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Introduction: Optical coherence tomography (OCT) is a commonly used imaging modality that provides detailed cross-sectional retinal images. This has revolutionised management of neovascular age-related macular degeneration. The need for repeated anti-vascular endothelial growth factor injections has led to therapy being delivered using OCT-guided retreatment strategies with both qualitative OCT features of disease activity (e.g. macular fluid) and changes in retinal thickness as triggers for retreatment The purpose of this study is to determine the intra-session repeatability of retinal thickness and volume measurements using the Topcon 3DOCT-1000 spectral-domain optical coherence tomography (SDOCT) device in patients with neovascular age-related macular degeneration (nAMD). This is the largest study to date looking specifically at the Topcon 3DOCT-1000. Materials and Methods: Two SDOCT raster scans were performed by the same blinded observer in the same sitting in consecutive patients attending for nAMD treatment as part of standard validation of a new device. Retrospective analysis was undertaken, with retinal thickness and volume measurements automatically calculated by the onboard software for each Early Treatment of Diabetic Retinopathy Study subfield for each scan. Bland-Altman methods of analysis were used to assess repeatability. Results: Data from the 73 patients were analyzed with a mean age of 78 years (standard deviation 8). The 95% coefficient of repeatability (CR) was 64 μm and 0.050 mm 3 for retinal thickness and volume respectively in the central 1 mm macular subfield. The CR did not exceed 85 μm (0.30 mm 3 ) in any subfield. The revised CR for retinal thickness and volume for the subgroup of 37 patients with no segmentation error in the central 1 mm subfield was 53 μm and 0.050 mm 3 respectively. Discussion : We report relatively modest intra-sessional repeatability of SDOCT retinal thickness and volume metrics in patients with nAMD in a clinical setting. Though useful in detecting clinical change from measurement variability in clinical practice, these results suggest the precision of macular thickness measurement does not approach the theoretical resolution of SDOCT.

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis.

Ocular angiogenesis and macular oedema are major causes of sight loss across the world. Aberrant neovascularisation, which may arise secondary to numerous disease processes, can result in reduced vision as a result of oedema, haemorrhage, and scarring. The development of antivascular endothelial growth factor (anti-VEGF) agents has revolutionised the treatment of retinal vasogenic conditions. These drugs are now commonly employed for the treatment of a plethora of ocular pathologies including choroidal neovascularisation, diabetic macular oedema, and retinal vein occlusion to name a few. In this paper, we will explore the current use of anti-VEGF in a variety of retinal diseases and the impact that these medications have had on visual outcome for patients.

Retinopathy of prematurity (ROP) is a disease of premature infants and a leading worldwide cause of child blindness [1]. An epidemic of ROP occurred between 1941 and 1953, when an estimated 12,000 infants in affluent countries suffered visual loss from ROP. The first case of ROP, known then as retrolental fibroplasia (RLF), was identified in 1942 [2] with likely total retinal detachment [1]. However, RLF is currently applied to describe later stage cicatricial (severe retinal scarring) disease with retinal detachment and formation of retrolental fibro‐ plastic membrane [2]. It is likely that the severe, advanced disease stage of RLF would have been more readily identifiable in 1942, in the absence of technological advancements that have added precision and clarity to ophthalmic diagnosis. Cases of ROP were reported throughout the developed world over the following decade. Intensive oxygen therapy as the key deter‐ minant of ROP was not known until the early 1950s when the suggestion of oxygen toxicity in ROP was made.

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is neovascularisation, the growth of abnormal new vessels. This paper describes an automated method for the detection of new vessels in retinal images. Two vessel segmentation approaches are applied, using the standard line operator and a novel modified line operator. The latter is designed to reduce false responses to non-vessel edges. Both generated binary vessel maps hold vital information which must be processed separately. This is achieved with a dual classification system. Local morphology features are measured from each binary vessel map to produce two separate feature sets. Independent classification is performed for each feature set using a support vector machine (SVM) classifier. The system then combines these individual classification outcomes to produce a final decision. Sensitivity and specificity results using a dataset of 60 images are 0.862 and 0.944 respectively on a per patch basis and 1.00 and 0.90 respectively on a per image basis.

