sensitivity. Here, we present the potential of quantitative phase imaging (QPI) techniques (1) for identification of bacterial species at single bacterium level. Employment of various QPI modalities provides the corresponding biophysical and biochemical properties of the bacterial cell in a rapid and label-free manner. First, we employed anisotropic Fourier transform light scattering (2) and demonstrated that light scattering from individual bacterium reflects structural information sufficient for identification of rod-shaped species. Second, the potential of spectroscopic QPI (3, 4) for extracting chemical composition of the bacterium with sub-genus sensitivity is suggested.1. Lee, K., K. Kim, J. Jung, J. H. Heo, S. Cho, S. Lee, G. Chang, Y. J. Jo, H. Park, and Y. K. Park. 2013. Quantitative phase imaging techniques for the study of cell pathophysiology: from principles to applications. Sensors 13:4170-4191.2. Kim, Y., J. M. Higgins, R. R. Dasari, S. Suresh, and Y. K. Park. 2012. Anisotropic light scattering of individual sickle red blood cells. J. Biomed. Opt. 17:040501.3. Park, Y., T. Yamauchi, W. Choi, R. Dasari, and M. S. Feld. 2009. Spectroscopic phase microscopy for quantifying hemoglobin concentrations in intact red blood cells. Optics Letters 34:3668-3670.4. Jang, Y., J. Jang, and Y. Park. 2012. Dynamic spectroscopic phase microscopy for quantifying hemoglobin concentration and dynamic membrane fluctuation in red blood cells. Optics Express 20.