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Michael Chaglasian,1 Murray Fingeret,2 Pinakin Gunvant Davey,3 Wei-Chieh Huang,4 Danny Leung,4 Edmund Ng,5 Charles A Reisman4 1Illinois Eye Institute, Illinois College of Optometry, Chicago, IL, USA; 2Department of Veterans Affairs, New York Harbor Health Care System, Brooklyn, NY, USA; 3School of Optometry, Western University of Health Sciences, Pomona, CA, USA; 4Topcon Healthcare Solutions Research and Development, Oakland, NJ, USA; 5Edmund Ng Consulting, LLC, Seattle, WA, USA Importance: The paper presents the range for measurements taken with a new spectral domain optical coherence tomography (OCT) device to establish a reference database for discrimination purposes. Objective: To report the range of thickness values for the new Topcon Maestro 3D OCT device with 2 scan size settings: the 12×9 mm wide field and 6×6 mm scans. Design: Prospective, multicenter cohort study conducted at 7 clinical sites across the USA. Setting: Primary eyecare clinics within academic, hospital, and private practice locations. Participants: Healthy volunteers; all enrolled participants underwent a complete ophthalmological examination to confirm healthy ocular status prior to being enrolled in the study. Main outcome measure: Average and 1st, 5th, 95th, and 99th percentile ranges for OCT parameters Early Treatment Diabetic Retinopathy Study macula full retinal thickness, ganglion cell + inner plexiform layer thickness (GCL + IPL), ganglion cell complex (GCC) thickness, circumpapillary retinal nerve fiber layer (cpRNFL) thickness. Results: Three hundred and ninety-nine eyes of 399 subjects were included in the analysis. Mean (SD) age was 46.3 (16.3) years (range 18–88 years). Forty-three percent of the subjects were male. Mean (SD) measurements (in μm) for the 12×9 mm wide scan were as follows: foveal thickness=237.079 (20.899), GCL + IPL=71.363 (5.924), GCC=105.949 (8.533), cpRNFL=104.720 (11.829); measurements for the 6×6 mm scans were as follows: foveal thickness=234.000 (20.657), GCL + IPL=71.726 (5.880), GCC=106.698 (9.094), cpRNFL=104.036 (11.341). Conclusion: The overall normal thickness values reported with Topcon 3D OCT-1 Maestro were like those studies with OCT from different manufactures. The reference limits at the 1st, 5th, 95th, and 99th percentile points establish the thresholds for the quantitative comparison of the cpRNFL and the macula in the human retina to a database of known healthy subjects. Keywords: spectral domain optical coherence tomography, normal eyes, 3D OCT-1 Maestro, macular measurements, circumpapillary retinal nerve fiber layer, optic disc

Optical Coherence Tomography (OCT) enables non-invasive imaging of the retina and is used to diagnose and manage ophthalmic diseases including glaucoma. We present the first large-scale genome-wide association study of inner retinal morphology using phenotypes derived from OCT images of 31,434 UK Biobank participants. We identify 46 loci associated with thickness of the retinal nerve fibre layer or ganglion cell inner plexiform layer. Only one of these loci has been associated with glaucoma, and despite its clear role as a biomarker for the disease, Mendelian randomisation does not support inner retinal thickness being on the same genetic causal pathway as glaucoma. We extracted overall retinal thickness at the fovea, representative of foveal hypoplasia, with which three of the 46 SNPs were associated. We additionally associate these three loci with visual acuity. In contrast to the Mendelian causes of severe foveal hypoplasia, our results suggest a spectrum of foveal hypoplasia, in part genetically determined, with consequences on visual function., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: APK is a paid consultant to Aerie, Allergan, Google Health, Novartis, Reichert, Santen and Thea. LRP is consultant for Verily, Eyenovia, Bausch+Lomb, and Nicox. JW is consultant for Allergan, Editas, Maze, Regenxbio and has a sponsored research grant from Aerpio.

