KEYWORDS: Wavefronts, Retinal scanning, Optical coherence tomography, In vivo imaging, Eye, Signal to noise ratio, Sensors, Glasses, Image resolution, Cones
We propose a compact full-field OCT assisted by an adaptive lens positioned in front of the eye for wavefront correction, enabling to ally high resolution (2 μm × 2 μm × 8 μm) with a wide field-of-view (5°× 5°) for in vivo retinal imaging.
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.
Eye movements are commonly seen as an obstacle to high-resolution ophthalmic imaging. In this context we study the natural axial movements of in vivo human eye and show that they can be used to modulate the optical phase and retrieve tomographic images via time-domain full-field optical coherence tomography (TD-FF-OCT). This approach opens a path to a simplified ophthalmic TD-FF-OCT device, operating without the usual piezo motor-camera synchronization. The device demonstrates in vivo human corneal images under different image retrieval schemes (2-phase and 4-phase) and different exposure times (3.5 ms, 10 ms, 20 ms).
The highest three-dimensional (3D) resolution possible in in-vivo retinal imaging is achieved by combining optical coherence tomography (OCT) and adaptive optics. However, this combination brings important limitations, such as small field-of-view and complex, cumbersome systems, preventing so far the translation of this technology from the research lab to clinics. Here, we mitigate these limitations by combining our compact time-domain full-field OCT (FFOCT) with a multi-actuator adaptive lens positioned just in front of the eye, in a technique we call the adaptive-glasses wavefront sensorless approach. Through this approach, we demonstrate that ocular aberrations can be corrected, increasing the FFOCT signal-to-noise ratio and enabling imaging of different retinal layers with a 2μm x 2μm x 8μm resolution over a 5° x 5° field-of-view, without major anisoplanatism influence.
Allying high-resolution with a large field-of-view (FOV) is of great importance in the fields of biology and medicine, but particularly challenging when imaging non-flat living samples such as the retina. Indeed, high-resolution is normally achieved with adaptive optics (AO) and scanning methods, which considerably reduce the useful FOV and increase the system complexity. Here, we introduce coherence gate shaping for FF-OCT, to optically shape the coherence gate geometry to match the retinal curvature, thus achieving a larger FOV than previously possible. Using this instrument, we obtained high-resolution images of photoreceptors close to the foveal center without AO and with a 1x1m² FOV. This novel advance facilitates the extraction of photoreceptor-based biomarkers and 4D monitoring of individual photoreceptors. We compare our findings with AO-assisted ophthalmoscopes, highlighting the potential of FF-OCT, as a compact system, to become a routine clinical imaging technique.
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 present a filtering procedure based on singular value decomposition to remove artifacts arising from sample motion during dynamic full field OCT acquisitions. The presented method succeeded in removing artifacts created by environmental noise from data acquired in a clinical setting, including in vivo data. Moreover, we report on a new method based on using the cumulative sum to compute dynamic images from raw signals, leading to a higher signal to noise ratio, and thus enabling dynamic imaging deeper in tissues.
To achieve 3D high-cellular resolution, a great effort, in the past years, was made to develop Adaptive Optics (AO)-OCT systems. However, such systems require quite complex, expensive and cumbersome hardware, making clinical transfer challenging. Moreover, conventional AO correction is limited to the retina isoplanatic patch (about 1deg), reducing the useful field of view (FOV). Recently, we showed the potential of Time Domain Full-Field-OCT (FF-OCT) to achieve 2deg FOV high-cellular-resolution in-vivo retinal imaging without using AO. Nevertheless, the technique was still facing some challenges in providing consistent and reproducible images (mainly due to axial eye motion), and it presented a reduced signal and FOV. Here, we present the new generation of FF-OCT system with axial eye motion tracking. We show new results and methods to minimize dispersion and coherence gate curvature enabling achieving 4deg (potentially 8deg) FOV high-cellular-resolution retinal images.
KEYWORDS: Adaptive optics, Eye, Optical coherence tomography, Signal to noise ratio, 3D image enhancement, 3D image processing, Retinal scanning, Glasses, In vivo imaging, Aberration correction
To achieve 3D high-cellular resolution, a great effort, in the past years, was made to develop Adaptive Optics (AO)-OCT systems. However, such systems require quite complex, expensive and cumbersome hardware, making clinical transfer challenging. Recently, we demonstrated that the use of spatially incoherent illumination in Time-Domain Full-Field (FF)-OCT offers a valuable advantage: the lateral resolution is almost insensitive to ocular aberrations that only affect the FF-OCT signal level. We took advantage of this property to image in-vivo photoreceptor mosaic without using an AO technique. Nevertheless, the FF-OCT technique was still facing some challenges in providing consistent and reproducible images, mainly due to axial eye motion and reduced signal level. Here, we present the Adaptive Glasses-assisted FF-OCT, where an adaptive lens is placed just in front of the eye, like spectacles, enabling correction of the first 10 Zernike polynomials, increasing the FF-OCT signal level.
Full-Field Optical Coherence Tomography (FFOCT) is an effective technique for tissue anatomy imaging, allowing cancer detection through the observation of disorders in the tissue microarchitecture. Moreover, with the temporal analysis of the FFOCT signal variations, a functional dimension is added, allowing the distinction of cell types through their intracellular activity. This complementary imaging mode, called Dynamic Cell Imaging (DCI), has shown the ability to identify normal cells, cancer cells and immune cells in different types of tissue such as breast, liver or lung.
On samples ranging from cell cultures to entire tissue resections, DCI signals are recorded and analyzed in order to characterize the involved endogenous biomarker at the subcellular scale. Longitudinal studies of these samples over a few hours are performed under different environment perturbations intended to modify the cell metabolism.
The potential of bimodal FFOCT is evaluated through a clinical study organized at the department of breast surgery of Peking University People’s Hospital in Beijing. More than 200 breast samples and lymph nodes are included. A part of the images will be directly compared to histology to identify reading criteria and build a reference atlas. The other part will be read on a blind study to measure the ability of cancer detection with respect to histology.
To take full advantage of the FFOCT and the DCI information richness for faster cancer assessment during surgeries, a computer-aided diagnostic system based on Machine Learning, and more specifically Deep Learning, is investigated.
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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