Super-resolution retinal imaging using optically reassigned scanning laser ophthalmoscopy

In vivo imaging of human retinal ganglion cells using optical coherence tomography without adaptive optics

Retinal ganglion cells play an important role in human vision, and their degeneration results in glaucoma and other neurodegenerative diseases. Imaging these cells in the living human retina can greatly improve the diagnosis and treatment of glaucoma. However, owing to their translucent soma and tight packing arrangement within the ganglion cell layer (GCL), successful imaging has only been achieved with sophisticated research-grade adaptive optics (AO) systems. For the first time we demonstrate that GCL somas can be resolved and cell morphology can be quantified using non-AO optical coherence tomography (OCT) devices with optimal parameter configuration and post-processing.

Dynamic structured illumination for confocal microscopy

Structured illumination enables the tailoring of an imaging device's optical transfer function to enhance resolution. We propose the incorporation of a temporal periodic modulation, specifically a rotating mask, to encode multiple transfer functions in the temporal domain. This approach is demonstrated using a confocal microscope configuration. At each scanning position, a temporal periodic signal is recorded. By filtering around each harmonic of the rotation frequency, multiple images of the same object can be constructed. The image carried by the nth harmonic is a convolution of the object with a phase vortex of topological charge n, similar to the outcome when using a vortex phase plate as an illumination. This enables the collection of chosen high spatial frequencies from the sample, thereby enhancing the spatial resolution of the confocal microscope.

Label-free image scanning microscopy for kHz super-resolution imaging and single particle tracking

We report the modification of a label-free image scanning microscope (ISM) to perform asynchronous 2D imaging at up to 24kHz while keeping the lateral resolution gain and background rejection of a regular label-free ISM setup. Our method uses a resonant mirror oscillating at 12kHz for one-direction scanning and a chromatic line for instantaneous scanning in the other direction. We adapt optical photon reassignment in this scanning regime to perform fully optical super-resolution imaging. We exploit the kHz imaging capabilities of this confocal imaging system for single nanoparticle tracking down to 20 nm for gold and 50 nm for silica particles as well as imaging freely moving Lactobacillus with improved resolution.

Nondestructive inspection of surface nanostructuring using label-free optical super-resolution imaging

Ultrafast laser processing can induce surface nanostructurating (SNS) in most materials with dimensions close to the irradiation laser wavelength. In-situ SNS characterization could be key for laser parameter's fine-tuning, essential for the generation of complex and/or hybrid nanostructures. Laser Induced Periodic Surface Structures (LIPSS) created in the ultra-violet (UV) range generate the most fascinating effects. They are however highly challenging to characterize in a non-destructive manner since their dimensions can be as small as 100 nm. Conventional optical imaging methods are indeed limited by diffraction to a resolution of [Formula: see text] nm. Although optical super-resolution techniques can go beyond the diffraction limit, which in theory allows the visualization of LIPSS, most super-resolution methods require the presence of small probes (such as fluorophores) which modifies the sample and is usually incompatible with a direct surface inspection. In this paper, we demonstrate that a modified label-free Confocal Reflectance Microscope (CRM) in a photon reassignment regime (also called re-scan microscopy) can detect sub-diffraction limit LIPSS. SNS generated on a titanium sample irradiated with a [Formula: see text] nm femtosecond UV-laser were characterized with nanostructuring period ranging from 105 to 172 nm. Our label-free, non-destructive optical surface inspection was done at 180 [Formula: see text]m[Formula: see text]/s, and the results are compared with commercial SEM showing the metrological efficiency of our approach.

In vivo super-resolution of the brain - How to visualize the hidden nanoplasticity?

Super-resolution fluorescence microscopy has entered most biological laboratories worldwide and its benefit is undisputable. Its application to brain imaging, for example in living mice, enables the study of sub-cellular structural plasticity and brain function directly in a living mammal. The demands of brain imaging on the different super-resolution microscopy techniques (STED, RESOLFT, SIM, ISM) and labeling strategies are discussed here as well as the challenges of the required cranial window preparation. Applications of super-resolution in the anesthetized mouse brain enlighten the stability and plasticity of synaptic nanostructures. These studies show the potential of in vivo super-resolution imaging and justify its application more widely in vivo to investigate the role of nanostructures in memory and learning.

