Purpose To investigate whether intraoperative retinal changes during epiretinal membrane (ERM) peeling affect anatomic or functional outcomes after surgery. Methods We measured retinal thickness using an intraoperative optical coherence tomography (iOCT) device in patients undergoing pars plana vitrectomy with membrane peeling for idiopathic ERM. Changes in intraoperative central macular thickness (iCMT) were compared with postoperative improvements in CMT and best-corrected visual acuity (VA). Results Twenty-seven eyes from 27 patients (mean age 68 years) underwent iOCT-assisted ERM peeling surgery. Before surgery, mean VA was logMAR 0.50 ± 0.36 (Snellen 20/63), and mean baseline CMT was 489 ± 82 µm. Mean iCMT before peeling was 477 ± 87 µm, which correlated well with preoperative CMT (P < 0.001). Mean change in iCMT was −39.6 ± 37 µm (range −116 to +77 µm). After surgery, VA improved to logMAR 0.40 ± 0.38 (Snellen 20/50) at month 1 and logMAR 0.27 ± 0.23 (Snellen 20/37) at month 3, whereas CMT decreased to 397 ± 44 µm and 396 ± 51 µm at months 1 and 3. Eyes that underwent greater amount of iCMT change (absolute value of iCMT change) were associated with greater CMT reduction at month 1 (P < 0.001) and month 3 (P = 0.010), whereas those with greater intraoperative thinning (actual iCMT change) showed a trend toward better VA outcomes at months 1 (P = 0.054) and 3 (P = 0.036). Conclusions Intraoperative changes in retinal thickness may predict anatomic and visual outcomes after idiopathic ERM peeling surgery. Translational Relevance Our study suggests that intraoperative retinal tissue response to ERM peeling surgery measured by iOCT may be a prognostic indicator for restoration of retinal architecture and for visual acuity outcomes.

Purpose To employ quantitative fundus autofluorescence (qAF) imaging in rhesus macaques to noninvasively assess retinal pigment epithelial (RPE) lipofuscin in nonhuman primates (NHPs) as a model of aging and age-related macular degeneration (AMD). Methods The qAF imaging was performed on eyes of 26 rhesus macaques (mean age 18.8 ± 8.2 years, range 4–27 years) with normal-appearing fundus or with age-related soft drusen using a confocal scanning laser ophthalmoscope with 488 nm excitation and an internal fluorescence reference. Eyes with soft drusen also underwent spectral-domain optical coherence tomography imaging to measure drusen volume and height of individual drusen lesions. The qAF levels were measured from the perifoveal annular ring (quantitative autofluorescence 8 [qAF8]) using the Delori grid, as well as focally over individual drusen lesions in this region. The association between qAF levels and age, sex, and drusen presence and volume were determined using multivariable regression analysis. Results Mean qAF levels increased with age (P < 0.001) and were higher in females (P = 0.047). Eyes with soft drusen exhibited reduced mean qAF compared with age-matched normal eyes (P = 0.003), with greater drusen volume showing a trend toward decreased qAF levels. However, qAF levels are focally increased over most individual drusen (P < 0.001), with larger drusen appearing more hyperautofluorescent (R2 = 0.391, P < 0.001). Conclusions In rhesus macaques, qAF levels are increased with age and female sex, but decreased in eyes with soft drusen, similar to human AMD. However, drusen lesions appear hyperautofluorescent unlike those in humans, suggesting similarities and differences in RPE lipofuscin between humans and NHPs that may provide insight into drusen biogenesis and AMD pathogenesis.

Purpose:To characterize the evolution and structure of soft drusen in aged rhesus macaques using in vivo multimodal retinal imaging and ex vivo histologic and ultrastructural analyses as a nonhuman primate model of early age-related macular degeneration (AMD).Methods:Multimodal imaging including fundus photography, spectral domain optical coherence tomography (SD-OCT), and fundus autofluorescence (FAF) were used to characterize and track individual drusen lesions in 20 aged rhesus macaques (mean age 23.3 ± 2.7 years) with drusenoid lesions over 2 years, followed by semithin histologic analysis and transmission electron microscopy (TEM).Results:Although most drusen gradually increased in size, a portion spontaneously regressed or collapsed over 2 years. Histologic analyses showed that soft drusen exhibit hypertrophy and dysmorphia of overlying retinal pigment epithelium (RPE), as seen in early and intermediate AMD, but do not exhibit RPE atrophy, RPE migration, or photoreceptor degeneration characteristic of advanced AMD. Ultrastructure of soft drusen showed abundant lipid particles within Bruch's membrane and AMD-related basal linear deposits (BlinD) resembling those in human drusen.Conclusions:The dynamic remodeling, histologic findings, and ultrastructural features of soft drusen in aged rhesus macaques support nonhuman primates as an animal model of early AMD and reveal important insights into drusen biogenesis and AMD development.

