Publisher's Note: This paper, originally published on 14 March 2023, was replaced with a corrected/revised version on 5 January 2024. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.
Numerous retinal pathologies affect cone photoreceptor photopigment density, making it a potentially attractive functional biomarker for detecting and tracking disease progression. Conventional methods to measure photopigment density include psychophysical color matching, microspectrophotometry, and retinal densitometry, but these are either subjective, measure the aggregate response/change of thousands of cones, or are performed ex vivo. Recently, we have developed a method to measure spectral sensitivities of individual human cone photoreceptors objectively, non-invasively, and in vivo with adaptive optics optical coherence tomography (AO-OCT). In preliminary results we have observed variability in the spectral sensitivities of individual cones of the same type (S, M or L) that we hypothesize attributes to inter-cone variations in photopigment density. If correct, this may be of significant clinical interest. Here, we test this hypothesis by (1) deriving an expression for the relative photopigment densities of individual cone photoreceptors based on a theoretical model of the cone absorption process and (2) using this expression to estimate photopigment density from our AO-OCT measurements of spectral sensitivity. Our mean spectral sensitivity measurements align well to Stockman & Sharpe’s well-recognized cone fundamentals with a total least-squared error of 0.12 and confidence intervals (CI) <0.36, <0.025 and <0.017 for S, M, and L cones, respectively. The substantive variability in individual cone spectral sensitivities once related to photopigment density exhibits a distribution of standard deviation=0.177 for a group of 703 cones. This indicates a two-fold difference in light sensitivity between the least sensitive cone (least amount of photopigment) and the most sensitive cone (largest amount of photopigment) for 95% of the cones measured. Furthermore, we found relative photopigment density decreased with increasing retinal eccentricity from nasal to temporal retina at 3.8° eccentricity with a slope of -0.24/° (p < .001). Both density distribution and eccentricity dependence are consistent with the literature.
Adaptive optics (AO) measures and corrects ocular wavefront aberrations, enabling cellular-resolution retinal imaging and stimulation, and enhanced visual performance. AO is a dynamic control system that must track and correct temporal changes in ocular aberrations in real time. This necessitates a wavefront sensor whose integration time and readout time are sufficiently short to minimize the latency of the feedback system and hence maximize AO performance. Most current ophthalmic AO systems use long wavefront sensor integration times on the order of 10−60 ms, resulting in long latencies, low AO loop rates (typically no greater than 10 Hz with a discontinuous-exposure scheme), and small AO closed-loop bandwidths (less than 1.5 Hz). Here, by using an integration time (0.126 ms) that is 100−500× shorter and a readout speed of the wavefront sensor that is 3−100× higher, we reduce the AO latency and increase the AO bandwidth by ~30× to 37.5 Hz. Although our wavefront sensor detects 100−500× fewer photons, our noise analysis shows that this limited number of photons is still sufficient for diffraction-limited wavefront measurements and hence our wavefront sensing is photon-efficient. We demonstrate that the resulting ultrafast AO running at 233 Hz significantly improves aberration correction and retinal image quality over conventional AO in a clinically-relevant scenario.
Adaptive optics (AO) enables retinal imaging at cellular resolution. Today, most ophthalmic AO systems have closed-loop bandwidths of ≤2 Hz, insufficient for many conditions encountered in the clinic. Here, we develop an ultrafast AO with a bandwidth of 32.6 Hz and evaluate its use with optical coherence tomography. After AO activation, the RMS wavefront aberration from an un-cyclopleged human eye dropped below diffraction limit within 5 ms, 40× faster than the fastest ophthalmic AO system reported in the literature. Because the system converges so quickly, we can use the data immediately after a blink or when imaging locations are changed, even in eyes wearing contact lenses.
Adaptive optics optical coherence tomography technology enables non-invasive high-resolution retinal imaging and promises earlier detection of ocular disease. However, the images are corrupted by eye-movement artifacts that must be corrected to permit proper image analysis. We developed a method for efficiently removing eye-movement artifacts of A-lines using a multiple-reference global coordinate system. It corrects 3D translational eye movements, torsional eye movements, and image scaling, minimizing image distortion and substantially improving both regularity of the cone photoreceptor mosaic and clarity of individual cones.
