Parafoveal cone function in choroideremia assessed with adaptive optics optoretinography.

Choroideremia (CHM) is an X-linked retinal degeneration leading to loss of the photoreceptors, retinal pigment epithelium (RPE), and choroid. Adaptive optics optoretinography is an emerging technique for noninvasive, objective assessment of photoreceptor function. Here, we investigate parafoveal cone function in CHM using adaptive optics optoretinography and compare with cone structure and clinical assessments of vision. Parafoveal cone mosaics of 10 CHM and four normal-sighted participants were imaged with an adaptive optics scanning light ophthalmoscope. While acquiring video sequences, a 2 s 550Δ10 nm, 450 nW/deg2 stimulus was presented. Videos were registered and the intensity of each cone in each frame was extracted, normalized, standardized, and aggregated to generate the population optoretinogram (ORG) over time. A gamma-pdf was fit to the ORG and the peak was extracted as ORG amplitude. CHM ORG amplitudes were compared to normal and were correlated with bound cone density, ellipsoid zone to RPE/Bruch's membrane (EZ-to-RPE/BrM) distance, and foveal sensitivity using Pearson correlation analysis. ORG amplitude was significantly reduced in CHM compared to normal (0.22 ± 0.15 vs. 1.34 ± 0.31). In addition, CHM ORG amplitude was positively correlated with cone density, EZ-to-RPE/BrM distance, and foveal sensitivity. Our results demonstrate promise for using ORG as a biomarker of photoreceptor function.

Peak Cone Density Predicted from Outer Segment Length Measured on Optical Coherence Tomography.

PURPOSE: To compare peak cone density predicted from outer segment length measured on optical coherence tomography with direct measures of peak cone density from adaptive optics scanning light ophthalmoscopy. METHODS: Data from 42 healthy participants with direct peak cone density measures and optical coherence tomography line scans available were used in this study. Longitudinal reflectivity profiles were analyzed using two methods of identifying the boundaries of the ellipsoid and interdigitation zones to estimate maximum outer segment length: peak-to-peak and the slope method. These maximum outer segment length values were then used to predict peak cone density using a previously described geometrical model. A comparison between predicted and direct peak cone density measures was then performed. RESULTS: The mean bias between observers for estimating maximum outer segment length across methods was less than 2 µm. Cone density predicted from the peak-to-peak method against direct cone density measures showed a mean bias of 6,812 cones/mm2 with 50% of participants displaying a 10% difference or less between predicted and direct cone density values. Cone density derived from the slope method showed a mean bias of -17,929 cones/mm2 relative to direct cone density measures, with only 41% of participants demonstrating less than a 10% difference between direct and predicted cone density values. CONCLUSION: Predicted foveal cone density derived from peak-to-peak outer segment length measurements using commercial optical coherence tomography show modest agreement with direct measures of peak cone density from adaptive optics scanning light ophthalmoscopy. The methods used here are imperfect predictors of cone density, however, further exploration of this relationship could reveal a clinically relevant marker of cone structure.

The Shape of the Foveal Avascular Zone: When a Circle Isn't Round.

Translational Relevance: Quantitative assessment of OCT-A images includes evaluating circularity and roundness of the FAZ. Inconsistent or inaccurate mathematical definitions of these metrics impacts their utility as biomarkers and impairs the ability to combine and compare results across studies.

Extracting spacing-derived estimates of rod density in healthy retinae.

Quantification of the rod photoreceptor mosaic using adaptive optics scanning light ophthalmoscopy (AOSLO) remains challenging. Here we demonstrate a method for deriving estimates of rod density and rod:cone ratio based on measures of rod spacing, cone numerosity, and cone inner segment area. Twenty-two AOSLO images with complete rod visualization were used to validate this spacing-derived method for estimating density. The method was then used to estimate rod metrics in an additional 105 images without complete rod visualization. The spacing-derived rod mosaic metrics were comparable to published data from histology. This method could be leveraged to develop large normative databases of rod mosaic metrics, though limitations persist with intergrader variability in assessing cone area and numerosity.