Comparison of Cone Mosaic Metrics From Images Acquired With the SPECTRALIS High Magnification Module and Adaptive Optics Scanning Light Ophthalmoscopy

Purpose

To compare cone mosaic metrics derived from adaptive optics scanning light ophthalmoscopy (AOSLO) images with those derived from Heidelberg Engineering SPECTRALIS High Magnification Module (HMM) images.

Methods

Participants with contiguous cone mosaics had HMM imaging performed at locations superior and temporal to the fovea. These images were registered and averaged offline and then aligned to split-detection AOSLO images; 200 × 200-µm regions of interest were extracted from both modalities. Cones were semi-automatically identified by two graders to provide estimates of cone density and spacing.

Results

Thirty participants with contiguous cone mosaics were imaged (10 males, 20 females; age range, 11-67 years). Image quality varied, and 80% of our participants had analyzable HMM images. The intergrader intraclass correlation coefficients for cone metrics were good for both modalities (0.688-0.757 for HMM; 0.805-0.836 for AOSLO). Cone density estimates from HMM images were lower by 2661 cones/mm2 (24.1%) on average compared to AOSLO-derived estimates. Accordingly, HMM estimates of cone spacing were increased on average compared to AOSLO.

Conclusions

The cone mosaic can be visualized in vivo using the SPECTRALIS HMM, although image quality is variable and imaging is not successful in every individual. Metrics extracted from HMM images can differ from those from AOSLO, although excellent agreement is possible in individuals with excellent optical quality and precise co-registration between modalities.

Translational Relevance

Emerging non-adaptive optics-based photoreceptor imaging is more clinically accessible than adaptive optics techniques and has potential to expand high-resolution imaging in a clinical environment.

In-vivo sub-diffraction adaptive optics imaging of photoreceptors in the human eye with annular pupil illumination and sub-Airy detection

Adaptive optics scanning light ophthalmoscopy (AOSLO) allows non-invasive visualization of the living human eye at the microscopic scale; but even with correction of the ocular wavefront aberrations over a large pupil, the smallest cells in the photoreceptor mosaic cannot always be resolved. Here, we synergistically combine annular pupil illumination with sub-Airy disk confocal detection to demonstrate a 33% improvement in transverse resolution (from 2.36 to 1.58 μm) and a 13% axial resolution enhancement (from 37 to 32 μm), an important step towards the study of the complete photoreceptor mosaic in heath and disease. Interestingly, annular pupil illumination also enhanced the visualization of the photoreceptor mosaic in non-confocal detection schemes such as split detection AOSLO, providing a strategy for enhanced multimodal imaging of the cone and rod photoreceptor mosaic.

Super-resolution ophthalmoscopy: Virtually structured detection for resolution improvement in retinal imaging

Quantitative retinal imaging is essential for advanced study and clinical management of eye diseases. However, spatial resolution of retinal imaging has been limited due to available numerical aperture and optical aberration of the ocular optics. Structured illumination microscopy has been established to break the diffraction-limit resolution in conventional light microscopy. However, practical implementation of structured illumination microscopy for in vivo ophthalmoscopy of the retina is challenging due to inevitable eye movements that can produce phase artifacts. Recently, we have demonstrated the feasibility of using virtually structured detection as one alternative to structured illumination microscopy for super-resolution imaging. By providing the flexibility of digital compensation of eye movements, the virtually structured detection provides a feasible, phase-artifact-free strategy to achieve super-resolution ophthalmoscopy. In this article, we summarize the technical rationale of virtually structured detection, and its implementations for super-resolution imaging of freshly isolated retinas, intact animals, and awake human subjects.

