Observation of cone and rod photoreceptors in normal subjects and patients using a new generation adaptive optics scanning laser ophthalmoscope.

We demonstrate the capability of a new generation adaptive optics scanning laser ophthalmoscope (AOSLO) to resolve cones and rods in normal subjects, and confirm our findings by comparing cone and rod spacing with published histology measurements. Cone and rod spacing measurements are also performed on AOSLO images from two different diseased eyes, one affected by achromatopsia and the other by acute zonal occult outer retinopathy (AZOOR). The potential of AOSLO technology in the study of these and other retinal diseases is illustrated

Open Source Software for Automatic Detection of Cone Photoreceptors in Adaptive Optics Ophthalmoscopy Using Convolutional Neural Networks

Imaging with an adaptive optics scanning light ophthalmoscope (AOSLO) enables direct visualization of the cone photoreceptor mosaic in the living human retina. Quantitative analysis of AOSLO images typically requires manual grading, which is time consuming, and subjective; thus, automated algorithms are highly desirable. Previously developed automated methods are often reliant on ad hoc rules that may not be transferable between different imaging modalities or retinal locations. In this work, we present a convolutional neural network (CNN) based method for cone detection that learns features of interest directly from training data. This cone-identifying algorithm was trained and validated on separate data sets of confocal and split detector AOSLO images with results showing performance that closely mimics the gold standard manual process. Further, without any need for algorithmic modifications for a specific AOSLO imaging system, our fully-automated multi-modality CNN-based cone detection method resulted in comparable results to previous automatic cone segmentation methods which utilized ad hoc rules for different applications. We have made free open-source software for the proposed method and the corresponding training and testing datasets available online

Microscopic Inner Retinal Hyper-reflective Phenotypes in Retinal and Neurologic Disease

Purpose. We surveyed inner retinal microscopic features in retinal and neurologic disease using a reflectance confocal adaptive optics scanning light ophthalmoscope (AOSLO). Methods. Inner retinal images from 101 subjects affected by one of 38 retinal or neurologic conditions and 11 subjects with no known eye disease were examined for the presence of hyper-reflective features other than vasculature, retinal nerve fiber layer, and foveal pit reflex. The hyper-reflective features in the AOSLO images were grouped based on size, location, and subjective texture. Clinical imaging, including optical coherence tomography (OCT), scanning laser ophthalmoscopy, and fundus photography was analyzed for comparison. Results. Seven categories of hyper-reflective inner retinal structures were identified, namely punctate reflectivity, nummular (disc-shaped) reflectivity, granular membrane, waxy membrane, vessel-associated membrane, microcysts, and striate reflectivity. Punctate and nummular reflectivity also was found commonly in normal volunteers, but the features in the remaining five categories were found only in subjects with retinal or neurologic disease. Some of the features were found to change substantially between follow up imaging months apart. Conclusions. Confocal reflectance AOSLO imaging revealed a diverse spectrum of normal and pathologic hyper-reflective inner and epiretinal features, some of which were previously unreported. Notably, these features were not disease-specific, suggesting that they might correspond to common mechanisms of degeneration or repair in pathologic states. Although prospective studies with larger and better characterized populations, along with imaging of more extensive retinal areas are needed, the hyper-reflective structures reported here could be used as disease biomarkers, provided their specificity is studied further

A Smartphone-Based Tool for Rapid, Portable, and Automated Wide-Field Retinal Imaging.

Purpose:High-quality, wide-field retinal imaging is a valuable method for screening preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging. Methods:The system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multicolored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by nonophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity. Results:The system automatically generated 100° retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for diabetic retinopathy (DR) screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%. Conclusions:Automation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening. Translational Relevance:Enhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening

Cone Spacing Correlates With Retinal Thickness and Microperimetry in Patients With Inherited Retinal Degenerations.