Intergrader agreement of foveal cone topography measured using adaptive optics scanning light ophthalmoscopy.

The foveal cone mosaic can be directly visualized using adaptive optics scanning light ophthalmoscopy (AOSLO). Previous studies in individuals with normal vision report wide variability in the topography of the foveal cone mosaic, especially the value of peak cone density (PCD). While these studies often involve a human grader, there have been no studies examining intergrader reproducibility of foveal cone mosaic metrics. Here we re-analyzed published AOSLO foveal cone images from 44 individuals to assess the relationship between the cone density centroid (CDC) location and the location of PCD. Across 5 graders with variable experience, we found a measurement error of 11.7% in PCD estimates and higher intergrader reproducibility of CDC location compared to PCD location (p < 0.0001). These estimates of measurement error can be used in future studies of the foveal cone mosaic, and our results support use of the CDC location as a more reproducible anchor for cross-modality analyses.

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.

Automated image processing pipeline for adaptive optics scanning light ophthalmoscopy.

To mitigate the substantial post-processing burden associated with adaptive optics scanning light ophthalmoscopy (AOSLO), we have developed an open-source, automated AOSLO image processing pipeline with both "live" and "full" modes. The live mode provides feedback during acquisition, while the full mode is intended to automatically integrate the copious disparate modules currently used in generating analyzable montages. The mean (±SD) lag between initiation and montage placement for the live pipeline was 54.6 ± 32.7s. The full pipeline reduced overall human operator time by 54.9 ± 28.4%, with no significant difference in resultant cone density metrics. The reduced overhead decreases both the technical burden and operating cost of AOSLO imaging, increasing overall clinical accessibility.

Cone photoreceptor reflectance variation in the northern tree shrew and thirteen-lined ground squirrel.

In vivo images of human cone photoreceptors have been shown to vary in their reflectance both spatially and temporally. While it is generally accepted that the unique anatomy and physiology of the photoreceptors themselves drives this behavior, the exact mechanisms have not been fully elucidated as most studies on these phenomena have been limited to the human retina. Unlike humans, animal models offer the ability to experimentally manipulate the retina and perform direct in vivo and ex vivo comparisons. The thirteen-lined ground squirrel and northern tree shrew are two emerging animal models being used in vision research. Both models feature cone-dominant retinas, overcoming a key limitation of traditional rodent models. Additionally, each possesses unique but well-documented anatomical differences in cone structure compared to human cones, which can be leveraged to further constrain theoretical models of light propagation within photoreceptors. Here we sought to characterize the spatial and temporal reflectance behavior of cones in these species. Adaptive optics scanning light ophthalmoscopy (AOSLO) was used to non-invasively image the photoreceptors of both species at 5 to 10 min intervals over the span of 18 to 25 min. The reflectance of individual cone photoreceptors was measured over time, and images at individual time points were used to assess the variability of cone reflectance across the cone mosaic. Variability in spatial and temporal photoreceptor reflectance was observed in both species, with similar behavior to that seen in human AOSLO images. Despite the unique cone structure in these animals, these data suggest a common origin of photoreceptor reflectance behavior across species. Such data may help constrain models of the cellular origins of photoreceptor reflectance signals. These animal models provide an experimental platform to further explore the morphological origins of light capture and propagation.

ENHANCED S-CONE SYNDROME: VISUAL FUNCTION, CROSS-SECTIONAL IMAGING, AND CELLULAR STRUCTURE WITH ADAPTIVE OPTICS OPHTHALMOSCOPY.

