We present cone spectral sensitivity and photopigment density measures in the living human eye using adaptive optics optical coherence tomography (AO-OCT) and initial results in rods. AO-OCT optoretinograms after visible light stimulation of variable intensities were acquired. Cones were classified and the mean post-stimulus response to incident retinal energy and wavelength was fit to a power law and related to spectral sensitivity and photopigment density. Individual cone sensitivities showed excellent agreement with ex vivo macaque suction electrophysiology measurements (Baylor 1987). Photopigment density variation and increasing photopigment towards the fovea were consistent with the literature. Rod mean µΔOPL responses trended in the direction of expected rod sensitivity.
Adaptive optics (AO) ophthalmoscopes enable retinal imaging at cellular resolution. The small field of view (FOV) and high magnification of these instruments make inclusion of a fixation channel critical for controlling the patch of retina that is stimulated with light and imaged. Here, we develop a more powerful fixation channel that is integrated with an improved stimulus channel in the Indiana AO optical coherence tomography (AO-OCT) system. It uses all stock components except one 3D printed optical mount and some machined adaptor plates. We balanced the trade-offs between subject working distance, steering field of view, dioptric correction range, and stimulus light efficiency and achieved better performance in all areas compared to our previous channel. We report on the overarching objectives of the integrated fixation and stimulus channel, its design and its validation as illustrated by several AO-OCT imaging examples. While intended for our AO-OCT system, the design, components, and performance trade-offs are general enough to be applicable to many other AO ophthalmoscopes in the field.
Cone photoreceptors are central to vision and die in many retinal degenerative diseases. High-resolution retinal imaging methods–notably adaptive optics optical coherence tomography (AO-OCT)–use these cells’ reflectance profiles to characterize their morphologic and functional properties in the living human eye to assess their health. While some cone cells reveal reflections that correspond to identifiable features such as the inner segment/outer segment junction (IS/OS) and cone outer segment tip (COST), other cells can generate additional unexplained reflections that complicate our ability to characterize their reflectance profile. Here, we present a new quantitative method to properly identify cone reflections in AO-OCT images that correspond to their features. We use this method to estimate the prevalence of any additional cone reflections in healthy eyes and eyes with retinitis pigmentosa (RP) and to identify the true COST reflection. Using our method as a ground truth, we find that the conventional method (which identifies COST as the brightest reflection between IS/OS and retinal pigment epithelium) misidentified COST in 6.1±1.5% of cones in healthy controls. In the transition zones of RP, this rate can increase to 18.8%. In these cones, our method’s estimate of cone outer segment length and optoretinogram response differed by 36.8 ± 12.8% and 20.7 ± 17.6%, respectively, in healthy controls, and by 79.5 ± 21.2% and 34.9 ± 24.8% in the transition zone of RP.
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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.
The high resolution of adaptive optics optical coherence tomography (AO-OCT) allows 3-dimensional imaging of individual cone photoreceptors in vivo. Histology has revealed that short-wavelength-sensitive (S) cones have distinct structural features compared with medium-wavelength-sensitive (M) and long-wavelength-sensitive (L) cones. Quantifying these structural features in images of living human retinas may provide a simpler and quicker method for identifying S cones than by imaging cone function (e.g., optoretinography). Here, we present a quantitative method for using AO-OCT measurements of cone structure in a support vector machine (SVM) classifier to identify individual S cones. For every cone cell, we measured six key structural parameters: inner segment length (ISL), outer segment length (OSL), inner segment / outer segment conjunction (IS/OS) diameter, cone outer-segment tip (COST) diameter, IS/OS reflectance, and COST reflectance. ISL and OSL were determined from depth differences between reflections of the external limiting membrane (ELM) and IS/OS, and IS/OS and COST, respectively. Each reflection’s depth was measured with sub-pixel accuracy using Gaussian interpolation; its diameter was measured using the gradient information from the en face projection at that depth. Among 6,398 analyzed cones in six subjects, we found S cones had significantly longer ISLs, shorter OSLs, and wider IS/OS diameters than did cones of other types. We used these structural differences in our SVM model to classify cone spectral types and compared results with cone optoretinography. In five of the six subjects, S cones were identified with F1 scores ranging from 0.78 to 0.93.
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.
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.
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.
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.
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.
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.
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.
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 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.
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