Human color vision depends fundamentally on three spectral types of cone photoreceptors, yet methods to objectively measure these types across the whole visible spectrum in the living human eye do not exist. Here we demonstrate a new method based on phase-sensitive adaptive optics optical coherence tomography that offers the sensitivity and resolution to obtain spectral sensitivities with extremely high precision from 450-635 nm. We present the first objective measurements of human cone spectral sensitivity from 450 – 635 nm for all three cone types and demonstrate a path for quantifying spectral sensitivity over the whole visible spectrum.
Significance: Adaptive optics optical coherence tomography (AO-OCT) technology enables non-invasive, high-resolution three-dimensional (3D) imaging of the retina and promises earlier detection of ocular disease. However, AO-OCT data are corrupted by eye-movement artifacts that must be removed in post-processing, a process rendered time-consuming by the immense quantity of data.
Aim: To efficiently remove eye-movement artifacts at the level of individual A-lines, including those present in any individual reference volume.
Approach: We developed a registration method that cascades (1) a 3D B-scan registration algorithm with (2) a global A-line registration algorithm for correcting torsional eye movements and image scaling and generating global motion-free coordinates. The first algorithm corrects 3D translational eye movements to a single reference volume, accelerated using parallel computing. The second algorithm combines outputs of multiple runs of the first algorithm using different reference volumes followed by an affine transformation, permitting registration of all images to a global coordinate system at the level of individual A-lines.
Results: The 3D B-scan algorithm estimates and corrects 3D translational motions with high registration accuracy and robustness, even for volumes containing microsaccades. Averaging registered volumes improves our image quality metrics up to 22 dB. Implementation in CUDA™ on a graphics processing unit registers a 512 × 512 × 512 volume in only 10.6 s, 150 times faster than MATLAB™ on a central processing unit. The global A-line algorithm minimizes image distortion, improves regularity of the cone photoreceptor mosaic, and supports enhanced visualization of low-contrast retinal cellular features. Averaging registered volumes improves our image quality up to 9.4 dB. It also permits extending the imaging field of view (∼2.1 × ) and depth of focus (∼5.6 × ) beyond what is attainable with single-reference registration.
Conclusions: We can efficiently correct eye motion in all 3D at the level of individual A-lines using a global coordinate system.
Significance: There are no label-free imaging descriptors related to physiological activity of inner retinal cells in the living human eye. A major reason is that inner retinal neurons are highly transparent and reflect little light, making them extremely difficult to visualize and quantify.
Aim: To measure physiologically-induced optical changes of inner retinal cells despite their challenging optical properties.
Approach: We developed an imaging method based on adaptive optics and optical coherence tomography (AO-OCT) and a suite of postprocessing algorithms, most notably a new temporal correlation method.
Results: We captured the temporal dynamics of entire inner retinal layers, of specific tissue types, and of individual cells across three different timescales from fast (seconds) to extremely slow (one year). Time correlation analysis revealed significant differences in time constant (up to 0.4 s) between the principal layers of the inner retina with the ganglion cell layer (GCL) being the most dynamic. At the cellular level, significant differences were found between individual GCL somas. The mean time constant of the GCL somas (0.69 ± 0.17 s) was ∼ 30 % smaller than that of nerve fiber bundles and inner plexiform layer synapses and processes. Across longer durations, temporal speckle contrast and time-lapse imaging revealed motion of macrophage-like cells (over minutes) and GCL neuron loss and remodeling (over one year).
Conclusions: Physiological activity of inner retinal cells is now measurable in the living human eye.
Quantitative features of individual ganglion cells (GCs) are potential paradigm changing biomarkers for improved diagnosis and treatment monitoring of GC loss in neurodegenerative diseases like glaucoma and Alzheimer’s disease. The recent incorporation of adaptive optics (AO) with extremely fast and high-resolution optical coherence tomography (OCT) allows visualization of GC layer (GCL) somas in volumetric scans of the living human eye. The current standard approach for quantification – manual marking of AO-OCT volumes – is subjective, time consuming, and not practical for large scale studies. Thus, there is a need to develop an automatic technique for rapid, high throughput, and objective quantification of GC morphological properties. In this work, we present the first fully automatic method for counting and measuring GCL soma diameter in AO-OCT volumes. Aside from novelty in application, our proposed deep learningbased algorithm is novel with respect to network architecture. Also, previous deep learning OCT segmentation algorithms used pixel-level annotation masks for supervised learning. Instead in this work, we use weakly supervised training, which requires significantly less human input in curating the training set for the deep learning algorithm, as our training data is only associated with coarse-grained labels. Our automatic method achieved a high level of accuracy in counting GCL somas, which was on par with human performance yet orders of magnitude faster. Moreover, our automatic method’s measure of soma diameters was in line with previous histological and in vivo semi-automatic measurement studies. These results suggest that our algorithm may eventually replace the costly and time-consuming manual marking process in future studies.