PURPOSE: To describe in detail the phenotype of a patient with enhanced S-cone syndrome. METHODS: We describe a 13-year-old boy who presented with blurred vision, vitreous cells, cystoid macular edema refractory to steroid treatment, and a negative uveitic workup. The patient underwent a complete ophthalmic examination, full-field electroretinograms (ffERG), automatic static perimetry and multimodal imaging with spectral domain optical coherence tomography, and adaptive optics scanning laser ophthalmoscopy (AOSLO). RESULTS: Spectral domain optical coherence tomography demonstrated cystoid macular edema and a hyperthick, delaminated midperipheral retina. Fluorescein angiography did not demonstrate macular leakage. Rod-mediated ffERGs were undetectable, and there was a supernormal response to short-wavelength stimuli compared with photopically matched longer wavelengths of light consistent with enhanced S-cone syndrome. Gene screening was positive for compound heterozygous mutations NR2E3: a known (c.119-2 A>C) and a novel (c.119-1G>A) mutation. By perimetry, sensitivities were normal or above normal for short-wavelength stimuli; there was no detectable rod-mediated vision. AOSLO demonstrated higher than normal cone densities in the perifoveal retina and evidence for smaller outer segment cone diameters. CONCLUSION: Evidence for supernumerary cones (at least twice the normal complement) by AOSLO and spectral domain optical coherence tomography was associated with supernormal S-cone sensitivities and electroretinogram responses confirming previous in vivo findings in postmortem human specimens. Smaller than normal cones in enhanced S-cone syndrome may represent "hybrid" photoreceptors analogous to the rd7/rd7 murine model of the disease.

Optoretinography of individual human cone photoreceptors.

Photoreceptors mediate the first step of vision, transducing light and passing signals to retinal neurons that ultimately send signals along the optic nerve to the brain. A functional deficiency in the photoreceptors, due to either congenital or acquired disease, can significantly affect an individual's sight and quality of life. Methods for quantifying the health and function of photoreceptors are essential for understanding both the progression of disease and the efficacy of treatment. Given that emerging treatments such as gene, stem cell, and small molecule therapy are designed to operate at the cellular scale, it is desirable to monitor function at the commensurate resolution of individual photoreceptors. Previously, non-invasive imaging methods for visualizing photoreceptor mosaic structure have been used to infer photoreceptor health, but these methods do not assess function directly. Conversely, most functional techniques, such as ERG and conventional microperimetry, measure function by aggregating the effects of signals from many photoreceptors. We have previously shown that stimulus-evoked intrinsic changes in intensity can be measured reliably in populations of cone photoreceptors in the intact human eye, a measurement we refer to more generally as the cone optoretinogram. Here we report that we can resolve the intensity optoretinogram at the level of individual cones. Moreover, we show that the individual cone optoretinogram exhibits two key signatures expected of a functional measure. First, responses in individual cones increase systematically as a function of stimulus irradiance. Second, we can use the amplitude of the functional response to middle wavelength (545 nm) light to separate the population of short-wavelength-sensitive (S) cones from the population of middle- and long-wavelength-sensitive (L and M) cones. Our results demonstrate the promise of optoretinography as a direct diagnostic measure of individual cone function in the living human eye.

Assessing Interocular Symmetry of the Foveal Cone Mosaic.

Purpose: To test the hypothesis that foveal cone topography is symmetrical between contralateral eyes. Methods: We used adaptive optics scanning light ophthalmoscopy to acquire images of the foveal cone mosaic in each eye of 58 subjects with normal vision (35 female, 23 male). Cones were semiautomatically identified over a 300 × 300-µm foveal area. From these cone coordinates, maps of cone density were derived, and we extracted estimates of peak cone density from each map. Mosaic regularity was assessed using Voronoi cell area regularity (VCAR). Average roundness and average area of the 70%, 75%, 80%, 85%, and 90% of peak density isodensity contours were evaluated. Results: The average peak cone density for right eyes was 180,286 cones/mm2 (n = 49) and for left eyes was 182,397 cones/mm2 (n = 45), with a mean absolute difference of 6363 cones/mm2 (n = 43). Peak density, cone spacing, VCAR, and average area within the isodensity contours of fellow eyes were not significantly different (P = 0.60, P = 0.83, P = 0.30, and P = 0.39, respectively). However, the average roundness of the isodensity contours was 2% more circular in the right eyes than in the left eyes (P = 0.02). Conclusions: There is interocular symmetry of peak foveal cone density, mosaic regularity, and area encompassing the most densely packed cells in subjects with normal vision. The origin and significance of the observed interocular difference in average roundness of the isodensity contours are unclear.

