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CLAUDE BOCCARA, OLIVIER THOUVENIN, Michel Paques, mathias fink, Jose Alain Sahel, Kate Grieve; Cell motility as FFOCT biomarker in primate and rodent retinal explants. Invest. Ophthalmol. Vis. Sci. 2017;58(8):4865.
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© ARVO (1962-2015); The Authors (2016-present)
We previously showed full-field optical coherence tomography (FFOCT) imaging of retina and used multimodal fluorescence-FFOCT to identify cells in the retinal ganglion cell layer (GCL) (Grieve et al, IOVS 2016). FFOCT revealed micrometric morphological detail in these tissues, and allowed visualization of fibers, vessels, and cellular details. However some cells were sometimes masked by the stronger scattering signals from overlying fibrous structures.
Here we apply a new method, named dynamic FFOCT, to imaging of retinal explants in order to reveal hidden cells. This technique relies on cell motility to create intrinsic contrast in the image. The signal is produced by fluctuations, caused by intracellular displacements that are occurring in the 10-100 Hz range. Macaque, mouse and rat retinal explants were imaged with full-field optical coherence tomography (FFOCT) in both static and dynamic modes. Time series were acquired over 24 hour periods.
Static and dynamic FFOCT create complementary contrast on different structures. Stationary structures in static mode include fibers and vessels, while moving structures in dynamic mode are intracellular, thus creating or enhancing contrast in previously invisible cells. Color coding according to temporal frequency bands highlighted different cell populations. In the mouse GCL for example, two cell populations are identified: round cells with almost no intracellular inhomogeneity, and fewer cells with a faster cytoplasm, and a slower dark center, that could correspond to the nucleus. Time series on retinal explants showed reduction in activity in cell nuclei over time, indicating their death.
Composite static and dynamic FFOCT provides the best possible image containing the most information for imaging of retinal explants. Dynamic FFOCT adds information on cell activity and therefore cell health, which is of interest in longitudinal explant studies. Next steps involve further quantification of the motility signal, including use of the signal as a biomarker of cell viability, and exploring whether the cell populations identified by color coding correspond to specific cell types, leading the way to label-free differentiation of retinal neurons.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.
Merged static (red) and dynamic (green) FFOCT images identify stationary (fibers, vessels) and dynamic (cell) structures.
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