Retinitis Pigmentosa (RP), the most common group of inherited retinal degenerative diseases, is characterized by progressive loss of peripheral vision that surrounds an island of healthy central vision and a transition zone of reduced vision. The most debilitating phase of the disease is cone photoreceptor death whose biological mechanisms remain unknown. Traditional clinical methods such as perimetry and electroretinography are gold standards for diagnosing and monitoring RP and indirectly assessing cone function. Both methods, however, lack the spatial resolution and sensitivity to assess disease progression at the level of individual photoreceptor cells, where it begins. To address this need, we developed an imaging method based on phase-sensitive adaptive optics optical coherence tomography (PS-AO-OCT) that characterizes cone dysfunction in RP subjects by stimulating cone cells with flashes of light and measuring their resulting nanometer-scale changes in optical path length. We introduce new biomarkers to quantify cone dysfunction. We find cone function decreases with increasing RP severity and even in the healthy central area where cone structure appears normal, cones respond differently than cones in the healthy controls.
Human color vision is achieved by mixing neural signals from cone photoreceptors sensitive to long- (L), medium- (M), and short- (S) wavelength light. The spatial arrangement and proportion of these spectral types in the retina set fundamental limits on color perception, and abnormal or missing types lead to color vision deficiencies. In vivo mapping of the trichromatic cone mosaic provides the most direct and quantitative means to assess the role photoreceptors play in color vision, but current methods of in vivo imaging have important limitations that preclude their widespread use. In this study, we present a new method for classifying cones based on their unique phase response to flashes of quasi-monochromatic light. Our use of phase provides unprecedented efficiency (30 min of subject time/retinal location) and accuracy (<0.02% of uncertainty), thus making in vivo cone classification practical in a wide range of color vision applications. We used adaptive optics optical coherence tomography to resolve cone cells in 3D and customized post-processing algorithms to extract the phase signal of individual cones. We successfully characterized light-induced changes to the phase signature of cones under different illuminant spectra, established the relationship between this phase change and the three cone spectral types, and used this relationship to classify and map cones in two color normal subjects.
The ganglion cell (GC) is the primary cell type damaged by diseases of the optic nerve such as glaucoma. Assessment of individual glaucoma risk is limited by our inability to accurately measure GC degeneration and loss. Recently, adaptive optics optical coherence tomography (AO-OCT) has enabled visualization and quantification of individual GC layer (GCL) somas in normal, healthy subjects. Quantifying GC loss in glaucoma, however, requires longitudinal assessment of these cells, which is confounded by normal age-related loss of these same cells. The ability to distinguish between these two causes of cell death is therefore paramount for early detection of glaucoma. In this study, we assess the ability of our AO-OCT method to track individual GCL somas over a period of one year and of our post processing methods to reliably measure soma loss rates. In four normal subjects with no history of ocular disease, we measured a soma loss rate of 0.15±0.04 %/yr (average±SD). As expected, this rate is more consistent with loss due to normal aging (~0.5%/yr) than to glaucomatous progression (~4.6%/yr). Aside from these rare isolated losses, the GCL soma mosaic was highly stable over the one year interval examined. Our measurements of peak GCL soma density did not differ significantly from histology reported in the literature.
The inner retina is critical for visual processing, but much remains unknown about its neural circuitry and vulnerability to disease. A major bottleneck has been our inability to observe the structure and function of the cells composing these retinal layers in the living human eye. Here, we present a noninvasive method to observe both structural and functional information. Adaptive optics optical coherence tomography (AO-OCT) is used to resolve the inner retinal cells in all three dimensions and novel post processing algorithms are applied to extract structure and physiology down to the cellular level. AO-OCT captured the 3D mosaic of individual ganglion cell somas, retinal nerve fiber bundles of micron caliber, and microglial cells, all in exquisite detail. Time correlation analysis of the AO-OCT videos revealed notable temporal differences between the principal layers of the inner retina. The GC layer was more dynamic than the nerve fiber and inner plexiform layers. At the cellular level, we applied a customized correlation method to individual GCL somas, and found a mean time constant of activity of 0.57 s and spread of ±0.1 s suggesting a range of physiological dynamics even in the same cell type. Extending our method to slower dynamics (from minutes to one year), time-lapse imaging and temporal speckle contrast revealed appendage and soma motion of resting microglial cells at the retinal surface.
