ImportanceIt is important to establish reliable outcome measures to detect progression in retinitis pigmentosa (RP).BackgroundTo evaluate progression of RP using multimodal imaging, including spectral‐domain optical coherence tomography (SD‐OCT), fundus autofluorescence (FAF) and microperimetry (MP).DesignRetrospective longitudinal study at a tertiary teaching hospital.Participants205 eyes of 106 patients with RP with 1 to 5 y of follow‐up.MethodsDemographics and visual acuity (VA) were recorded, and each modality was graded at baseline and every annual follow‐up. SD‐OCT was graded for the width of ellipsoid zone (EZ), FAF was graded for the diameter and area of the hyperautofluorescent ring (if present), and MP was graded for mean, central and paracentral sensitivity. Spearman's correlation was used to measure correlations at baseline. Mixed effects models were used to estimate the annual change of each parameter, adjusted for disease duration.Main Outcome MeasuresRate of progression.ResultsThe median VA at baseline was 75 letters and was positively correlated with mean and central sensitivity (r: 0.372 and 0.394; P = 0.01 for both). All parameters (except paracentral sensitivity) were strongly correlated with each other (r: 0.673‐0.991; P < 0.001 for all). The annual rates of change for each parameter were as follows: VA, −2.3 letters (P < 0.001); EZ, −151 μm (P < 0.001); ring diameter, −132 μm (P < 0.001); ring area, −0.4 mm2 (P < 0.001); mean sensitivity, −0.3 dB (P < 0.001); central sensitivity, −0.7 dB (P < 0.001); paracentral sensitivity, −0.4 dB (P < 0.001).Conclusions and RelevanceStructural and functional measures are well correlated in RP and can reliably measure disease progression within the course of a year.

Purpose To describe the feasibility of peripheral OCT imaging in retinal diseases using a novel full-field device. Methods A total of 134 consecutive eyes were referred and imaged on the Optos Silverstone swept-source OCT (SS-OCT) (Optos PLC; Dunfermline, UK). Scanning laser ophthalmoscope (SLO) images and the associated SS-OCT images were obtained in the posterior pole, mid-periphery or far periphery based on the nature of the referral and on new areas of interest observed in the optomap images at the time of imaging. Results A total of 134 eyes (96 patients) were enrolled in the study. One hundred and twenty-five eyes (91 patients) with 38 retinal pathologies were prospectively assessed and 9 eyes (5 patients) were excluded due to incomplete image acquisition. The average age of the subjects was 54 years (range 21–92 years). Thirty-nine out of 125 eyes (31%) had macular pathologies. Eighty-six out of 125 eyes (69%) had peripheral only pathologies, an area which cannot be visualized by standard OCT devices with a 50 degree field-of-view. Conclusions The ability to capture peripheral pathologies using an integrated SLO-UWF imaging with full-field swept-source provided high-grade anatomical insight that confirmed the medical and surgical management in a majority of cases. Its use in the mid- and far periphery provides a holistic clinical picture, which can potentially aid in the understanding of various retinal pathologies.

Purpose To Utilize OCT-A to measure the change in size (mm 2 ) and density (flow index) of choroidal neovascular membranes (CNVMs) from baseline to week 52 of treatment-naïve wet age-related macular degeneration (wARMD) patients receiving intravitreal aflibercept injections (IAI). Methods Patients were treated with IAI at baseline, month 1 and month 2 and then every other month for a total of 12 months. Along with clinical examination and best corrected visual acuity (BCVA), OCT-A 6and 3-mm scans were acquired at every visit between May 2017 and January 2019. Data from baseline, week 12 and week 52 were analyzed prospectively and included in the final analysis.Results Twenty-five eyes from 23 patients were included in the study. The mean BCVA at baseline and week 52 increased from 20/125 to 20/80, respectively (p \ 0.001). The mean CST at baseline and week 52 decreased from 330.48 to 222.40 lm, respectively (p \ 0.001). 1Seventeen patients (18 eyes) completed all protocol-based 6 9 6 mm and 3 9 3 mm OCT-A scans. In this subgroup, 6-mm OCT-A scans revealed that the mean size of the CNVM before and after IAI was 1.21 mm 2 and 0.56 mm 2 , respectively (p \ 0.001), while the 3-mm OCT-A scans at baseline and week 52 demonstrated a decrease in mean size of the CNVM from 0.89 to 0.37 mm 2 , respectively (p \ 0.001). The 6-mm perfusion density map revealed no difference at either time points. Conclusions OCT-A provides a useful approach for monitoring and evaluating the treatment of intravitreal aflibercept for CNVMs. Mean size of CNVMs can be identified by 3-or 6-mm scans, but without machine learning, it requires extensive segmentation. While reproducibility and clear delineation of CNVMs in wARMD using OCT-A is challenging, OCT-A does offer the ability to monitor CNVM size changes during treatment and may offer another biomarker to assist in assessing treatment response.