Non-confocal adaptive optics scanning laser ophthalmoscopy (AOSLO) has enhanced the study of human retinal photoreceptors by providing complementary information to standard confocal AOSLO images. Previously we developed the first confocal handheld AOSLO (HAOSLO) capable of in vivo cone photoreceptor imaging in supine and non-cooperative patients. Here, we introduce the first multimodal (M-)HAOSLO for confocal and non-confocal split-detection (SD) imaging to allow for more comprehensive patient data collection. Aside from its unprecedented miniature size and weight, M-HAOSLO is also the first system to perform sensorless wavefront-corrected SD imaging of cone photoreceptors.

Adaptive optics scanning laser ophthalmoscopy (AOSLO) has advanced the study of retinal structure and function by enabling in vivo imaging of individual photoreceptors. Most implementations of AOSLOs are large, complex tabletop systems, thereby preventing high quality photoreceptor imaging of patients who are unable to sit upright and/or fixate for an imaging session. We have previously addressed this limitation in the clinical translation of AOSLO by developing the first confocal handheld AOSLO (HAOSLO) capable of cone photoreceptor visualization in adults and infants. However, confocal AOSLO images suffer from imaging artifacts and the inability to detect remnant cone structure, leading to ambiguous or potentially misleading results. Recently, it has been shown that non-confocal split-detection (SD) AOSLO images, created by the collection of multiply backscattered light, enables more reliable studies of retinal photoreceptors by providing images of the cone inner segment. In this paper, we detail the extension of our HAOSLO probe to enable multi-channel light collection resulting in the first ever multimodal handheld AOSLO (M-HAOSLO). Imaging sessions were conducted on two dilated, healthy human adult volunteers, and M-HAOSLO images taken in handheld operation mode reveal the cone photoreceptor mosaic. Aside from being the first miniaturized and portable implementation of a SD AOSLO system, M-HAOSLO relies on sensorless optimization of the wavefront to correct aberrations. Thus, we also show the first ever SD images collected after correction of the eye’s estimated wavefront.

Age-related macular degeneration (AMD) - the leading cause of vision loss in the elderly - share many risks factors as atherosclerosis, which exhibits loss of vascular compliance resulting from aging and oxidative stress. Here, we attempt to explore choroidal and retinal vascular compliance in patients with AMD by evaluating dynamic vascular changes using live ocular imaging following treatment with oral sildenafil citrate, a phosphodiesterase type 5 (PDE5) inhibitor and potent vasodilator. Enhanced-depth imaging optical coherence tomography (EDI-OCT) and OCT angiography (OCT-A) were performed on 46 eyes of 23 subjects, including 15 patients with non-exudative AMD in one eye and exudative AMD in the fellow eye, and 8 age-matched control subjects. Choroidal thickness, choroidal vascularity, and retinal vessel density were measured across the central macula at 1 and 3 hours after a 100 mg oral dose of sildenafil citrate. Baseline choroidal thickness was 172.1 ± 60.0 μm in non-exudative AMD eyes, 196.4 ± 89.8 μm in exudative AMD eyes, and 207.4 ± 77.7 μm in control eyes, with no difference between the 3 groups (P = 0.116). After sildenafil, choroidal thickness increased by 6.0% to 9.0% at 1 and 3 hours in all groups (P = 0.001–0.014). Eyes from older subjects were associated with choroidal thinning at baseline (P = 0.005) and showed less choroidal expansion at 1 hour and 3 hours after sildenafil (P = 0.001) regardless of AMD status (P = 0.666). The choroidal thickening appeared to be primarily attributed to expansion of the stroma rather than luminal component. Retinal vascular density remained unchanged after sildenafil in all 3 groups (P = 0.281–0.587). Together, our studies suggest that vascular response of the choroid to sildenafil decreases with age, but is not affected by the presence of non-exudative or exudative AMD, providing insight into changes in vessel compliance in aging and AMD.

