HoloMonitor M4: holographic imaging cytometer for real-time kinetic label-free live-cell analysis of adherent cells

Sebesta, Mikael; Egelberg, Peter; Langberg, Anders; Lindskov, Jens-Henrik; Alm, Kersti; Janicke, Birgit

doi:10.1117/12.2216731

Cited by 19 publications

(29 citation statements)

References 7 publications

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“…QPI has been used as the basis for reporting on cell proliferation, morphology, and motility (reviewed in Ref. Although many of these studies utilized customized set-ups, culture conditions and analytics, their success has resulted in the development of commercially available "plug and play" QPI platforms (23). More recent reports have used machine learning based analyses of features derived from QPI images to distinguish metastatic potential, drug-response, program activation, and modes of cellular migration (17)(18)(19)(20)(21)(22).…”

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confidence: 99%

“…Collectively, these and other reports have fully established QPI platforms as quantitative time-lapse cytometers with single cell resolution. Although many of these studies utilized customized set-ups, culture conditions and analytics, their success has resulted in the development of commercially available "plug and play" QPI platforms (23). Some of these cytometers can be housed fully in mammalian cell incubators and image a large assortment of common culture plates or medias, enabling the possibility of non-invasive and non-interruptive cell motility analysis during routine culture.…”

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confidence: 99%

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Evaluation of holographic imaging cytometer holomonitor M4® motility applications

Zhang

Judson

2018

Cytometry Pt A

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Digital holographic cytometry (DHC) and other methods of quantitative phase imaging permit extended time-lapse imaging of mammalian cells in the absence of induced cellular toxicity. Manufactured DHC platforms equipped with semi-automated image acquisition, segmentation, and analysis software packages (or modules) for assessing cell behavior are now commercially available. When housed in mammalian cell incubators these cytometers offer the potential to monitor and quantify a range of cellular behaviors without disrupting routine culture. Realization of this potential requires validation against established standards. Two proprietary software modules for assessing cellular motility available using the HoloMonitor M4 DHC platform were evaluated on human melanoma cells lines with known relative motility and metastatic potential. One such software package, the Track Cells module, was run during routine culture. In addition, the Wound Healing module was conducted in parallel with established transwell migration and invasion assays. Each module was evaluated for reproducibility and correlation to established assays. Both software modules reliably recorded increased cellular motility in the metastatic 1205Lu line as compared with the non-metastatic WM793 line. In a direct comparison of the two propriety DHC software modules and two established transwell assays, the relative cell motilities were well correlated. The granularity of data provided by the Track Cells module permitted the additional identification of rare hyper-motile cells in the metastatic population and the distinction of motility from division associated displacement. The two HoloMonitor M4 DHC proprietary software modules for assessing cellular motility yielded reproducible results that were well-correlated with established standards.

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confidence: 99%

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confidence: 99%

Evaluation of holographic imaging cytometer holomonitor M4® motility applications

Zhang

Judson

2018

Cytometry Pt A

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“…Holograms were captured using a HoloMonitor M4 DHC system 38 and acquired every hour to observe all cell divisions in the non-treated conditions. The holograms were processed computationally using HStudio to produce an intensity image representing a quantitative map of light-wave phase shifts 38 – 40 . Individual cellular events were segmented and tracked from the resulting phase shift images.…”

Section: Resultsmentioning

confidence: 99%

High accuracy label-free classification of kinetic cell states from holographic cytometry

Hejna

Jorapur

Song

et al. 2017

Preprint

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Abstract:Digital holographic microscopy permits live and label-free visualization of adherent cells. Here we report the application of this approach for high accuracy kinetic quantitative cytometry. We identify twenty-six label-free optical and morphological features that are biologically independent. When used as a basis for machine learning, these features allow blind single cell classification with up to 95% accuracy. We present methods to control for inherent holographic noise, thereby establishing a set of reliable quantitative features. Together, these contributions permit continuous digital holographic cytometry for three or more days. Applying our approach to human melanoma cells treated with a panel of cancer therapeutics, we can track the response of each cell, simultaneously classifying multiple behaviors such as cell cycle length, motility, apoptosis, senescence, and heterogeneity of response to each therapeutic. Importantly, we demonstrate relationships between these phenotypes over time. This work thus provides an experimental and computational roadmap for low cost live-cell imaging and kinetic classification of heterogeneous adherent cell populations. Introduction:

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“…The current method directly counts cell numbers and quantitatively analyzes cell area and SI changes of individual cells studied, thereby providing the opportunity to investigate real-time cell responses to therapies, including effects on mitotic phases, without requiring labeling reagents or additional devices (18,29,36). Besides cell area and SI changes, more advanced data processing, such as machine learning algorithms (30) will also be useful to precisely identify cell cycle stages, especially for the interphase G1, G2, and S.…”

Section: Discussionmentioning

confidence: 99%

“…The quantitative signal intensity (SI) of QPI images allows for the direct observation of specific cell cycle events without requiring labeling (18,29,30). As shown in Figures 3A and 3C, the metaphase plate could be observed clearly as an intense line at the center of the nucleus, where the chromosome condensed and aligned.…”

Section: Cell Cycle Stagesmentioning

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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HoloMonitor M4: holographic imaging cytometer for real-time kinetic label-free live-cell analysis of adherent cells

Cited by 19 publications

References 7 publications

Evaluation of holographic imaging cytometer holomonitor M4® motility applications

Evaluation of holographic imaging cytometer holomonitor M4® motility applications

High accuracy label-free classification of kinetic cell states from holographic cytometry

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

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