Dynamic cell-mass movement analyses tool

Abstract

Background and Objective: Digital Holographic Microscopy provides a new kind of quantitative image data about live cells’ in vitro activities. Apart from non-invasive and staining-free imaging, it offers topological weighting of cell mass. This led us to develop a particular tool for assessing cell mass dynamics. Methods: Programming language Python and a training set of time-lapse images of adherent HT-1080 cells derived from human fibrosarcoma taken with dry objective 40x/0.95 at 30-second intervals were used to create the Analytical Image Differencing (AID) method. Results: The AID makes the best of these new data by evaluating the difference between the chosen two quantitative phase images from the time-lapse series. The contribution of the method is demonstrated on hiQPI (Holographic Incoherent-light-source Quantitative Phase Imaging) image data taken with a Q-phase microscope. The analysis outputs are graphical and complemented with numerical data. To underscore the significance of the Analytical Image Differencing (AID) method, an initial pilot experiment was conducted to show the available analyses of sequential overlapping images capturing the movement of cancer cells. Notably, besides defining changes in areas used by the cell (newly or steadily occupied or better abandoned) it is an introduction to the zero-line concept, which denotes spots of tranquility among continuously moving surroundings. Conclusions: The measurement of zero-line length has emerged as a novel biomarker for characterizing cell mass transfer. The sensitivity of phase change measurements is demonstrated. The noise quality of input images obtained with incoherent (hiQPI) and coherent (QPI) methods is compared. The resulting effect on the AID method output is also shown. The findings of this study introduce a novel approach to evaluating cellular behavior in vitro. The concept emerged as a particularly noteworthy outcome. Collectively, these results highlight the substantial potential of AID in advancing the field of cancer cells biology, particularly.

Background and Objective: Digital Holographic Microscopy provides a new kind of quantitative image data about live cells’ in vitro activities. Apart from non-invasive and staining-free imaging, it offers topological weighting of cell mass. This led us to develop a particular tool for assessing cell mass dynamics. Methods: Programming language Python and a training set of time-lapse images of adherent HT-1080 cells derived from human fibrosarcoma taken with dry objective 40x/0.95 at 30-second intervals were used to create the Analytical Image Differencing (AID) method. Results: The AID makes the best of these new data by evaluating the difference between the chosen two quantitative phase images from the time-lapse series. The contribution of the method is demonstrated on hiQPI (Holographic Incoherent-light-source Quantitative Phase Imaging) image data taken with a Q-phase microscope. The analysis outputs are graphical and complemented with numerical data. To underscore the significance of the Analytical Image Differencing (AID) method, an initial pilot experiment was conducted to show the available analyses of sequential overlapping images capturing the movement of cancer cells. Notably, besides defining changes in areas used by the cell (newly or steadily occupied or better abandoned) it is an introduction to the zero-line concept, which denotes spots of tranquility among continuously moving surroundings. Conclusions: The measurement of zero-line length has emerged as a novel biomarker for characterizing cell mass transfer. The sensitivity of phase change measurements is demonstrated. The noise quality of input images obtained with incoherent (hiQPI) and coherent (QPI) methods is compared. The resulting effect on the AID method output is also shown. The findings of this study introduce a novel approach to evaluating cellular behavior in vitro. The concept emerged as a particularly noteworthy outcome. Collectively, these results highlight the substantial potential of AID in advancing the field of cancer cells biology, particularly.