PurposeTo evaluate the performance of a deep learning-based, fully automated, multi-class, macular fluid segmentation algorithm relative to expert annotations in a heterogeneous population of confirmed wet age-related macular degeneration (wAMD) subjects.MethodsTwenty-two swept-source optical coherence tomography (SS-OCT) volumes of the macula from 22 from different individuals with wAMD were manually annotated by two expert graders. These results were compared using cross-validation (CV) to automated segmentations using a deep learning-based algorithm encoding spatial information about retinal tissue as an additional input to the network. The algorithm detects and delineates fluid regions in the OCT data, differentiating between intra- and sub-retinal fluid (IRF, SRF), as well as fluid resulting from in serous pigment epithelial detachments (PED). Standard metrics for fluid detection and quantification were used to evaluate performance.ResultsThe per slice receiver operating characteristic (ROC) area under the curves (AUCs) for each of these fluid types were 0.90, 0.94 and 0.94 for IRF, SRF and PED, respectively. Per volume results were 0.94 and 0.88 for IRF and PED (SRF being present in all cases). The correlation of fluid volume between the expert graders and the algorithm were 0.99 for IRF, 0.99 for SRF and 0.82 for PED.ConclusionsAutomated, deep learning-based segmentation is able to accurately detect and quantify different macular fluid types in SS-OCT data on par with expert graders.

Short-term improvements in retinal anatomy are known to occur in preclinical models of photoreceptor transplantation. However, correlative changes over the long term are poorly understood. We aimed to develop a quantifiable imaging biomarker grading scheme, using noninvasive multimodal confocal scanning laser ophthalmoscopy (cSLO) imaging, to enable serial evaluation of photoreceptor transplantation over the long term. Methods: Photoreceptor cell suspensions or sheets from rhodopsin-green fluorescent protein mice were transplanted subretinally, into either NOD.CB17-Prkdc scid /J or C3H/HeJ-Pde6b rd1 mice. Multimodal cSLO imaging was performed serially for up to three months after transplantation. Imaging biomarkers were scored, and a grade was defined for each eye by integrating the scores. Image grades were correlated with immunohistochemistry (IHC) data. Results: Multimodal imaging enabled the extraction of quantitative imaging biomarkers including graft size, GFP intensity, graft length, on-target graft placement, intra-graft lamination, hemorrhage, retinal atrophy, and periretinal proliferation. Migration of transplanted material was observed. Changes in biomarker scores and grades were detected in 14/16 and 7/16 eyes, respectively. A high correlation was found between image grades and IHC parameters. Conclusions: Serial evaluation of multiple imaging biomarkers, when integrated into a per-eye grading scheme, enabled comprehensive tracking of longitudinal changes in photoreceptor cell grafts over time. The application of systematic multimodal in vivo imaging could be useful in increasing the efficiency of preclinical retinal cell transplantation studies in rodents and other animal models. Translational Relevance: By allowing longitudinal evaluation of the same animal over time, and providing quantifiable biomarkers, non-invasive multimodal imaging improves the efficiency of retinal transplantation studies in animal models. Such assays will facilitate the development of cell therapy for retinal diseases.

We describe a novel large homozygous deletion in the RLBP1 gene encoding the cellular retinaldehyde-binding protein in a patient of Iranian descent with retinitis punctata albescens. Genotype-phenotype studies may provide more information about the functions of the RLBP1 encoding proteins and the disease course, because RLBP1 mutations are associated with high phenotypic variability and are therefore a necessity for future tailored individual therapies.

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Purpose To evaluate the predictive ability of a deep learning-based algorithm to determine long-term best-corrected distance visual acuity (BCVA) outcomes in neovascular age-related macular degeneration (nARMD) patients using baseline swept-source optical coherence tomography (SS-OCT) and OCT-angiography (OCT-A) data. Methods In this phase IV, retrospective, proof of concept, single center study, SS-OCT data from 17 previously treated nARMD eyes was used to assess retinal layer thicknesses, as well as quantify intraretinal fluid (IRF), subretinal fluid (SRF), and serous pigment epithelium detachments (PEDs) using a novel deep learning-based, macular fluid segmentation algorithm. Baseline OCT and OCT-A morphological features and fluid measurements were correlated using the Pearson correlation coefficient (PCC) to changes in BCVA from baseline to week 52. Results Total retinal fluid (IRF, SRF and PED) volume at baseline had the strongest correlation to improvement in BCVA at month 12 (PCC = 0.652, p = 0.005). Fluid was subsequently sub-categorized into IRF, SRF and PED, with PED volume having the next highest correlation (PCC = 0.648, p = 0.005) to BCVA improvement. Average total retinal thickness in isolation demonstrated poor correlation (PCC = 0.334, p = 0.189). When two features, mean choroidal neovascular membranes (CNVM) size and total fluid volume, were combined and correlated with visual outcomes, the highest correlation increased to PCC = 0.695 (p = 0.002). Conclusions In isolation, total fluid volume most closely correlates with change in BCVA values between baseline and week 52. In combination with complimentary information from OCT-A, an improvement in the linear correlation score was observed. Average total retinal thickness provided a lower correlation, and thus provides a lower predictive outcome than alternative metrics assessed. Clinically, a machine-learning approach to analyzing fluid metrics in combination with lesion size may provide an advantage in personalizing therapy and predicting BCVA outcomes at week 52.