The in vivo observation of the human retina at the cellular level is crucial to detect lesions before irreversible visual loss occurs, to follow the time course of retinal diseases and to evaluate and monitor the early effects of treatments. Despite the phenomenal advances in optical coherence tomography (OCT) and adaptive optics systems, in vivo imaging of several retinal cells is still elusive. Here we propose a radically different method compared to OCT, called transscleral optical phase imaging (TOPI), which allows to image retinal cells with high contrast, high resolution, and within an acquisition time suitable for clinical use. TOPI relies on high-angle oblique illumination of the retina, combined with adaptive optics, to enhance the phase contrast of transparent cells. We first present in-vivo images of retinal cells, from the retinal pigment epithelium (RPE) to the nerve and vascular layers of the retina, in eleven healthy volunteers without pupil dilation. The morphology of the cells in vivo is then compared to that of images obtained with the same technique applied on ex vivo human RPE and pig retinas. Finally, we demonstrate the ability of high resolution phase microscopy to image pericytes and microglia around rat retinal capillaries. Our results show the ability of TOPI to image and quantify retinal cells up to the RPE depth within a maximum time of 9 seconds over a field of view of 4.4 x 4.4°, opening new avenue in the in vivo exploration of the deepest layer of the retina in healthy and diseased eyes.

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The phase sensitivity limit of Differential Phase Contrast (DPC) with partially coherent light is analyzed in details. The parameters to tune phase sensitivity, such as the diameter of illumination, the numerical aperture of the objective, and the noise of the camera are taken into account to determine the minimum phase contrast that can be detected. We found that a priori information about the sample can be used to fine-tune these parameters to increase phase contrast. Based on this information, we propose a simple algorithm to predict phase sensitivity of a DPC setup, which can be performed before the setup is built. Experiments confirm the theoretical findings.

The observation of retinal cellular structures is fundamental to the understanding of eye pathologies. However, except for rods and cones, most of the retinal microstructures are weakly reflective and thus difficult to image with state of the art reflective optical imaging techniques such as optical coherence tomography. Recently, we demonstrated the possibility of obtaining the phase contrast of retinal cells in the eye using oblique illumination of the retina. Indeed, by illuminating the eye with incoherent oblique illumination, we obtain a secondary oblique illumination from the backscattered light which can then be used to obtain phase contrast in an effective transmission-like configuration. In this technique, a weak phase signal is modulated over an intense background. Maximizing this phase contrast is thus crucial for the image quality. Here, we investigate the parameters that affect phase contrast by modelling image formation with the backscattered light. We find that the key parameter for maximizing contrast is the intensity profile of the backscattered light. Specifically, the gradient of the profile is found to be proportional to the phase contrast. We validate the model by comparing simulations with experimental results on ex-vivo retina samples.

Objective To develop a fully automated method of retinal pigmented epithelium (RPE) cells detection, segmentation and analysis based on in vivo cellular resolution images obtained with the transscleral optical phase imaging method (TOPI). Methods Fourteen TOPI-RPE images from 11 healthy individuals were analysed. The developed image processing method encompassed image filtering and normalisation, detection and removal of blood vessels, cell detection and cell membrane segmentation. The produced measures were cellular density of RPE layer, cell area, number of neighbouring cells, eccentricity, circularity and solidity. In addition, we proposed coefficient of variation (CV) of RPE cellular membrane (CMD CV ) and the solidity of the RPE cell membrane-shape as new metrics for the assessment of RPE single cells. ResultsThe observed median cellular density of the RPE layer was 3743 cells/µm 2 (interquartile rate (IQR) 1687), with a median observed RPE cell area of 193 µm 2 (IQR 141). The mean number of neighbouring cells was 5.22 (standard deviation (SD) 0.05) per RPE cell. The mean RPE cell eccentricity was 0.67 (SD 0.02), median circularity 0.83 (IQR 0.01), and median solidity 0.92 (IQR 0.00). The median CMD CV was 0.19 (IQR 0.02). The method is characterised by a median image processing and analysis time of 48 sec (IQR 12) per image. Conclusions The present study provides the first fully automated quantitative assessment of human RPE single cells in vivo. The method provides a baseline for future research in the field of clinical ophthalmology, enabling characterisation and diagnostics of retinal diseases at the single-cell level.