Purpose: To describe associations of ocular and systemic factors with retinal pigment epithelium (RPE)-Bruch's membrane (BM) complex thickness as measured by spectral-domain (SD) optical coherence tomography (OCT)., Design: Multisite community-based study. This research has been conducted using the UK Biobank Resource., Participants: Sixty-seven thousand three hundred eighteen people 40 to 69 years old received questionnaires, physical examination, and eye examination, including macular SD OCT. Systematic selection process identified 34 652 eyes with high-quality SD OCT images from normal individuals for analysis., Methods: We included people with no self-reported ocular disease, diabetes, or neurologic disorders; visual acuity of ≥20/25; refraction between -6 diopters (D) to 6 D, and IOP of 6 to 21 mmHg. Only high-quality, well-centered SD OCT images with central, stable fixation were included. Descriptive statistics, t tests, and regression analyses were performed. Multivariate regression modeling was used to adjust for covariates and to identify relationships between RPE-BM thickness and ocular and systemic features., Main Outcome Measures: Retinal pigment epithelium-BM thickness, as measured by SD OCT segmentation using Topcon Advanced Boundary Segmentation at 9 Early Treatment of Diabetic Retinopathy Study subfields., Results: Mean RPE-BM thickness was 26.3 μm (standard deviation, 4.8 μm) at central subfield. Multivariate regression with age stratification showed that RPE thinning became apparent after age 45. Among those aged ≤45, RPE-BM was significantly thicker among those of black or mixed/other race (+3.61 and +1.77 μm vs. white, respectively; P < 0.001) and higher hyperopia (+0.4 μm/D; P < 0.001), but not for other variables considered. Among those age >45, RPE-BM was significantly thinner with older age (-0.10 μm/year; P < 0.001), Asian ethnicity (-0.45 μm vs. white; P = 0.02), taller height (-0.02 μm/cm; P < 0.001), higher IOP (-0.03 μm/mmHg; P < 0.001), and regular smoking (-0.27 μm vs. nonsmokers; P = 0.02). In contrast, RPE-BM was significantly thicker among black or mixed/other race (+3.29 μm and +0.81 μm vs. white, respectively; P < 0.001) and higher hyperopia (+0.28 μm/D; P < 0.001). There was no significant association with sex or Chinese ethnicity., Conclusions: We describe novel findings of RPE-BM thickness in normal individuals, a structure that varies with age, ethnicity, refraction, IOP, and smoking. The significant association with IOP is especially interesting and may have relevance for the etiology of glaucoma, while the association between age and smoking may have relevance for the etiology of age-related macular degeneration., (Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness., Methods: In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available "spectral domain" OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion., Results: 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days., Conclusions: We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging., Competing Interests: Charles A. Reisman and Qi Yang are both employed by Topcon Medical Systems, Inc. Other than this employment relationship, Topcon has not funded or sponsored this research in any way and furthermore, this relationship does not affect or alter the authors' adherence to PLOS journals’ data sharing or materials policies.