Diabetic retinopathy (DR) is a retinal vascular disease and is one of the most common causes of blindness worldwide. Proliferative diabetic retinopathy (PDR) is the most advanced stage of the disease and poses a high risk of severe visual impairment. PDR is characterised by the growth of abnormal new vessels known as neovascularisation. In this paper, we propose the use of the matched filter (MF) technique for vessel segmentation with emphasis on using two different sets of parameters to allow for the detection of new vessels. Parameters are selected to first increase and then decrease the MF response to new vessels, followed by thresholding to produce two separate binary vessel maps. The difference image removes most normal vessels and retains all possible new vessels, therefore making further analysis a much simpler task. Several steps are also included to reduce the detection of non vessel objects (dark and bright lesions). Five local features associated with the morphology of the vasculature are used to create a feature set. Based on these features, regions of the retina are categorized as normal or abnormal using a k-nearest neighbour classifier. Sensitivity and specificity results were 100% and 70% respectively on a per image basis.

Retinal detachment is a potentially blinding condition. It is caused by separation of neurosensory retina from the underlying retinal pigment epithelium. Despite treatment advances, functional results remain poor (with only 42% achieving 6/12 vision and only 28% if the macula is involved). There are three distinct types of retinal detachment: rhegmatogenous (RRD), tractional and exudative. For the purpose of this chapter we will focus on RRD.

IntroductionDiabetic macular edema (DME) is an important cause of vision loss. England has a national systematic photographic retinal screening programme to identify patients with diabetic eye disease. Grading retinal photographs according to this national protocol identifies surrogate markers for DME. We audited a care pathway using a spectral-domain optical coherence tomography (SDOCT) clinic to identify macular pathology in this subset of patients.MethodsA prospective audit was performed of patients referred from screening with mild to moderate non-proliferative diabetic retinopathy (R1) and surrogate markers for diabetic macular edema (M1) attending an SDOCT clinic. The SDOCT images were graded by an ophthalmologist as SDOCT positive, borderline or negative. SDOCT positive patients were referred to the medical retina clinic. SDOCT negative and borderline patients were further reviewed in the SDOCT clinic in 6 months.ResultsFrom a registered screening population of 17 551 patients with diabetes mellitus, 311 patients met the inclusion criteria between (March 2008 and September 2009). We analyzed images from 311 patients' SDOCT clinic episodes. There were 131 SDOCT negative and 12 borderline patients booked for revisit in the OCT clinic. Twenty-four were referred back to photographic screening for a variety of reasons. A total of 144 were referred to ophthalmology with OCT evidence of definite macular pathology requiring review by an ophthalmologist.DiscussionThis analysis shows that patients with diabetes, mild to moderate non-proliferative diabetic retinopathy (R1) and evidence of diabetic maculopathy on non-stereoscopic retinal photographs (M1) have a 42.1% chance of having no macular edema on SDOCT imaging as defined by standard OCT definitions of DME when graded by a retinal specialist. SDOCT imaging is a useful adjunct to colour fundus photography in screening for referable diabetic maculopathy in our screening population.

Optic nerve assessment is important for many blinding diseases, with cup-to-disc ratio (CDR) assessments commonly used in both diagnosis and progression monitoring of glaucoma patients. Optic disc, cup, rim area and CDR measurements all show substantial variation between human populations and high heritability estimates within populations. To identify loci underlying these quantitative traits, we performed a genome-wide association study in two Australian twin cohorts and identified rs3858145, P = 6.2 × 10−10, near the ATOH7 gene as associated with the mean disc area. ATOH7 is known from studies in model organisms to play a key role in retinal ganglion cell formation. The association with rs3858145 was replicated in a cohort of UK twins, with a meta-analysis of the combined data yielding P = 3.4 × 10−10. Imputation further increased the evidence for association for several SNPs in and around ATOH7 (P = 1.3 × 10−10 to 4.3 × 10−11, top SNP rs1900004). The meta-analysis also provided suggestive evidence for association for the cup area at rs690037, P = 1.5 × 10−7, in the gene RFTN1. Direct sequencing of ATOH7 in 12 patients with optic nerve hypoplasia, one of the leading causes of blindness in children, revealed two novel non-synonymous mutations (Arg65Gly, Ala47Thr) which were not found in 90 unrelated controls (combined Fisher's exact P = 0.0136). Furthermore, the Arg65Gly variant was found to have very low frequency (0.00066) in an additional set of 672 controls.