Conventionally, cell chemotaxis is studied on two‐dimensional (2D) transparent surfaces, due to limitations in optical and image data‐collection techniques. However, surfaces that more closely mimic the natural environment of cells are often opaque. Optical coherence tomography (OCT) is a noninvasive label‐free imaging technique, which offers the potential to visualize moving cells on opaque surfaces and in three dimensions (3D). Here, we demonstrate that OCT is an effective means of time‐lapse videomicroscopy of Dictyostelium cells undergoing 3D (2D+time) cell migration on nitrocellulose substrates and 4D (3D+time) chemotaxis within low‐density agarose gels. The generated image sequences are compatible with current computer‐based image‐analysis software for quantification of cell motility. This demonstrates the utility of OCT for cell tracking and analysis of cell chemotaxis in complex environments. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

The dispersion mismatch between sample and reference arm in frequency-domain optical coherence tomography (OCT) can be used to iteratively suppress complex conjugate artifacts and thereby increase the imaging range. In this paper, we propose a fast dispersion encoded full range (DEFR) algorithm that detects multiple signal components per iteration. The influence of different dispersion levels on the reconstruction quality is analyzed experimentally using a multilayered scattering phantom and in vivo retinal tomograms at 800 nm. Best results have been achieved with 30 mm SF11, with neglectable resolution decrease due to finite resolution of the spectrometer. Our fast DEFR algorithm achieves an average suppression ratio of 55 dB and typically converges within 5 to 10 iterations. The processing time on non-dedicated hardware was 5 to 10 seconds for tomograms with 512 depth scans and 4096 sampling points per depth scan. Application of DEFR to the more challenging 1060 nm wavelength region is also demonstrated by introducing an additional optical fibre in the sample arm.

Optical coherence tomography (OCT) has revolutionises the diagnosis of retinal disease based on the detection of microscopic rather than subcellular changes in retinal anatomy. However, currently the technique is limited to the detection of microscopic rather than subcellular changes in retinal anatomy. However, coherence based imaging is extremely sensitive to both changes in optical contrast and cellular events at the micrometer scale, and can generate subtle changes in the spectral content of the OCT image. Here we test the hypothesis that OCT image speckle (image texture) contains information regarding otherwise unresolvable features such as organelle changes arising in the early stages of neuronal degeneration. Using ultrahigh resolution (UHR) OCT imaging at 800 nm (spectral width 140 nm) we developed a robust method of OCT image analyses, based on spatial wavelet and texture-based parameterisation of the image speckle pattern. For the first time we show that this approach allows the non-invasive detection and quantification of early apoptotic changes in neurons within 30 min of neuronal trauma sufficient to result in apoptosis. We show a positive correlation between immunofluorescent labelling of mitochondria (a potential source of changes in cellular optical contrast) with changes in the texture of the OCT images of cultured neurons. Moreover, similar changes in optical contrast were also seen in the retinal ganglion cell- inner plexiform layer in retinal explants following optic nerve transection. The optical clarity of the explants was maintained throughout in the absence of histologically detectable change. Our data suggest that UHR OCT can be used for the non-invasive quantitative assessment of neuronal health, with a particular application to the assessment of early retinal disease.

Visualization of cell migration during chemotaxis using spectral domain optical coherence tomography (OCT) requires non‐standard processing techniques. Stripe artefacts and camera noise floor present in OCT data prevent detailed computer‐assisted reconstruction and quantification of cell locomotion. Furthermore, imaging artefacts lead to unreliable results in automated texture based cell analysis. Here we characterize three pronounced artefacts that become visible when imaging sample structures with high dynamic range, e.g. cultured cells: (i) time‐varying fixed‐pattern noise; (ii) stripe artefacts generated by background estimation using tomogram averaging; (iii) image modulations due to spectral shaping. We evaluate techniques to minimize the above mentioned artefacts using an 800 nm optical coherence microscope. Effect of artefact reduction is shown exemplarily on two cell cultures, i.e. Dictyostelium on nitrocellulose substrate, and retinal ganglion cells (RGC‐5) cultured on a glass coverslip. Retinal imaging also profits from the proposed processing techniques. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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