Characterising live cell behaviour: Traditional label-free and quantitative phase imaging approaches

Kasprowicz, Richard; Suman, Rakesh; O’Toole, Peter

doi:10.1016/j.biocel.2017.01.004

Cited by 94 publications

(97 citation statements)

References 44 publications

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“…Indeed, there is a range of growth and proliferation rates in all cell lines measured. The growth and proliferation rate is one example of a unique QPI measurement that takes into account the whole population rather than individual cells and in this case is represented as total dry mass over time [17] [ Figure 4H]. …”

Section: Resultsmentioning

confidence: 99%

“…The high contrast images generated by the system are label-free and exempt from focal drift, allowing extended time-lapse imaging [17][18][19] . The high-contrast nature of the images facilitates automated individual cell segmentation and tracking with the Cell Analysis Toolbox ® software, which outputs extensive and specific feature measurements for each cell.…”

Section: Image Capture Using Ptychography and Image Analysis Using Cementioning

confidence: 99%

See 1 more Smart Citation

Tumor heterogeneity and therapy resistance - implications for future treatments of prostate cancer

Frame¹,

Noble²,

Klein³

et al. 2017

JCMT

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Aim:To develop new therapies for prostate cancer, disease heterogeneity must be addressed. This includes patient variation, multi-focal disease, cellular heterogeneity, genomic changes and epigenetic modification. This requires more representative models to be used in more innovative ways. Methods: This study used a panel of cell lines and primary prostate epithelial cell cultures derived from patient tissue. Several assays were used; alamar blue, colony forming assays, γH2AX and Ki67 immunofluorescence and comet assays. Ptychographic quantitative phase imaging (QPI), a label-free imaging technique, combined with Cell Analysis Toolbox software, was implemented to carry out real-time analysis of cells and to retrieve morphological, kinetic and population data. Results: A combination of radiation and Vorinostat may be more effective than radiation alone. Primary prostate cancer stem-like cells are more resistant to etoposide than more differentiated cells. Analysis of QPI images showed that cell lines and primary cells differ in their size, motility and proliferation rate. A QPI signature was developed in order to identify two subpopulations of cells within a heterogeneous primary culture. Conclusion: Use of primary prostate epithelial cultures allows assessment of therapies whilst taking into account cellular heterogeneity. Analysis of rare cell populations and embracing novel techniques may ultimately lead to identifying and overcoming treatment resistance.

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Section: Resultsmentioning

confidence: 99%

Section: Image Capture Using Ptychography and Image Analysis Using Cementioning

confidence: 99%

Tumor heterogeneity and therapy resistance - implications for future treatments of prostate cancer

Frame¹,

Noble²,

Klein³

et al. 2017

JCMT

Self Cite

View full text Add to dashboard Cite

show abstract

“…Microscope techniques such as Light-Sheet-based Fluorescence Microscopy and Total Internal Reflection Fluorescence Microscopy limit the phototoxic effect (7,11). These attempts have, however, resulted in algorithms which are cell type specific or require a number of cell type specific parameters to be set by the operator (17). Phase contrast microscopy complements fluorescence microscopy by allowing cells to be imaged unaltered.…”

Section: Introductionmentioning

confidence: 99%

“…Several attempts have been made to automatically process phase contrast images to reliably count adherent cells directly in a cell culture vessel (12)(13)(14)(15)(16). These attempts have, however, resulted in algorithms which are cell type specific or require a number of cell type specific parameters to be set by the operator (17). In the future, software based on deep learning will make image analysis easier for all types of images (18).…”

Section: Introductionmentioning

confidence: 99%

Label‐free high temporal resolution assessment of cell proliferation using digital holographic microscopy

Janicke¹,

Kårsnäs²,

Egelberg³

et al. 2017

Cytometry Pt A

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Cell proliferation assays are widely applied in biological sciences to understand the effect of drugs over time. However, current methods often assess cell population growth indirectly, that is, the cells are not actually counted. Instead other parameters, for example, the amount of protein, are determined. These methods often also demand phototoxic labels, have low temporal resolution, or employ end-point assays, and frequently are labor intensive. We have developed a robust and label-free kinetic cell proliferation assay with high temporal resolution for adherent cells using digital holographic microscopy (DHM), one of many quantitative phase microscopy techniques. As no labels or stains are required, and only very low intensity illumination is necessary, the technique allows for noninvasive continuous cell counting. Only two image processing settings were adjusted between cell lines, making the assay practical, user friendly, and free of user bias. The developed direct assay was validated by analyzing cell cultures treated with various concentrations of the anti-cancer drug etoposide, a well-established topoisomerase inhibitor that causes DNA damage and leads to programmed cell death. After treatment, the unstained adherent cells were nondestructively imaged every 30 min for 36 h inside a cell incubator. In the recorded time-lapse image sequences, individual cells were automatically identified to provide detailed growth curves and growth rate data of cell number, confluence, and average cell volume. Our results demonstrate how these parameters facilitate a deeper understanding of cell processes than what is achievable with current single-parameter and end-point methods. © 2017 International Society for Advancement of Cytometry.

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“…Recently, several label-free imaging techniques, including quantitative phase imaging (QPI), differential interference contrast (DIC) and phase contrast microsco-py, have been developed to characterize relevant cellular phenotypes (17)(18)(19)(20)(21). For example, cell responses to drug exposure have been investigated using QPI (22).…”

Section: Introductionmentioning

confidence: 99%

Characterization of dormant and active human cancer cells by quantitative phase imaging

2017

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The switch of tumor cells from a dormant, non-angiogenic phenotype to an active, angiogenic phenotype is a critical step in early cancer progression. To date, relatively little is known about the cellular behaviors of angiogenic and non-angiogenic tumor cell phenotypes. In this study, holographic imaging cytometry, a quantitative phase imaging (QPI) technique was used to continuously and non-invasively analyze, quantify, and compare a panel of fundamental cellular behaviors of angiogenic and non-angiogenic human osteosarcoma cells (KHOS) in a simple and economical way. Results revealed that angiogenic KHOS cells (KHOS-A) have significantly higher cell motility speeds than their non-angiogenic counterpart (KHOS-N) while no difference in their cell proliferation rates and cell cycle lengths were observed. KHOS-A cells were also found to have significantly smaller cell areas and greater cell optical thicknesses when compared with the non-angiogenic KHOS-N cells. No difference in average cell volumes was observed. These studies demonstrate that the morphology and behavior of angiogenic and non-angiogenic cells can be continuously, efficiently, and non-invasively monitored using a simple, quantitative, and economical system that does not require tedious and time-consuming assays to provide useful information about tumor dormancy. © 2017 International Society for Advancement of Cytometry.

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Characterising live cell behaviour: Traditional label-free and quantitative phase imaging approaches

Cited by 94 publications

References 44 publications

Tumor heterogeneity and therapy resistance - implications for future treatments of prostate cancer

Tumor heterogeneity and therapy resistance - implications for future treatments of prostate cancer

Label‐free high temporal resolution assessment of cell proliferation using digital holographic microscopy

Characterization of dormant and active human cancer cells by quantitative phase imaging

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