Cone Identification in Choroideremia: Repeatability, Reliability, and Automation Through Use of a Convolutional Neural Network.

Purpose: Adaptive optics imaging has enabled the visualization of photoreceptors both in health and disease. However, there remains a need for automated accurate cone photoreceptor identification in images of disease. Here, we apply an open-source convolutional neural network (CNN) to automatically identify cones in images of choroideremia (CHM). We further compare the results to the repeatability and reliability of manual cone identifications in CHM. Methods: We used split-detection adaptive optics scanning laser ophthalmoscopy to image the inner segment cone mosaic of 17 patients with CHM. Cones were manually identified twice by one experienced grader and once by two additional experienced graders in 204 regions of interest (ROIs). An open-source CNN either pre-trained on normal images or trained on CHM images automatically identified cones in the ROIs. True and false positive rates and Dice's coefficient were used to determine the agreement in cone locations between data sets. Interclass correlation coefficient was used to assess agreement in bound cone density. Results: Intra- and intergrader agreement for cone density is high in CHM. CNN performance increased when it was trained on CHM images in comparison to normal, but had lower agreement than manual grading. Conclusions: Manual cone identifications and cone density measurements are repeatable and reliable for images of CHM. CNNs show promise for automated cone selections, although additional improvements are needed to equal the accuracy of manual measurements. Translational Relevance: These results are important for designing and interpreting longitudinal studies of cone mosaic metrics in disease progression or treatment intervention in CHM.

Automatic longitudinal montaging of adaptive optics retinal images using constellation matching.

Adaptive optics (AO) scanning laser ophthalmoscopy offers a non-invasive approach for observing the retina at a cellular level. Its high resolution capabilities have direct application for monitoring and treating retinal diseases by providing quantitative assessment of cone health and density across time. However, accurate longitudinal analysis of AO images requires that AO images from different sessions be aligned, such that cell-to-cell correspondences can be established between timepoints. Such alignment is currently done manually, a time intensive task that is restrictive for large longitudinal AO studies. Automated longitudinal montaging for AO images remains a challenge because the intensity pattern of imaged cone mosaics can vary significantly, even across short timespans. This limitation prevents existing intensity-based montaging approaches from being accurately applied to longitudinal AO images. In the present work, we address this problem by presenting a constellation-based method for performing longitudinal alignment of AO images. Rather than matching intensity similarities between images, our approach finds structural patterns in the cone mosaics and leverages these to calculate the correct alignment. These structural patterns are robust to intensity variations, allowing us to make accurate longitudinal alignments. We validate our algorithm using 8 longitudinal AO datasets, each with two timepoints separated 6-12 months apart. Our results show that the proposed method can produce longitudinal AO montages with cell-to-cell correspondences across the full extent of the montage. Quantitative assessment of the alignment accuracy shows that the algorithm is able to find longitudinal alignments whose accuracy is on par with manual alignments performed by a trained rater.

Fully Automated Estimation of Spacing and Density for Retinal Mosaics.

PURPOSE: To introduce and validate a novel, fully automated algorithm for determining pointwise intercell distance (ICD) and cone density. METHODS: We obtained images of the photoreceptor mosaic from 14 eyes of nine subjects without retinal pathology at two time points using an adaptive optics scanning laser ophthalmoscope. To automatically determine ICD, the radial average of the discrete Fourier transform (DFT) of the image was analyzed using a multiscale, fit-based algorithm to find the modal spacing. We then converted the modal spacing to ICD by assuming a hexagonally packed mosaic. The reproducibility of the algorithm was assessed between the two datasets, and accuracy was evaluated by comparing the results against those calculated from manually identified cones. Finally, the algorithm was extended to determine pointwise ICD and density in montages by calculating modal spacing over an overlapping grid of regions of interest (ROIs). RESULTS: The differences of DFT-derived ICD between the test and validation datasets were 3.2% ± 3.5% (mean ± SD), consistent with the differences in directly calculated ICD (1.9% ± 2.9%). The average ICD derived by the automated method was not significantly different between the development and validation datasets and was equivalent to the directly calculated ICD. When applied to a full montage, the automated algorithm produced estimates of cone density across retinal eccentricity that well match prior empiric measurements. CONCLUSIONS: We created an accurate, repeatable, and fully automated algorithm for determining ICD and density in both individual ROIs and across entire montages. TRANSLATIONAL RELEVANCE: The use of fully automated and validated algorithms will enable rapid analysis over the full photoreceptor montage.