Absorption of light by photoreceptors initiates vision, but also leads to accumulation of toxic photo-oxidative
compounds in the photoreceptor outer segment (OS). To prevent this buildup, small packets of OS discs are
periodically pruned from the distal end of the OS, a process called disc shedding. Unfortunately dysfunction in
any part of the shedding event can lead to photoreceptor and RPE dystrophy, and has been implicated in
numerous retinal diseases, including age related macular degeneration and retinitis pigmentosa. While much is
known about the complex molecular and signaling pathways that underpin shedding, all of these advancements
have occurred in animal models using postmortem eyes. How these translate to the living retina and to humans
remain major obstacles. To that end, we have recently discovered the optical signature of cone OS disc shedding
in the living human retina, measured noninvasively using optical coherence tomography equipped with adaptive
optics in conjunction with post processing methods to track and monitor individual cones in 4D. In this study,
we improve on this method in several key areas: increasing image acquisition up to MHz A-scan rates,
improving reliability to detect disc shedding events, establishing system precision, and developing cone
tracking for use across the entire awake cycle. Thousands of cones were successfully imaged and tracked over
the 17 hour period in two healthy subjects. Shedding events were detected in 79.5% and 77.4% of the tracked
cones. Similar to previous animal studies, shedding prevalence exhibited a diurnal rhythm. But we were
surprised to find that for these two subjects shedding occurred across the entire day with broad, elevated
frequency in the morning and decreasing frequency as the day progressed. Consistent with this, traces of the
average cone OS length revealed shedding dominated in the morning and afternoon and renewal in the evening.
Retinal pigment epithelium (RPE) cells are vital to health of the outer retina, however, are often
compromised in ageing and ocular diseases that lead to blindness. Early manifestation of RPE disruption
occurs at the cellular level, but while in vivo biomarkers at this scale hold considerable promise, RPE
cells have proven extremely challenging to image in the living human eye. Recently we addressed this
problem by using organelle motility as a novel contrast agent to enhance the RPE cell in conjunction with
3D resolution of adaptive optics-optical coherence tomography (AO-OCT) to section the RPE layer. In
this study, we expand on the central novelty of our method – organelle motility – by characterizing the
dynamics of the motility in individual RPE cells, important because of its direct link to RPE physiology.
To do this, AO-OCT videos of the same retinal patch were acquired at approximately 1 min intervals or
less, time stamped, and registered in 3D with sub-cellular accuracy. Motility was quantified by an
exponential decay time constant, the time for motility to decorrelate the speckle field across an RPE cell.
In two normal subjects, we found the decay time constant to be just 3 seconds, thus indicating rapid
motility in normal RPE cells.
A maximum a-posteriori (MAP) estimator for signal amplitude of optical coherence tomography (OCT) is presented. This
estimator provides an accurate and low bias estimation of the correct OCT signal amplitude even at very low signal-tonoise
ratios. As a result, contrast improvement of retinal OCT images is demonstrated. In addition, this estimation method
allows for an estimation reliability to be calculated. By combining the MAP estimator with a previously demonstrated
attenuation imaging algorithm, we present attenuation coefficient images of the retina. From the reliability derived from
the MAP image one can also determine which regions of the attenuation images are unreliable. From Jones matrix OCT
data of the optic nerve head (ONH), we also demonstrate that combining MAP with polarization diversity (PD) OCT
images can generate intensity images with fewer birefringence artifacts, resulting in better attenuation images. Analysis of
the MAP intensity images shows higher image SNR than averaging.
