By inducing stress on Retinal Pigment Epithelium cell cultures, changes in dynamic subcellular signals were observed with Dynamic Full-Field OCT. Comparing with immunochemistry, mitochondria were identified as the main contributor of dynamic signal.
Dynamic FFOCT allows us to record the intrinsic motion of biological samples in 3D, over hours. We performed scratch assays on primary porcine RPE and human induced pluripotent stem cells derived RPE cell cultures. We plotted motion maps from the optical flow. For wounds <40µm, the cell layer close the wound at different speeds depending on the type of RPE cells. For bigger wounds, the cell layer retract, mimicking degenerative diseases. Comparison between Dynamic FFOCT images and Immuno-chemistry images showed that mitochondria may contribute to the dynamic profile of cells. Dynamic FFOCT can be useful for the study of regenerative medicine.
Dynamic FFOCT allows us to see the sub-cellular motion of biological samples. We are able to follow the evolution in the same plane of biological samples for hours thanks to an autofocus procedure. RPE cells are involved in the integrity of retina and vision. We performed a linear scratch assay in RPE cell culture with a surgical scalpel blade, inducing border cell migration at 20.8 µm/h to close the scratch. We also recorded motility of microvilli, thanks to rapid GPU computing. Quantitative live imaging of RPE cell culture with DFFOCT is useful in development of disease models of retinal degeneration.
We applied quantitative dynamic full-field OCT (qDFFOCT) to imaging of human induced pluripotent stem cell retinal organoids which are a platform for investigating retinal development, pathophysiology, and cellular therapies. In contrast to histological analysis and immunofluorescence staining in which multiple specimens fixed at different times are used to reconstruct developmental processes, qDFFOCT imaging can provide repeated images and analysis of the same living organoids with a contrast created by intracellular organelle motion and linked to metabolism. In order to quantify the dynamic signal, we computed each image in Hue-Saturation-Value color-space and benefitted from the latest advances in GPU computing to accelerate the process. We performed time-lapse acquisitions in a locked plane, highlighting cell differentiation, division and mitosis with a sub-micrometer resolution. By moving deeper into the samples, we were also able to acquire series of planes in depth to reconstruct the organoid 3D organization. We also applied qDFFOCT on a damaged macaque cornea and used cutting edge algorithms to track cell motion and successfully reconstruct a migration map of epithelial wound healing. This could help understand the healing mechanism and have great interest in cell therapy. Besides showing our latest results we will explain the signal processing chain we developed to compute quantitative dynamic images where the colors code continuously for dynamic frequencies. Our overall aim is to use the dynamic signal as a non-invasive marker to predict cell type and cell cycle phases, making qDFFOCT a new label-free imaging method.
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