Assessing Retinal Structure in Patients with Parkinson's Disease.

OBJECTIVE: The retina is an extension of the central nervous system (CNS), and ocular symptoms can precede manifestations of CNS disorders. Given that several neurodegenerative conditions that affect the brain exhibit ocular symptoms, the retina may be an accessible biomarker to monitor disease progression. Dopamine, the key neurotransmitter related to Parkinson's disease (PD), is contained in amacrine and interplexiform cells, which reside in specific retinal layers. Understanding how loss of dopaminergic cells affects retinal anatomy could be relevant for monitoring disease progression. Here, our objective is to evaluate retinal structure (foveal pit morphology and thickness) in patients with PD. METHODS: Thirty-three Caucasian subjects diagnosed with PD and 40 age-matched Caucasian control subjects underwent retinal imaging with spectral-domain optical coherence tomography (SD-OCT). Axial length measurements were used to correct the lateral scale of each macular volume scan. From these corrected volumes, foveal morphology was quantified with previously described algorithms, and Early Treatment Diabetic Retinopathy Study (ETDRS) grids of retinal thickness were generated and incorporated into a logistic regression model to predict PD. RESULTS: Interocular foveal morphology measurements were highly symmetrical in PD patients and control subjects. There were no significant differences in foveal pit morphology between PD patients and control subjects. Using a model incorporating sex and axial length corrected ETDRS regions, we generated a receiver operating characteristic curve with a C-statistic of 0.80. CONCLUSION: Our study, which to our knowledge is the first to properly scale OCT measurements when quantifying retinal thickness, demonstrates that PD patients retain foveal symmetry between eyes. When constructing a model to predict PD, sex, along with the center 1 mm and temporal outer ETDRS regions, were significant predictors of PD. In addition to proper scaling of OCT measures, gender and racial differences in retinal anatomy should be considered in building future predictive PD models when using OCT.

A 2-Year Longitudinal Study of Normal Cone Photoreceptor Density.

Purpose: Despite the potential for adaptive optics scanning light ophthalmoscopy (AOSLO) to quantify retinal disease progression at the cellular level, there remain few longitudinal studies investigating changes in cone density as a measure of disease progression. Here, we undertook a prospective, longitudinal study to investigate the variability of cone density measurements in normal subjects during a 2-year period. Methods: Fourteen eyes of nine subjects with no known ocular pathology were imaged both at a baseline and a 2-year follow-up visit by using confocal AOSLO at five retinal locations. Two-year affine-registered images were created to minimize the effects of intraframe distortions. Regions of interest were cropped from baseline, 2-year manually aligned, and 2-year affine-registered images. Cones were identified (graded masked) and cone density was extracted. Results: Mean baseline cone density (cones/mm2) was 87,300, 62,200, 45,500, 28,700, and 18,200 at 190, 350, 500, 900, and 1500 µm, respectively. The mean difference (± standard deviation [SD]) in cone density from baseline to 2-year affine-registered images was 1400 (1700), 100 (1800), 300 (800), 400 (800), and 1000 (2400) cones/mm2 at the same locations. The mean difference in cone density during the 2-year period was lower for affine-registered images than manually aligned images. Conclusions: There was no meaningful change in normal cone density during a 2-year period. Intervisit variability in cone density measurements decreased when intraframe distortions between time points were minimized. This variability must be considered when planning prospective longitudinal clinical trials using changes in cone density as an outcome measure for assessing retinal disease progression.