KEYWORDS: Optical coherence tomography, Polarization, Angiography, In vivo imaging, Coherence (optics), Computing systems, Eye, Tissues, Doppler tomography, Signal to noise ratio, Signal detection
A new optical coherence angiography (OCA) method, called correlation mapping OCA (cmOCA), is presented by
using the SNR-corrected complex correlation. An SNR-correction theory for the complex correlation calculation
is presented. The method also integrates a motion-artifact-removal method for the sample motion induced
decorrelation artifact. The theory is further extended to compute more reliable correlation by using multi-
channel OCT systems, such as Jones-matrix OCT. The high contrast vasculature imaging of in vivo human
posterior eye has been obtained. Composite imaging of cmOCA and degree of polarization uniformity indicates
abnormalities of vasculature and pigmented tissues simultaneously.
There are several applications of quantitative micro-displacement measurement of a biological specimen,
including characterization of mechanical property and monitoring a laser-induced photothermal expansion. In
this study, we proposed a quantitative micro-displacement measurement method using optical coherence
tomography (OCT). Specifically, the axial displacement is measured by Doppler OCT and magnitude of
displacement is measured by correlation coefficient. By using this method, we measured the local and microdisplacement
of the chicken muscles during laser irradiation. The proposed method successfully visualizes
thermal changes of chicken muscle due to the laser irradiation. The measured displacement and deformation
are useful information for the further understanding of the thermal changes.
Wide field of view (FOV) retinal imaging with high resolution has been demonstrated for quantitative analysis of retinal
microstructures. An adaptive optics scanning laser ophthalmoscope (AO-SLO) that was built in our laboratory was
improved by a customized scanning protocol for scanning wide region. A post-processing program was developed for
generating wide FOV retinal images. The high resolution retinal image with 1.7 degree by 3.0 degree FOV were
obtained.
Adaptive optics spectral domain optical coherence tomography (AO SD-OCT) has provided three-dimensional high isotropic
resolution retinal images in vivo. In order to enhance the image quality of deep region of the eye, the alternative wavelength
of 1-μm has been used for ophthalmic OCT. This study aims to develop AO SD-OCT with one-micrometer probe
and demonstrated high penetration and high resolution retinal imaging. A broadband 1-μm SLD light source (Suplerlum)
have the center wavelength of 1.03 μm and the spectral bandwidth of 106 nm. Axial scans were obtained by an InGaAs line
scan camera with the speed of 47,000 Hz. The aberrations of the system and the eye were measured by Shack-Hartmann
wavefront sensor (HASO32, Imagine Eyes, France) and corrected by a single deformable mirror (Mirao52, Imagine Eyes).
The AO closed loop was working with the iteration frequency of 7 Hz. The residual root mean square (RMS) wavefront
error was typically reduced to 0.1 μm. Seven eyes of 7 normal subjects were examined. The signal gain was found for all
subjects with AO. The waving interface of nerve fiber layer and ganglion cell layer, the interface between ganglion cell
layer and inner plexiform layer and choroid-sclera interface were observed. AO SD-OCT with one-micrometer probe may
be useful not only for the investigation of photoreceptors but also nerve fiber abnormalities.
Adaptive optics scanning laser ophthalmoscope with 1-micrometer band probe is presented. The residual wavefront error
was less than 0.02 with in vivo human eye. Photoreceptor cones are visualized at the eccentricity up to 10 degrees.
An adaptive optics scanning laser ophthalmoscope (AOSLO) corrects ocular aberrations to provide clear retinal images in
vivo with high lateral resolution. In this study, we developed an AOSLO system with a 1 μm wavelength probe beam. This
wavelength band is effective in improving the retinal imaging capability of AO systems. Because of the long wavelength,
the AOSLO system has high tolerance to a mechanical deformation of mirror surfaces; further, it is easier to achieve
diffraction limit of the system. To visualize individual photoreceptors, parafoveal regions of retinas of two normal subjects
were examined using the 1 μm wavelength AOSLO system. Ocular aberrations were measured using a Shack-Hartmann
wavefront sensor and an 840 nm superluminescent diode light source as an AO beacon. A magnetic deformable mirror was
used for the correction of ocular aberrations. When AO correction was carried out, the residual RMS wavefront error was
measured to be less than 0.1 μm. This residual aberration resulted in a lateral resolution of 3.6 μm of the retinal image.
Despite the relatively low transform-limited resolution due to the longer wavelength, the AOSLO could successfully be
used to visualize individual photoreceptors, flow of blood cells, and nerve fibers. It was found that the developed AOSLO
system with a center wavelength of 1 μm can effectively visualize individual photoreceptors.
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