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Purpose: Application of artificial intelligence (AI) to macular OCT scans to segment and quantify volumetric change in anatomical and pathological features during intravitreal treatment for neovascular age-related macular degeneration (AMD)., Design: Retrospective analysis of OCT images from the Moorfields Eye Hospital AMD Database., Participants: A total of 2115 eyes from 1801 patients starting anti-VEGF treatment between June 1, 2012, and June 30, 2017., Methods: The Moorfields Eye Hospital neovascular AMD database was queried for first and second eyes receiving anti-VEGF treatment and had an OCT scan at baseline and 12 months. Follow-up scans were input into the AI system and volumes of OCT variables were studied at different time points and compared with baseline volume groups. Cross-sectional comparisons between time points were conducted using Mann-Whitney U test., Main Outcome Measures: Volume outputs of the following variables were studied: intraretinal fluid, subretinal fluid, pigment epithelial detachment (PED), subretinal hyperreflective material (SHRM), hyperreflective foci, neurosensory retina, and retinal pigment epithelium., Results: Mean volumes of analyzed features decreased significantly from baseline to both 4 and 12 months, in both first-treated and second-treated eyes. Pathological features that reflect exudation, including pure fluid components (intraretinal fluid and subretinal fluid) and those with fluid and fibrovascular tissue (PED and SHRM), displayed similar responses to treatment over 12 months. Mean PED and SHRM volumes showed less pronounced but also substantial decreases over the first 2 months, reaching a plateau postloading phase, and minimal change to 12 months. Both neurosensory retina and retinal pigment epithelium volumes showed gradual reductions over time, and were not as substantial as exudative features., Conclusions: We report the results of a quantitative analysis of change in retinal segmented features over time, enabled by an AI segmentation system. Cross-sectional analysis at multiple time points demonstrated significant associations between baseline OCT-derived segmented features and the volume of biomarkers at follow-up. Demonstrating how certain OCT biomarkers progress with treatment and the impact of pretreatment retinal morphology on different structural volumes may provide novel insights into disease mechanisms and aid the personalization of care. Data will be made public for future studies., Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (© 2024 by the American Academy of Ophthalmology.)

Importance: Despite widespread availability and consensus on its advantages for detailed imaging of geographic atrophy (GA), spectral-domain optical coherence tomography (SD-OCT) might benefit from automated quantitative OCT analyses in GA diagnosis, monitoring, and reporting of its landmark clinical trials., Objective: To analyze the association between pegcetacoplan and consensus GA SD-OCT end points., Design, Setting, and Participants: This was a post hoc analysis of 11 614 SD-OCT volumes from 936 of the 1258 participants in 2 parallel phase 3 studies, the Study to Compare the Efficacy and Safety of Intravitreal APL-2 Therapy With Sham Injections in Patients With Geographic Atrophy (GA) Secondary to Age-Related Macular Degeneration (OAKS) and Study to Compare the Efficacy and Safety of Intravitreal APL-2 Therapy With Sham Injections in Patients With Geographic Atrophy (GA) Secondary to Age-Related Macular Degeneration (DERBY). OAKS and DERBY were 24-month, multicenter, randomized, double-masked, sham-controlled studies conducted from August 2018 to July 2020 among adults with GA with total area 2.5 to 17.5 mm2 on fundus autofluorescence imaging (if multifocal, at least 1 lesion ≥1.25 mm2). This analysis was conducted from September to December 2023., Interventions: Study participants received pegcetacoplan, 15 mg per 0.1-mL intravitreal injection, monthly or every other month, or sham injection monthly or every other month., Main Outcomes and Measures: The primary end point was the least squares mean change from baseline in area of retinal pigment epithelium and outer retinal atrophy in each of the 3 treatment arms (pegcetacoplan monthly, pegcetacoplan every other month, and pooled sham [sham monthly and sham every other month]) at 24 months. Feature-specific area analysis was conducted by Early Treatment Diabetic Retinopathy Study (ETDRS) regions of interest (ie, foveal, parafoveal, and perifoveal)., Results: Among 936 participants, the mean (SD) age was 78.5 (7.22) years, and 570 participants (60.9%) were female. Pegcetacoplan, but not sham treatment, was associated with reduced growth rates of SD-OCT biomarkers for GA for up to 24 months. Reductions vs sham in least squares mean (SE) change from baseline of retinal pigment epithelium and outer retinal atrophy area were detectable at every time point from 3 through 24 months (least squares mean difference vs pooled sham at month 24, pegcetacoplan monthly: -0.86 mm2; 95% CI, -1.15 to -0.57; P < .001; pegcetacoplan every other month: -0.69 mm2; 95% CI, -0.98 to -0.39; P < .001). This association was more pronounced with more frequent dosing (pegcetacoplan monthly vs pegcetacoplan every other month at month 24: -0.17 mm2; 95% CI, -0.43 to 0.08; P = .17). Stronger associations were observed in the parafoveal and perifoveal regions for both pegcetacoplan monthly and pegcetacoplan every other month., Conclusions and Relevance: These findings offer additional insight into the potential effects of pegcetacoplan on the development of GA, including potential effects on the retinal pigment epithelium and photoreceptors., Trial Registration: ClinicalTrials.gov Identifiers: NCT03525600 and NCT03525613.