PurposeTo determine whether high-resolution retinal imaging measures of macular structure correlate with visual function over 36 months in retinal degeneration (RD) patients and normal subjects.MethodsTwenty-six eyes of 16 RD patients and 16 eyes of 8 normal subjects were studied at baseline; 15 eyes (14 RD) and 11 eyes (6 normal) were studied 36 months later. Adaptive Optics Scanning Laser Ophthalmoscopy (AOSLO) was used to identify regions of interest (ROIs) with unambiguous cones at baseline to measure cone spacing. AOSLO images were aligned with spectral-domain optical coherence tomography (SD-OCT) and fundus-guided microperimetry results to correlate structure and function at the ROIs. SD-OCT images were segmented to measure inner segment (IS) and outer segment (OS) thickness. Correlations between cone spacing, IS and OS thickness and sensitivity were assessed using Spearman correlation coefficient ρ with bootstrap analyses clustered by person.ResultsCone spacing (ρ = 0.57, P < 0.001) and macular sensitivity (ρ = 0.19, P = 0.14) were significantly correlated with eccentricity in patients. Controlling for eccentricity, cone spacing Z-scores were inversely correlated with IS (ρ = -0.29, P = 0.002) and OS thickness (ρ = -0.39, P < 0.001) in RD patients only, and with sensitivity in normal subjects (ρ = -0.22, P < 0.001) and RD patients (ρ = -0.38, P < 0.001). After 36 months, cone spacing increased (P < 0.001) and macular sensitivity decreased (P = 0.007) compared to baseline in RD patients.ConclusionsCone spacing increased and macular sensitivity declined significantly in RD patients over 36 months. High resolution images of cone structure correlated with retinal sensitivity, and may be appropriate outcome measures for clinical trials in RD

Assessing Photoreceptor Structure Associated with Ellipsoid Zone Disruptions Visualized with Optical Coherence Tomography

Purpose: To compare images of photoreceptor layer disruptions obtained with optical coherence tomography (OCT) and adaptive optics scanning light ophthalmoscopy (AOSLO) in a variety of pathologic states.Methods: Five subjects with photoreceptor ellipsoid zone disruption as per OCT and clinical diagnoses of closed-globe blunt ocular trauma (n = 2), macular telangiectasia type 2 (n = 1), blue-cone monochromacy (n = 1), or cone-rod dystrophy (n = 1) were included. Images were acquired within and around photoreceptor lesions using spectral domain OCT, confocal AOSLO, and split-detector AOSLO.Results: There were substantial differences in the extent and appearance of the photoreceptor mosaic as revealed by confocal AOSLO, split-detector AOSLO, and spectral domain OCT en face view of the ellipsoid zone.Conclusion: Clinically available spectral domain OCT, viewed en face or as B-scan, may lead to misinterpretation of photoreceptor anatomy in a variety of diseases and injuries. This was demonstrated using split-detector AOSLO to reveal substantial populations of photoreceptors in areas of no, low, or ambiguous ellipsoid zone reflectivity with en face OCT and confocal AOSLO. Although it is unclear if these photoreceptors are functional, their presence offers hope for therapeutic strategies aimed at preserving or restoring photoreceptor function

Relationship Between the Foveal Avascular Zone and Foveal Pit Morphology

Purpose.To assess the relationship between foveal pit morphology and size of the foveal avascular zone (FAZ). Methods. Forty-two subjects were recruited. Volumetric images of the macula were obtained using spectral domain optical coherence tomography. Images of the FAZ were obtained using either a modified fundus camera or an adaptive optics scanning light ophthalmoscope. Foveal pit metrics (depth, diameter, slope, volume, and area) were automatically extracted from retinal thickness data, whereas the FAZ was manually segmented by two observers to extract estimates of FAZ diameter and area. Results. Consistent with previous reports, the authors observed significant variation in foveal pit morphology. The average foveal pit volume was 0.081 mm3 (range, 0.022 to 0.190 mm3). The size of the FAZ was also highly variable between persons, with FAZ area ranging from 0.05 to 1.05 mm2 and FAZ diameter ranging from 0.20 to 1.08 mm. FAZ area was significantly correlated with foveal pit area, depth, and volume; deeper and broader foveal pits were associated with larger FAZs. Conclusions. Although these results are consistent with predictions from existing models of foveal development, more work is needed to confirm the developmental link between the size of the FAZ and the degree of foveal pit excavation. In addition, more work is needed to understand the relationship between these and other anatomic features of the human foveal region, including peak cone density, rod-free zone diameter, and Henle fiber layer

