Local and Global Associations of Reticular Pseudodrusen in Age-Related Macular Degeneration.

PURPOSE: To investigate the spatial distribution of reticular pseudodrusen (RPD) in eyes with age-related macular degeneration (AMD) and their correlation with functional measures, retinal thickness, and changes over time. DESIGN: Longitudinal, cohort study. PARTICIPANTS: Thirty-five participants with RPD and spectrum of AMD severity (including no AMD). METHODS: Multimodal imaging was graded by a reading center, including evaluation of color fundus imaging to assess AMD severity scores. Reticular pseudodrusen presence on OCT volumes was confirmed on en face imaging and the RPD extent was contoured on infrared images. One study eye per participant underwent rod-mediated dark adaptation, measuring rod intercept time (RIT) at 5° and, if needed, 12° superior to the fovea. MAIN OUTCOME MEASURES: The primary outcome was RIT and OCT thickness measures which were correlated with RPD area. RESULTS: A total of 51 eyes had ≥ 1 visit with RPD detected (mean follow-up, 2.19 ± 2.04 years; range, 0-5 years), totaling 169 eye-based visits with RPD. Of the 51 eyes with RPD, 5 (9.8%) developed geographic atrophy and 17 (33.3%) progressed to neovascular AMD. Larger RPD areas were detected more frequently in AMD severity scores 6-7. Reticular pseudodrusen area within an eye generally increased over time. The lesion distribution showed a predilection for the superior retina, especially the outer superior subfield of the ETDRS grid, with the central subfield having least involvement. Reticular pseudodrusen area was inversely correlated with central subfield thickness and positively correlated with RIT at 5° (P = 0.001; r2 = 0.01) and 12° (P = 0.004; r2 = 0.01). Rod-mediated dark adaptation at 5° reached the test ceiling in > 85% of visits, irrespective of RPD lesion presence/absence at the test location. Retinal thickness decreased monotonically, with the central subfield demonstrating the greatest percentage change over 5 years (Δ = -5.47%). CONCLUSIONS: In AMD, RPD involve predominantly the superior retina but can involve all ETDRS subfields and evolve over time. Eyes with RPD exhibit structural and functional impairments that can be measured beyond the boundaries of the RPD lesions, suggesting changes associated with RPD are associated with both local changes and a more widespread process. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

RPGR: Deep Phenotyping and Genetic Characterization With Findings Specific to the 3'-end of ORF15.

Purpose: To describe a group of patients with retinitis pigmentosa GTPase regulator (RPGR)-related retinopathy with a tapetal-like retinal sheen and corresponding changes in the reflectivity of the ellipsoid zone on optical coherence tomography (OCT) imaging. Methods: A retrospective case series of 66 patients with a disease-causing variant in RPGR was performed. An expert examiner, masked to patient demographics, clinical evaluations, and specific RPGR variant, analyzed color fundus photographs for the presence of a tapetal-like retinal sheen and assessed OCT images for the presence of an abnormally broad hyper-reflective band in the outer retina. Longitudinal reflectivity profiles were generated and compared with healthy controls. Results: Twelve patients (18.2%) had a retinal sheen on color images that cosegregated with an abnormally broad hyper-reflective ellipsoid zone band on OCT imaging. Three-fourths of these patients were male, had a cone-rod dystrophy, and had pathogenic RPGR variants located toward the 3'-end of ORF15. This group had a different longitudinal reflectivity profile signature compared with controls. After a period of prolonged dark adaptation, the abnormal hyper-reflective band on OCT became less apparent, and the outer retinal layers adopted a more normal appearance. Conclusions: RPGR-related retinopathy should be considered for males presenting with retinal sheen, abnormal ellipsoid zone hyper-reflectivity, and cone or cone-rod dysfunction on ERG, and pursued with molecular testing. Our results have implications for understanding the role of the C-terminal domain encoded by RPGR ORF15 in the phototransduction cascade. Further, the findings may be important to incorporate into both inclusion criteria and outcome measure developments in future RPGR-related cone or cone-rod dystrophy clinical trials.

Retinal layer segmentation in optical coherence tomography (OCT) using a 3D deep-convolutional regression network for patients with age-related macular degeneration.

Introduction - Retinal layer segmentation in optical coherence tomography (OCT) images is an important approach for detecting and prognosing disease. Automating segmentation using robust machine learning techniques lead to computationally efficient solutions and significantly reduces the cost of labor-intensive labeling, which is traditionally performed by trained graders at a reading center, sometimes aided by semi-automated algorithms. Although several algorithms have been proposed since the revival of deep learning, eyes with severe pathological conditions continue to challenge fully automated segmentation approaches. There remains an opportunity to leverage the underlying spatial correlations between the retinal surfaces in the segmentation approach. Methods - Some of these proposed traditional methods can be expanded to utilize the three-dimensional spatial context governing the retinal image volumes by replacing the use of 2D filters with 3D filters. Towards this purpose, we propose a spatial-context, continuity and anatomical relationship preserving semantic segmentation algorithm, which utilizes the 3D spatial context from the image volumes with the use of 3D filters. We propose a 3D deep neural network capable of learning the surface positions of the layers in the retinal volumes. Results - We utilize a dataset of OCT images from patients with Age-related Macular Degeneration (AMD) to assess performance of our model and provide both qualitative (including segmentation maps and thickness maps) and quantitative (including error metric comparisons and volumetric comparisons) results, which demonstrate that our proposed method performs favorably even for eyes with pathological changes caused by severe retinal diseases. The Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for patients with a wide range of AMD severity scores (0-11) were within 0.84±0.41 and 1.33±0.73 pixels, respectively, which are significantly better than some of the other state-of-the-art algorithms. Conclusion - The results demonstrate the utility of extracting features from the entire OCT volume by treating the volume as a correlated entity and show the benefit of utilizing 3D autoencoder based regression networks for smoothing the approximated retinal layers by inducing shape based regularization constraints.