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.

Nonhuman primates are important preclinical models of retinal diseases because they uniquely possess a macula similar to humans. Ocular imaging technologies such as spectral-domain optical coherence tomography (SD-OCT) allow noninvasive, in vivo measurements of chorioretinal layers with near-histological resolution. However, the boundaries are based on differences in reflectivity, and detailed correlations with histological tissue layers have not been explored in rhesus macaques, which are widely used for biomedical research. Here, we compare the macular anatomy and thickness measurements of chorioretinal layers in rhesus macaque eyes using SD-OCT and high-resolution histological sections. Images were obtained from methylmethacrylate-embedded histological sections of 6 healthy adult rhesus macaques, and compared with SD-OCT images from 6 age-matched animals. Thicknesses of chorioretinal layers were measured across the central 3 mm macular region using custom semi-automated or manual software segmentation, and compared between the two modalities. We found that histological sections provide better distinction between the ganglion cell layer (GCL) and inner plexiform layer (IPL) than SD-OCT imaging. The first hyperreflective band between the external limiting membrane (ELM) and retinal pigment epithelium (RPE) appears wider on SD-OCT than the junction between photoreceptor inner and outer segments seen on histology. SD-OCT poorly distinguishes Henle nerve fibers from the outer nuclear layer (ONL), while histology correctly identifies these fibers as part of the outer plexiform layer (OPL). Overall, the GCL, inner nuclear layer (INL), and OPL are significantly thicker on histology, especially at the fovea; while the ONL, choriocapillaris (CC), and outer choroid (OC) are thicker on SD-OCT. Our results show that both SD-OCT and high-resolution histological sections allow reliable measurements of chorioretinal layers in rhesus macaques, with distinct advantages for different sublayers. These findings demonstrate the effects of tissue processing on chorioretinal anatomy, and provide normative values for chorioretinal thickness measurements on SD-OCT for future studies of disease models in these nonhuman primates.

Fast and reliable quantification of cone photoreceptors is a bottleneck in the clinical utilization of adaptive optics scanning light ophthalmoscope (AOSLO) systems for the study, diagnosis, and prognosis of retinal diseases. To-date, manual grading has been the sole reliable source of AOSLO quantification, as no automatic method has been reliably utilized for cone detection in real-world low-quality images of diseased retina. We present a novel deep learning based approach that combines information from both the confocal and non-confocal split detector AOSLO modalities to detect cones in subjects with achromatopsia. Our dual-mode deep learning based approach outperforms the state-of-the-art automated techniques and is on a par with human grading.

Photoreceptor ellipsoid zone (EZ) defects visible on optical coherence tomography (OCT) are important imaging biomarkers for the onset and progression of macular diseases. As such, accurate quantification of EZ defects is paramount to monitor disease progression and treatment efficacy over time. We developed and trained a novel deep learning-based method called Deep OCT Atrophy Detection (DOCTAD) to automatically segment EZ defect areas by classifying 3-dimensional A-scan clusters as normal or defective. Furthermore, we introduce a longitudinal transfer learning paradigm in which the algorithm learns from segmentation errors on images obtained at one time point to segment subsequent images with higher accuracy. We evaluated the performance of this method on 134 eyes of 67 subjects enrolled in a clinical trial of a novel macular telangiectasia type 2 (MacTel2) therapeutic agent. Our method compared favorably to other deep learning-based and non-deep learning-based methods in matching expert manual segmentations. To the best of our knowledge, this is the first automatic segmentation method developed for EZ defects on OCT images of MacTel2.