Adaptive optics for high-resolution imaging

Adaptive optics (AO) is a technique that corrects for optical aberrations. It was originally proposed to correct for the blurring effect of atmospheric turbulence on images in ground-based telescopes and was instrumental in the work that resulted in the Nobel prize-winning discovery of a supermassive compact object at the centre of our galaxy. When AO is used to correct for the eye's imperfect optics, retinal changes at the cellular level can be detected, allowing us to study the operation of the visual system and to assess ocular health in the microscopic domain. By correcting for sample-induced blur in microscopy, AO has pushed the boundaries of imaging in thick tissue specimens, such as when observing neuronal processes in the brain. In this primer, we focus on the application of AO for high-resolution imaging in astronomy, vision science and microscopy. We begin with an overview of the general principles of AO and its main components, which include methods to measure the aberrations, devices for aberration correction, and how these components are linked in operation. We present results and applications from each field along with reproducibility considerations and limitations. Finally, we discuss future directions.

Coherence gate shaping for wide field high-resolution in vivo retinal imaging with full-field OCT

Allying high-resolution with a large field-of-view (FOV) is of great importance in the fields of biology and medicine, but it is particularly challenging when imaging non-flat living samples such as the human 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. An alternative technique is time-domain full-field optical coherence tomography (FF-OCT), which has already shown its potential for in-vivo high-resolution retinal imaging. Here, we introduce coherence gate shaping for FF-OCT, to optically shape the coherence gate geometry to match the sample curvature, thus achieving a larger FOV than previously possible. Using this instrument, we obtained high-resolution images of living human photoreceptors close to the foveal center without AO and with a 1 mm × 1 mm FOV in a single shot. This novel advance enables the extraction of photoreceptor-based biomarkers with ease and spatiotemporal 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.

Two-photon image-scanning microscopy with SPAD array and blind image reconstruction

Two-photon excitation (2PE) laser scanning microscopy is the imaging modality of choice when one desires to work with thick biological samples. However, its spatial resolution is poor, below confocal laser scanning microscopy. Here, we propose a straightforward implementation of 2PE image scanning microscopy (2PE-ISM) that, by leveraging our recently introduced single-photon avalanche diode (SPAD) array detector and a novel blind image reconstruction method, is shown to enhance the effective resolution, as well as the overall image quality of 2PE microscopy. With our adaptive pixel reassignment procedure ∼1.6 times resolution increase is maintained deep into thick semi-transparent samples. The integration of Fourier ring correlation based semi-blind deconvolution is shown to further enhance the effective resolution by a factor of ∼2 - and automatic background correction is shown to boost the image quality especially in noisy images. Most importantly, our 2PE-ISM implementation requires no calibration measurements or other input from the user, which is an important aspect in terms of day-to-day usability of the technique.

Two-photon image-scanning microscopy with SPAD array and blind image reconstruction

Two-photon excitation (2PE) laser scanning microscopy is the imaging modality of choice when one desires to work with thick biological samples. However, its spatial resolution is poor, below confocal laser scanning microscopy. Here, we propose a straightforward implementation of 2PE image scanning microscopy (2PE-ISM) that, by leveraging our recently introduced single-photon avalanche diode (SPAD) array detector and a novel blind image reconstruction method, is shown to enhance the effective resolution, as well as the overall image quality of 2PE microscopy. With our adaptive pixel reassignment procedure ∼1.6 times resolution increase is maintained deep into thick semi-transparent samples. The integration of Fourier ring correlation based semi-blind deconvolution is shown to further enhance the effective resolution by a factor of ∼2 - and automatic background correction is shown to boost the image quality especially in noisy images. Most importantly, our 2PE-ISM implementation requires no calibration measurements or other input from the user, which is an important aspect in terms of day-to-day usability of the technique.

RAC-CNN: multimodal deep learning based automatic detection and classification of rod and cone photoreceptors in adaptive optics scanning light ophthalmoscope images

Quantification of the human rod and cone photoreceptor mosaic in adaptive optics scanning light ophthalmoscope (AOSLO) images is useful for the study of various retinal pathologies. Subjective and time-consuming manual grading has remained the gold standard for evaluating these images, with no well validated automatic methods for detecting individual rods having been developed. We present a novel deep learning based automatic method, called the rod and cone CNN (RAC-CNN), for detecting and classifying rods and cones in multimodal AOSLO images. We test our method on images from healthy subjects as well as subjects with achromatopsia over a range of retinal eccentricities. We show that our method is on par with human grading for detecting rods and cones.