Cells shape or density is an important marker of tissues pathology. However, individual cells are difficult to observe in thick tissues frequently presenting highly scattering structures such as collagen fibers. Endogenous techniques struggle to image cells in these conditions. Moreover, exogenous contrast agents like dyes, fluorophores or nanoparticles cannot always be used, especially if non-invasive imaging is required.
Scatterers motion happening down to the millisecond scale, much faster than the fix and highly scattering structures (global motion of the tissue), allowed us to develop a new approach based on the time dependence of the FF-OCT signals. This method reveals hidden cells after a spatiotemporal analysis based on singular value decomposition and wavelet analysis concepts. It does also give us access to local dynamics of imaged scatterers. This dynamic information is linked with the local metabolic activity that drives these scatterers.
Our technique can explore subcellular scales with micrometric resolution and dynamics ranging from the millisecond to seconds. By this mean we studied a wide range of tissues, animal and human in both normal and pathological conditions (cancer, ischemia, osmotic shock…) in different organs such as liver, kidney, and brain among others. Different cells, undetectable with FF-OCT, were identified (erythrocytes, hepatocytes…).
Different scatterer clusters express different characteristic times and thus can be related to different mechanisms that we identify with metabolic functions.
We are confident that the D-FFOCT, by accessing to a new spatiotemporal metabolic contrast, will be a leading technique on tissue imaging and could lead to better medical diagnosis.
Clement Apelian, Fabrice Harms, Olivier Thouvenin, and Claude A. Boccara, "Subcellular metabolic contrast in living tissue using dynamic full field OCT (D-FFOCT)
(Conference Presentation)," Proc. SPIE 9707, Dynamics and Fluctuations in Biomedical Photonics XIII, 97070T (Presented at SPIE BiOS: February 15, 2016; Published: 26 April 2016); https://doi.org/10.1117/12.2211015.4848677971001.
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