Automatic Detection of Cone Photoreceptors In Split Detector Adaptive Optics Scanning Light Ophthalmoscope Images

Quantitative analysis of the cone photoreceptor mosaic in the living retina is potentially useful for early diagnosis and prognosis of many ocular diseases. Non-confocal split detector based adaptive optics scanning light ophthalmoscope (AOSLO) imaging reveals the cone photoreceptor inner segment mosaics often not visualized on confocal AOSLO imaging. Despite recent advances in automated cone segmentation algorithms for confocal AOSLO imagery, quantitative analysis of split detector AOSLO images is currently a time-consuming manual process. In this paper, we present the fully automatic adaptive filtering and local detection (AFLD) method for detecting cones in split detector AOSLO images. We validated our algorithm on 80 images from 10 subjects, showing an overall mean Dice’s coefficient of 0.95 (standard deviation 0.03), when comparing our AFLD algorithm to an expert grader. This is comparable to the inter-observer Dice’s coefficient of 0.94 (standard deviation 0.04). To the best of our knowledge, this is the first validated, fully-automated segmentation method which has been applied to split detector AOSLO images

Photoreceptor perturbation around subretinal drusenoid deposits as revealed by adaptive optics scanning laser ophthalmoscopy

PURPOSE: To describe the microscopic structure of photoreceptors impacted by subretinal drusenoid deposits, also called pseudodrusen, an extracellular lesion associated with age-related macular degeneration (AMD), using adaptive optics scanning laser ophthalmoscopy (AOSLO). DESIGN: Observational case series. METHODS: We recruited 53 patients with AMD and 10 age-similar subjects who had normal retinal health. All subjects underwent color fundus photography, infrared reflectance, red-free reflectance, autofluorescence, and spectral-domain optical coherence tomography (OCT). Subretinal drusenoid deposits were classified by a 3-stage OCT-based grading system. Lesions and surrounding photoreceptors were examined by AOSLO. RESULTS: Subretinal drusenoid deposits were found in 26 eyes of 13 patients with AMD and imaged by AOSLO and spectral-domain OCT in 18 eyes (n = 342 lesions). Spectral-domain OCT showed subretinal drusenoid deposits as highly reflective material accumulated internal to the retinal pigment epithelium. AOSLO revealed that photoreceptor reflectivity was qualitatively reduced by stage 1 subretinal drusenoid deposits and was greatly reduced by stage 2. AOSLO presented a distinct structure in stage 3, a hyporeflective annulus consisting of deflected, degenerated or absent photoreceptors. A central core with a reflectivity superficially resembling photoreceptors is formed by the lesion material itself. A hyporeflective gap in the photoreceptor ellipsoid zone on either side of this core shown in spectral-domain OCT corresponded to the hyporeflective annulus seen by AOSLO. CONCLUSIONS: AOSLO and multimodal imaging of subretinal drusenoid deposits indicate solid, space-filling lesions in the subretinal space. Associated retinal reflectivity changes are related to lesion stages and are consistent with perturbations to photoreceptors, as suggested by histology

Transscleral Optical Phase Imaging of the Human Retina.

In-vivo observation of the human retina at the cellular level is crucial to detect the first signs of retinal diseases and properly treat them. Despite the phenomenal advances in adaptive optics (AO) systems, clinical imaging of many retinal cells is still elusive due to the low signal-to-noise ratio induced by transpupillary illumination. We present a transscleral optical phase imaging (TOPI) method, which relies on high-angle oblique illumination of the retina, combined with AO, to enhance cell contrast. Examination of eleven healthy volunteer eyes, without pupil dilation, shows the ability of this method to produce in-vivo images of retinal cells, from the retinal pigment epithelium to the nerve fibre layer. This method also allows the generation of high-resolution label-free ex-vivo phase images of flat-mounted retinas. The 4.4°x 4.4° field-of-view in-vivo images are recorded in less than 10 seconds, opening new avenues in the exploration of healthy and diseased retinas