Spatial summation in the human fovea: Do normal optical aberrations and fixational eye movements have an effect?

Psychophysical inferences about the neural mechanisms supporting spatial vision can be undermined by uncertainties introduced by optical aberrations and fixational eye movements, particularly in fovea where the neuronal grain of the visual system is fine. We examined the effect of these preneural factors on photopic spatial summation in the human fovea using a custom adaptive optics scanning light ophthalmoscope that provided control over optical aberrations and retinal stimulus motion. Consistent with previous results, Ricco's area of complete summation encompassed multiple photoreceptors when measured with ordinary amounts of ocular aberrations and retinal stimulus motion. When both factors were minimized experimentally, summation areas were essentially unchanged, suggesting that foveal spatial summation is limited by postreceptoral neural pooling. We compared our behavioral data to predictions generated with a physiologically-inspired front-end model of the visual system, and were able to capture the shape of the summation curves obtained with and without pre-retinal factors using a single postreceptoral summing filter of fixed spatial extent. Given our data and modeling, neurons in the magnocellular visual pathway, such as parasol ganglion cells, provide a candidate neural correlate of Ricco's area in the central fovea.

The Reliability of Cone Density Measurements in the Presence of Rods.

PURPOSE: Recent advances in adaptive optics scanning light ophthalmoscopy (AOSLO) have enabled visualization of cone inner segments through nonconfocal split-detection, in addition to rod and cone outer segments revealed by confocal reflectance. Here, we examined the interobserver reliability of cone density measurements in both AOSLO imaging modalities. METHODS: Five normal subjects (nine eyes) were imaged along the horizontal and vertical meridians using a custom AOSLO with confocal and nonconfocal split-detection modalities. The resulting images were montaged using a previously described semiautomatic algorithm. Regions of interest (ROIs) were selected from the confocal montage at 190 µm, and from split-detection and confocal montages at 900 and 1800 µm from the fovea. Four observers (three experts, one naïve) manually identified cone locations in each ROI, and these locations were used to calculate bound densities. Intraclass correlation coefficients and Dice's coefficients were calculated to assess interobserver agreement. RESULTS: Interobserver agreement was high in cone-only images (confocal 190 µm: 0.85; split-detection 900 µm: 0.91; split-detection 1800 µm: 0.89), moderate in confocal images at 900 µm (0.68), and poor in confocal images at 1800 µm (0.24). Excluding the naïve observer data substantially increased agreement within confocal images (190 µm: 0.99; 900 µm: 0.80; 1800 µm: 0.68). CONCLUSIONS: Interobserver measurements of cone density are more reliable in rod-free retinal images. Moreover, when using manual cell identification, it is essential that observers are trained, particularly for confocal AOSLO images. TRANSLATIONAL RELEVANCE: This study underscores the need for additional reliability studies in eyes containing pathology where identifying cones can be substantially more difficult.

Erratum: Non-invasive assessment of human cone photoreceptor function: erratum.

[This corrects the article on p. 5098 in vol. 8, PMID: 29188106.].

Non-invasive assessment of human cone photoreceptor function.

Vision begins when light isomerizes the photopigments within photoreceptors. Noninvasive cellular-scale observation of the structure of the human photoreceptor mosaic is made possible through the use of adaptive optics (AO) enhanced ophthalmoscopes, but establishing noninvasive objective measures of photoreceptor function on a similar scale has been more difficult. AO ophthalmoscope images acquired with near-infrared light show that individual cone photoreceptor reflectance can change in response to a visible stimulus. Here we show that the intrinsic response depends on stimulus wavelength and intensity, and that its action spectrum is well-matched to the spectral sensitivity of cone-mediated vision. Our results demonstrate that the cone reflectance response is mediated by photoisomerization, thus making it a direct measure of photoreceptor function.