Introduction: The diagnosis of neovascular age-related macular degeneration (nAMD), the leading cause of visual impairment in the developed world, relies on the interpretation of various imaging tests of the retina. These include invasive angiographic methods, such as Fundus Fluorescein Angiography (FFA) and, on occasion, Indocyanine-Green Angiography (ICGA). Newer, non-invasive imaging modalities, predominately Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), have drastically transformed the diagnostic approach to nAMD. The aim of this study is to undertake a comprehensive diagnostic accuracy assessment of the various imaging modalities used in clinical practice for the diagnosis of nAMD (OCT, OCTA, FFA and, when a variant of nAMD called Polypoidal Choroidal Vasculopathy is suspected, ICGA) both alone and in various combinations., Methods and Analysis: This is a non-inferiority, prospective, randomised diagnostic accuracy study of 1067 participants. Participants are patients with clinical features consistent with nAMD who present to a National Health Service secondary care ophthalmology unit in the UK. Patients will undergo OCT as per standard practice and those with suspicious features of nAMD on OCT will be approached for participation in the study. Patients who agree to take part will also undergo both OCTA and FFA (and ICGA if indicated). Interpretation of the imaging tests will be undertaken by clinicians at recruitment sites. A randomised design was selected to avoid bias from consecutive review of all imaging tests by the same clinician. The primary outcome of the study will be the difference in sensitivity and specificity between OCT+OCTA and OCT+FFA (±ICGA) for nAMD detection as interpreted by clinicians at recruitment sites., Ethics and Dissemination: The study has been approved by the South Central-Oxford B Research Ethics Committee with reference number 21/SC/0412.Dissemination of study results will involve peer-review publications, presentations at major national and international scientific conferences., Trial Registration Number: ISRCTN18313457., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Objective: Implementing teleophthalmology into the optometric referral pathway may ease the current pressures on hospital eye services caused by over-referrals from some optometrists. This study aimed to understand the practical implications of implementing teleophthalmology by analysing lived experiences and perceptions of teleophthalmology in the optometric referral pathway for suspected retinal conditions., Design: Qualitative in-depth interview study SETTING: Fourteen primary care optometry practices and four secondary care hospital eye services from four NHS Foundation Trusts across the UK., Participants: We interviewed 41 participants: patients (17), optometrists (18), and ophthalmologists (6) who were involved in the HERMES study. Through thematic analysis, we collated and present their experiences of implementing teleophthalmology., Results: All participants interviewed were positive towards teleophthalmology as it could enable efficiencies in the referral pathway and improve feedback and communication between patients and healthcare professionals. Concerns included setup costs for optometrists and anxieties from patients about not seeing an ophthalmologist face to face. However, reducing unnecessary visits and increasing the availability of resources and capacity were seen as significant benefits., Conclusions: Overall, we report positive experiences of implementing teleophthalmology into the optometric referral pathway for suspected retinal conditions. Successful implementation will require appropriate investment to set up and integrate new technology and remunerate services, and continued evaluation to ensure timely feedback to patients and between healthcare professionals is received., Trial Registration Number: ISRCTN18106677., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Purpose: Data are limited pertaining to the long-term benefits of aflibercept treatment for neovascular age-related macular degeneration (nAMD). The aim of this study was to provide outcomes, safety, durability and quality-of-life data with aflibercept using a modified treat, extend and fixed regime over 4 years., Methods: Prospective, multicentre, single cohort observational study of treatment-naïve nAMD participants treated with aflibercept as 2-year extension of the MATE-trial that compared early and late Treat-and-Extend for 2 years. Refracted ETDRS best corrected visual acuity (BCVA), central retinal thickness (CRT), treatment interval and adverse events were assessed. Quality-of-life was measured using the Macular Disease Dependent Quality of Life (MacDQoL) and Macular Disease Treatment Satisfaction Questionnaires (MacTSQ)., Results: Twenty-six of 40 participants completing the MATE-trial were enrolled with 20 completing the total 4-year study. Mean BCVA was 60.7 at Month 0 and 64.8 ETDRS letters at Month 48 while CRT decreased from 423.7 μm to 292.2 μm. Five participants discontinued treatment due to inactivity. The mean number of treatments and visits for the remaining participants was 27 and 30.0, respectively, with treatment intervals extended to 12 weeks in four participants at Month 48. Both AMD-specific QoL and treatment satisfaction remained stable between Months 0 and 48 and mean BCVA significantly correlated with AMD-specific QoL scores at Months 12, 24 and 48., Conclusions: Results suggest that BCVA can be maintained over 48 months when following a treat-extend-and-fix regimen of aflibercept with intervals out to 12 weeks, while maintaining AMD-specific QoL and treatment satisfaction., (© 2023 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.)

