ArticleFEBS open bio2017
Evaluation of the metastatic potential of malignant cells by image processing of digital holographic microscopy data.
Article in FEBS open bio, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Label-Free Cancer Detection Methods Based on Biophysical Cell Phenotypes.Bioengineering (Basel, Switzerland) · 2025Review
- Article
- Digital holographic microscopy evaluation of dynamic cell response to electroporation.Biomedical optics express · 2021Article
- Quantitative scoring of epithelial and mesenchymal qualities of cancer cells using machine learning and quantitative phase imaging.Journal of biomedical optics · 2020Article
- Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2019Article
- Quantitative phase imaging unravels new insight into dynamics of mesenchymal and amoeboid cancer cell invasion.Scientific reports · 2018Article
- Optophysiology of cardiomyocytes: characterizing cellular motion with quantitative phase imaging.Biomedical optics express · 2017Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The cell refractive index has been proposed as a putative cancer biomarker of great potential, being correlated with cell content and morphology, cell division rate and membrane permeability. We used digital holographic microscopy to compare the refractive index and dry mass density of two B16 murine melanoma sublines of different metastatic potential. Using statistical methods, the distribution of phase shifts within the reconstructed quantitative phase images was analyzed by the method of bimodality coefficients. The observed correlation of refractive index, dry mass density and bimodality profile with the metastatic potential of the cells was validated by real time impedance-based assay and clonogenic tests. We suggest that the refractive index and bimodality analysis of quantitative phase image histograms could be developed as optical biomarkers useful in label-free detection and quantitative evaluation of cell metastatic potential.
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Registered trials
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