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Cynomolgus monkeys exhibit human-like features, such as a fovea, so they are often used in non-clinical research. Nevertheless, little is known about the natural variation of the choroidal thickness in relation to origin and sex. A combination of deep learning and a deterministic computer vision algorithm was applied for automatic segmentation of foveolar optical coherence tomography images in cynomolgus monkeys. The main evaluation parameters were choroidal thickness and surface area directed from the deepest point on OCT images within the fovea, marked as the nulla with regard to sex and origin. Reference choroid landmarks were set underneath the nulla and at 500 µm intervals laterally up to a distance of 2000 µm nasally and temporally, complemented by a sub-analysis of the central bouquet of cones. 203 animals contributed 374 eyes for a reference choroid database. The overall average central choroidal thickness was 193 µm with a coefficient of variation of 7.8%, and the overall mean surface area of the central bouquet temporally was 19,335 µm 2 and nasally was 19,283 µm 2 . The choroidal thickness of the fovea appears relatively homogeneous between the sexes and the studied origins. However, considerable natural variation has been observed, which needs to be appreciated., (© 2022. The Author(s).)

Spatially-resolved retinal function can be measured by psychophysical testing like fundus-controlled perimetry (FCP or 'microperimetry'). It may serve as a performance outcome measure in emerging interventional clinical trials for macular diseases as requested by regulatory agencies. As FCP constitute laborious examinations, we have evaluated a machine-learning-based approach to predict spatially-resolved retinal function ('inferred sensitivity') based on microstructural imaging (obtained by spectral domain optical coherence tomography) and patient data in recessive Stargardt disease. Using nested cross-validation, prediction accuracies of (mean absolute error, MAE [95% CI]) 4.74 dB [4.48-4.99] were achieved. After additional inclusion of limited FCP data, the latter reached 3.89 dB [3.67-4.10] comparable to the test-retest MAE estimate of 3.51 dB [3.11-3.91]. Analysis of the permutation importance revealed, that the IS&OS and RPE thickness were the most important features for the prediction of retinal sensitivity. 'Inferred sensitivity', herein, enables to accurately estimate differential effects of retinal microstructure on spatially-resolved function in Stargardt disease, and might be used as quasi-functional surrogate marker for a refined and time-efficient investigation of possible functionally relevant treatment effects or disease progression.

Clinical science and medical imaging technology are traditionally displayed in two dimensions (2D) on a computer monitor. In contrast, three-dimensional (3D) virtual reality (VR) expands the realm of 2D image visualization, enabling an immersive VR experience with unhindered spatial interaction by the user. Thus far, analysis of data extracted from VR applications was mainly qualitative. In this study, we enhance VR and provide evidence for quantitative VR research by validating digital VR display of computed tomography (CT) data of the orbit. Volumetric CT data were transferred and rendered into a VR environment. Subsequently, seven graders performed repeated and blinded diameter measurements. The intergrader variability of the measurements in VR was much lower compared to measurements in the physical world and measurements were reasonably consistent with their corresponding elements in the real context. The overall VR measurements were 5.49% higher. As such, this study attests the ability of VR to provide similar quantitative data alongside the added benefit of VR interfaces. VR entails a lot of potential for the future research in ophthalmology and beyond in any scientific field that uses three-dimensional data.

Macular and cone/cone-rod dystrophies (MD/CCRD) demonstrate a broad genetic and phenotypic heterogeneity, with retinal alterations solely or predominantly involving the central retina. Targeted next-generation sequencing (NGS) is an efficient diagnostic tool for identifying mutations in patient with retinitis pigmentosa, which shows similar genetic heterogeneity. To detect the genetic causes of disease in patients with MD/CCRD, we implemented a two-tier procedure consisting of Sanger sequencing and targeted NGS including genes associated with clinically overlapping conditions. Disease-causing mutations were identified in 74% of 251 consecutive MD/CCRD patients (33% of the variants were novel). Mutations in ABCA4, PRPH2 and BEST1 accounted for 57% of disease cases. Further mutations were identified in CDHR1, GUCY2D, PROM1, CRX, GUCA1A, CERKL, MT-TL1, KIF11, RP1L1, MERTK, RDH5, CDH3, C1QTNF5, CRB1, JAG1, DRAM2, POC1B, NPHP1 and RPGR. We provide detailed illustrations of rare phenotypes, including autofluorescence and optical coherence tomography imaging. Targeted NGS also identified six potential novel genotype-phenotype correlations for FAM161A, INPP5E, MERTK, FBLN5, SEMA4A and IMPDH1. Clinical reassessment of genetically unsolved patients revealed subgroups with similar retinal phenotype, indicating a common molecular disease cause in each subgroup.