Purpose: To derive macular thickness measures and their associations by performing rapid, automated segmentation of spectral-domain optical coherence tomography (SD OCT) images collected and stored as part of the UK Biobank (UKBB) study., Design: Large, multisite cohort study in the United Kingdom. Analysis of cross-sectional data., Participants: Adults from the United Kingdom aged 40 to 69 years., Methods: Participants had nonmydriatic SD OCT (Topcon 3D OCT-1000 Mark II; Topcon GB, Newberry, Berkshire, UK) performed as part of the ocular assessment module. Rapid, remote, automated segmentation of the images was performed using custom optical coherence tomography (OCT) image analysis software (Topcon Advanced Boundary Segmentation [TABS]; Topcon GB) to generate macular thickness values. We excluded people with a history of ocular or systemic disease (diabetes or neurodegenerative diseases) and eyes with reduced vision (<0.1 logarithm of the minimum angle of resolution) or with low SD OCT signal-to-noise ratio and low segmentation success certainty., Main Outcome Measures: Macular thickness values across 9 Early Treatment of Diabetic Retinopathy Study (ETDRS) subfields., Results: The SD OCT scans of 67 321 subjects were available for analysis, with 32 062 people with at least 1 eye meeting the inclusion criteria. There were 17 274 women and 14 788 men, with a mean (standard deviation [SD]) age of 55.2 (8.2) years. The mean (SD) logarithm of the minimum angle of resolution visual acuity was -0.075 (0.087), and the refractive error was -0.071 (+1.91) diopters (D). The mean (SD) central macular thickness (CMT) in the central 1-mm ETDRS subfield was 264.5 (22.9) μm, with 95% confidence limits of 220.8 and 311.5 μm. After adjusting for covariates, CMT was positively correlated with older age, female gender, greater myopia, smoking, body mass index (BMI), and white ethnicity (all P < 0.001). Of note, macular thickness in other subfields was negatively correlated with older age and greater myopia., Conclusions: We report macular thickness data derived from SD OCT images collected as part of the UKBB study and found novel associations among older age, ethnicity, BMI, smoking, and macular thickness., (Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: To improve the detection of glaucoma, techniques for assessing local patterns of damage and for combining structure and function were developed., Methods: Standard automated perimetry (SAP) and frequency-domain optical coherence tomography (fdOCT) data, consisting of macular retinal ganglion cell plus inner plexiform layer (mRGCPL) as well as macular and optic disc retinal nerve fiber layer (mRNFL and dRNFL) thicknesses, were collected from 52 eyes of 52 healthy controls and 156 eyes of 96 glaucoma suspects and patients. In addition to generating simple global metrics, SAP and fdOCT data were searched for contiguous clusters of abnormal points and converted to a continuous metric (pcc). The pcc metric, along with simpler methods, was used to combine the information from the SAP and fdOCT. The performance of different methods was assessed using the area under receiver operator characteristic curves (AROC scores)., Results: The pcc metric performed better than simple global measures for both the fdOCT and SAP. The best combined structure-function metric (mRGCPL&SAP pcc, AROC = 0.868 ± 0.032) was better (statistically significant) than the best metrics for independent measures of structure and function. When SAP was used as part of the inclusion and exclusion criteria, AROC scores increased for all metrics, including the best combined structure-function metric (AROC = 0.975 ± 0.014)., Conclusions: A combined structure-function metric improved the detection of glaucomatous eyes. Overall, the primary sources of value-added for glaucoma detection stem from the continuous cluster search (the pcc), the mRGCPL data, and the combination of structure and function.

To provide a tool for quantifying the effects of retinitis pigmentosa (RP) seen on spectral domain optical coherence tomography images, an automated layer segmentation algorithm was developed. This algorithm, based on dual-gradient information and a shortest path search strategy, delineates the inner limiting membrane and three outer retinal boundaries in optical coherence tomography images from RP patients. In addition, an automated inner segment (IS)/outer segment (OS) contour detection method based on the segmentation results is proposed to quantify the locus of points at which the OS thickness goes to zero in a 3D volume scan. The segmentation algorithm and the IS/OS contour were validated with manual segmentation data. The segmentation and IS/OS contour results on repeated measures showed good within-day repeatability, while the results on data acquired on average 22.5 months afterward demonstrated a possible means to follow disease progression. In particular, the automatically generated IS/OS contour provided a possible objective structural marker for RP progression.

A novel automated boundary segmentation algorithm is proposed for fast and reliable quantification of nine intra-retinal boundaries in optical coherence tomography (OCT) images. The algorithm employs a two-step segmentation schema based on gradient information in dual scales, utilizing local and complementary global gradient information simultaneously. A shortest path search is applied to optimize the edge selection. The segmentation algorithm was validated with independent manual segmentation and a reproducibility study. It demonstrates high accuracy and reproducibility in segmenting normal 3D OCT volumes. The execution time is about 16 seconds per volume (480x512x128 voxels). The algorithm shows potential for quantifying images from diseased retinas as well.