Purpose:To identify changes induced by environmental tobacco smoke (ETS) in circulatory microRNA (miRNA) in plasma and ocular fluids of the Rhesus macaque and compare these changes to normal age-related changes. Tobacco smoke has been identified as the leading environmental risk factor for age-related macular degeneration (AMD). Methods:All Rhesus macaques were housed at the California National Primate Research Center (CNPRC), University of California, Davis. Four groups of animals were used: Group 1 (1-3 years old), Group 2 (19-28 years old), Group 3 (10-16 years old), and Group 4 (middle aged, 9-14 years old). Group 4 was exposed to smoke for 1 month. Ocular fluids and plasma samples were collected, miRNAs isolated, and expression data obtained using Affymetrix miRNA GeneTitan Array Plates 4.0. Bioinformatics analysis was done on the Affymetrix Expression Console (EC), Transcriptome Analysis Software (TAS) using ANOVA for candidate miRNA selection, followed by Ingenuity Pathway Analysis (IPA). Results:The expression of circulatory miRNAs showed statistically significant changes with age and ETS. In the plasma samples, 45 miRNAs were strongly upregulated (fold change >±1.5, p<0.05) upon ETS exposure. In the vitreous, three miRNAs were statistically significantly downregulated with ETS, and two of them (miR-6794 and miR-6790) were also statistically significantly downregulated with age. Some retinal layers exhibited a thinning trend measured with optical coherence tomography (OCT) imaging. The pathways activated were IL-17A, VEGF, and recruitment of eosinophils, Th2 lymphocytes, and macrophages. Conclusions:ETS exposure of Rhesus macaques resulted in statistically significant changes in the expression of the circulatory miRNAs, distinct from those affected by aging. The pathways activated appear to be common for ETS and AMD pathogenesis. These data will be used to develop an animal model of early dry AMD.

PURPOSE:To determine if different types of retinal fluid in the central macula affect the reproducibility of choroidal thickness (CT) measurements on enhanced depth imaging optical coherence tomography (EDI-OCT). DESIGN:Retrospective reliability analysis. METHODS:EDI-OCT images were obtained and the choroidal-scleral junction was analyzed through semiautomated segmentation. CT was measured at the fovea and averaged across the central 3-mm horizontal segment. Demographic data, central macular thickness, and type of fluid present were recorded. Intragrader and intergrader repeatability were assessed using the intraclass correlation coefficient (ICC) and coefficient of repeatability (CR). RESULTS:Of 124 eyes analyzed, 60 (48.4%) had diabetic macular edema, 32 (25.8%) had neovascular age-related macular degeneration, and 32 (25.8%) had other causes of fluid. Intergrader ICC (CR) was 0.95 (74.1 μm) and 0.96 (63.9 μm) for subfoveal and average CT, respectively. CR was similar across various causes of retinal fluid, but was worst for subretinal fluid compared to intraretinal or sub-retinal pigment epithelial fluid. CR also worsened with increasing choroidal thickness, but was not affected by retinal thickness. Intragrader repeatability was generally greater than intergrader values, and followed the same trend. CONCLUSIONS:The presence of macular fluid reduces CT measurement reproducibility, particularly in eyes with subretinal fluid and greater choroidal thickness. A difference of 74.1 μm in subfoveal CT or 63.9 μm in average CT may be necessary to detect true clinical change in eyes with macular fluid.

We present a novel framework combining convolutional neural networks (CNN) and graph search methods (termed as CNN-GS) for the automatic segmentation of nine layer boundaries on retinal optical coherence tomography (OCT) images. CNN-GS first utilizes a CNN to extract features of specific retinal layer boundaries and train a corresponding classifier to delineate a pilot estimate of the eight layers. Next, a graph search method uses the probability maps created from the CNN to find the final boundaries. We validated our proposed method on 60 volumes (2915 B-scans) from 20 human eyes with non-exudative age-related macular degeneration (AMD), which attested to effectiveness of our proposed technique.

Optical coherence tomography (OCT) has revolutionized diagnosis and prognosis of ophthalmic diseases by visualization and measurement of retinal layers. To speed up the quantitative analysis of disease biomarkers, an increasing number of automatic segmentation algorithms have been proposed to estimate the boundary locations of retinal layers. While the performance of these algorithms has significantly improved in recent years, a critical question to ask is how far we are from a theoretical limit to OCT segmentation performance. In this paper, we present the Cramèr-Rao lower bounds (CRLBs) for the problem of OCT layer segmentation. In deriving the CRLBs, we address the important problem of defining statistical models that best represent the intensity distribution in each layer of the retina. Additionally, we calculate the bounds under an optimal affine bias, reflecting the use of prior knowledge in many segmentation algorithms. Experiments using in vivo images of human retina from a commercial spectral domain OCT system are presented, showing potential for improvement of automated segmentation accuracy. Our general mathematical model can be easily adapted for virtually any OCT system. Furthermore, the statistical models of signal and noise developed in this paper can be utilized for the future improvements of OCT image denoising, reconstruction, and many other applications.