MobilityAnalyser: A novel approach for automatic quantification of cell mobility on periodic patterned substrates using brightfield microscopy images
•Automatic removal of periodic background patterns in brightfield microscopy images.•Effective at removing the patterns and performing cell detection and tracking.•Faster tracking with results of cell trajectory, distance, velocity and persistence.•Provides key parameters of cell mobility as a respo...
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Veröffentlicht in: | Computer methods and programs in biomedicine 2018-08, Vol.162, p.61-67 |
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Zusammenfassung: | •Automatic removal of periodic background patterns in brightfield microscopy images.•Effective at removing the patterns and performing cell detection and tracking.•Faster tracking with results of cell trajectory, distance, velocity and persistence.•Provides key parameters of cell mobility as a response to surface topography.
Surface topography of biomaterials has been shown to have an effect on cells behaviour. Cell-material interactions can be visually characterized by assessing both cell shape and spreading at initial time-points and, its migration patterns, as a response to the underlying topography. Whilst many have reported the study of cell migration and shape with fluorescence labelling, the focus on evaluating cells response to surface topography is to observe, under real-time conditions, interactions between cells and surfaces. In this manuscript we present a novel approach to automatically detect and remove periodic background patterns in brightfield microscopy images in order to perform automatic cell mobility analysis.
The developed software, MobilityAnalyser, performs automatic tracking of unmarked cells and allows the user to manually correct any incorrectly detected or tracked cell. Human Mesenchymal Stem Cells (hMSCs) trajectory, migration distance, velocity and persistence were evaluated over line and pillar micropatterned SiO2 films and on a flat SiO2 control substrate.
The developed software proved to be effective in automatically removing background patterns of both line and pillar shapes and in performing cell detection and tracking. MobilityAnalyser accurately measured cell mobility in a fraction of the time required for manual analysis and eliminated user subjectivity.
The results obtained with the software confirmed how different topographies affect cell trajectory, migration pathways and velocities, with a statistically significant increase for micropatterned surfaces, when compared with the flat control. The persistence parameter also proved the influence of both patterns on the directionality of cell movement.
MobilityAnalyser is an automatic tool that removes periodic background patterns, detects and tracks cells, and provides cell mobility parameters that characterize the response of cells to different surface topographies. The software is freely available at: https://drive.google.com/open?id=1Fbb321ogLD19SlRjceMETNUqDHgpeBPl. |
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ISSN: | 0169-2607 1872-7565 |
DOI: | 10.1016/j.cmpb.2018.05.003 |