Generalized cell morphological parameters based on interferometric phase microscopy and their application to cell life cycle characterization

Girshovitz, Pinhas; Shaked, Natan T.

doi:10.1364/boe.3.001757

Cited by 183 publications

(135 citation statements)

References 27 publications

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“…The ability to measure cell count was validated for the first time in 2008 by Mölder et al [21], using human breast and prostate cancer cell lines, as well as a mouse fibroblast cell line. Measurement of cell growth has been well documented for both adherent and non-adherent cells [8,9,15,[25][26][27][28]47,49,56,59,61]. By segmentation of cellular outlines, morphology and motility can also be studied [7,50,51,57,80].…”

Section: Principles Of Qpimentioning

confidence: 99%

“…Cell death and cell proliferation are stringently controlled by the cell cycle, and studies have shown the ability of QPI to identify the different phases of the cell life cycle, i.e., specific changes in cell phase correlating to either a G1 or a G2/M arrest [13,25,38,44,57,89]. Kamlund et al constructed individual cell trees showing the way in which the drug salinomycin affects individual cells cultured in normoxia or hypoxia, by monitoring the times to first and last division [13].…”

Section: Cell Death Studies With Qpimentioning

confidence: 99%

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Quantitative Phase Imaging for Label-Free Analysis of Cancer Cells—Focus on Digital Holographic Microscopy

2018

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Abstract:To understand complex biological processes, scientists must gain insight into the function of individual living cells. In contrast to the imaging of fixed cells, where a single snapshot of the cell's life is retrieved, live-cell imaging allows investigation of the dynamic processes underlying the function and morphology of cells. Label-free imaging of living cells is advantageous since it is used without fluorescent probes and maintains an appropriate environment for cellular behavior, otherwise leading to phototoxicity and photo bleaching. Quantitative phase imaging (QPI) is an ideal method for studying live cell dynamics by providing data from noninvasive monitoring over arbitrary time scales. The effect of drugs on migration, proliferation, and apoptosis of cancer cells are emerging fields suitable for QPI analysis. In this review, we provide a current insight into QPI applied to cancer research.

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Section: Principles Of Qpimentioning

confidence: 99%

Section: Cell Death Studies With Qpimentioning

confidence: 99%

Quantitative Phase Imaging for Label-Free Analysis of Cancer Cells—Focus on Digital Holographic Microscopy

2018

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“…33 It has been shown that the measured phase in the image corresponds to the dry mass density distribution within the cell. 26,27 In contrast to existing DHM techniques, 4,7,18,19 the use of incoherent illumination enables high-quality quantitative phase imaging with strong suppression of coherent noise and parasitic interferences while providing high temporal stability and spatial uniformity of the phase measurement. 25 Using the approach described in Ref.…”

Section: Image Acquisitionmentioning

confidence: 99%

“…Cell life cycle characterization by monitoring of morphometric (MO) and quantitative phase features was proposed in Ref. 18. Assessment of wound healing by monitoring the cellular volume, dry mass, and refractive index was presented in Ref.…”

Section: Introductionmentioning

confidence: 99%

Automated classification of cell morphology by coherence-controlled holographic microscopy

et al. 2017

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Abstract. In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherencecontrolled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.

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“…Similar multiparameter approaches have been previously utilized to characterize phase distortions in tissue sections, 14 red blood cells, 24 phase fluctuations observed in waves transmitted through cells, 16 and in the context of monitoring the cell cycle through phase-derived parameters. 25 Our approach is the first to investigate the interdependence of these parameters.…”

Section: Introductionmentioning

confidence: 99%

Network signatures of nuclear and cytoplasmic density alterations in a model of pre and postmetastatic colorectal cancer

et al. 2014

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Abstract. Cells contributing to the pathogenesis of cancer possess cytoplasmic and nuclear structural alterations that accompany their aberrant genetic, epigenetic, and molecular perturbations. Although it is known that architectural changes in primary and metastatic tumor cells can be quantified through variations in cellular density at the nanometer and micrometer spatial scales, the interdependent relationships among nuclear and cytoplasmic density as a function of tumorigenic potential has not been thoroughly investigated. We present a combined optical approach utilizing quantitative phase microscopy and partial wave spectroscopic microscopy to perform parallel structural characterizations of cellular architecture. Using the isogenic SW480 and SW620 cell lines as a model of pre and postmetastatic transition in colorectal cancer, we demonstrate that nuclear and cytoplasmic nanoscale disorder, micron-scale dry mass content, mean dry mass density, and shape metrics of the dry mass density histogram are uniquely correlated within and across different cellular compartments for a given cell type. The correlations of these physical parameters can be interpreted as networks whose nodal importance and level of connection independence differ according to disease stage. This work demonstrates how optically derived biophysical parameters are linked within and across different cellular compartments during the architectural orchestration of the metastatic phenotype.

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Generalized cell morphological parameters based on interferometric phase microscopy and their application to cell life cycle characterization

Cited by 183 publications

References 27 publications

Quantitative Phase Imaging for Label-Free Analysis of Cancer Cells—Focus on Digital Holographic Microscopy

Quantitative Phase Imaging for Label-Free Analysis of Cancer Cells—Focus on Digital Holographic Microscopy

Automated classification of cell morphology by coherence-controlled holographic microscopy

Network signatures of nuclear and cytoplasmic density alterations in a model of pre and postmetastatic colorectal cancer

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