4.5 Article

Label-free dynamic segmentation and morphological analysis of subcellular optical scatterers

Journal

JOURNAL OF BIOMEDICAL OPTICS
Volume 23, Issue 9, Pages -

Publisher

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
DOI: 10.1117/1.JBO.23.9.096004

Keywords

optical scatter imaging; label-free; mitochondrial rounding; digital image processing; texture feature

Funding

  1. New Jersey Commission on Brain Injury Research [CBIR14PIL005]
  2. NSF [CBET1512170]

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Imaging without fluorescent protein labels or dyes presents significant advantages for studying living cells without confounding staining artifacts and with minimal sample preparation. Here, we combine label-free optical scatter imaging with digital segmentation and processing to create dynamic subcellular masks, which highlight significantly scattering objects within the cells' cytoplasms. The technique is tested by quantifying organelle morphology and redistribution during cell injury induced by calcium overload. Objects within the subcellular mask are first analyzed individually. We show that the objects' aspect ratio and degree of orientation (orientedness) decrease in response to calcium overload, while they remain unchanged in untreated control cells. These changes are concurrent with mitochondrial fission and rounding observed by fluorescence, and are consistent with our previously published data demonstrating scattering changes associated with mitochondrial rounding during calcium injury. In addition, we show that the magnitude of the textural features associated with the spatial distribution of the masked objects' orientedness values, changes by more than 30% in the calcium-treated cells compared with no change or changes of less than 10% in untreated controls, reflecting dynamic changes in the overall spatial distribution and arrangement of subcellular scatterers in response to injury. Taken together, our results suggest that our method successfully provides label-free morphological signatures associated with cellular injury. Thus, we propose that dynamically segmenting and analyzing the morphology and organizational patterns of subcellular scatterers as a function of time can be utilized to quantify changes in a given cellular condition or state. (C) The Authors.

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