Artificial intelligence (AI) has great potential in ophthalmology. We investigated how ambiguous outputs from an AI diagnostic support system (AI-DSS) affected diagnostic responses from optometrists when assessing cases of suspected retinal disease. Thirty optometrists (15 more experienced, 15 less) assessed 30 clinical cases. For ten, participants saw an optical coherence tomography (OCT) scan, basic clinical information and retinal photography ('no AI'). For another ten, they were also given AI-generated OCT-based probabilistic diagnoses ('AI diagnosis'); and for ten, both AI-diagnosis and AI-generated OCT segmentations ('AI diagnosis + segmentation') were provided. Cases were matched across the three types of presentation and were selected to include 40% ambiguous and 20% incorrect AI outputs. Optometrist diagnostic agreement with the predefined reference standard was lowest for 'AI diagnosis + segmentation' (204/300, 68%) compared to 'AI diagnosis' (224/300, 75% p = 0.010), and 'no Al' (242/300, 81%, p =  < 0.001). Agreement with AI diagnosis consistent with the reference standard decreased (174/210 vs 199/210, p = 0.003), but participants trusted the AI more (p = 0.029) with segmentations. Practitioner experience did not affect diagnostic responses (p = 0.24). More experienced participants were more confident (p = 0.012) and trusted the AI less (p = 0.038). Our findings also highlight issues around reference standard definition., (© 2024. The Author(s).)

Background/aims: Evaluation of telemedicine care models has highlighted its potential for exacerbating healthcare inequalities. This study seeks to identify and characterise factors associated with non-attendance across face-to-face and telemedicine outpatient appointments., Methods: A retrospective cohort study at a tertiary-level ophthalmic institution in the UK, between 1 January 2019 and 31 October 2021. Logistic regression modelled non-attendance against sociodemographic, clinical and operational exposure variables for all new patient registrations across five delivery modes: asynchronous, synchronous telephone, synchronous audiovisual and face to face prior to the pandemic and face to face during the pandemic., Results: A total of 85 924 patients (median age 55 years, 54.4% female) were newly registered. Non-attendance differed significantly by delivery mode: (9.0% face to face prepandemic, 10.5% face to face during the pandemic, 11.7% asynchronous and 7.8%, synchronous during pandemic). Male sex, greater levels of deprivation, a previously cancelled appointment and not self-reporting ethnicity were strongly associated with non-attendance across all delivery modes. Individuals identifying as black ethnicity had worse attendance in synchronous audiovisual clinics (adjusted OR 4.24, 95% CI 1.59 to 11.28) but not asynchronous. Those not self-reporting their ethnicity were from more deprived backgrounds, had worse broadband access and had significantly higher non-attendance across all modes (all p<0.001)., Conclusion: Persistent non-attendance among underserved populations attending telemedicine appointments highlights the challenge digital transformation faces for reducing healthcare inequalities. Implementation of new programmes should be accompanied by investigation into the differential health outcomes of vulnerable populations., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Introduction: Sickle cell disease (SCD) is one of the most common genetic disorders in the UK, with over 15 000 people affected. Proliferative sickle cell retinopathy (SCR) is a well-described complication of SCD and can result in significant sight loss, although the prevalence in the UK is not currently known. There are currently no national screening guidelines for SCR, with wide variations in the management of the condition across the UK., Methods and Analysis: The Sickle Eye Project is an epidemiological, cross-sectional, non-interventional study to determine the prevalence of visual impairment due to SCR and/or maculopathy in the UK. Haematologists in at least 16 geographically dispersed hospitals in the UK linked to participating eye clinics will offer study participation to consecutive patients meeting the inclusion criteria attending the sickle cell clinic. The following study procedures will be performed: (a) best corrected visual acuity with habitual correction and pinhole, (b) dilated slit lamp biomicroscopy and funduscopy, (c) optical coherence tomography (OCT), (d) OCT angiography where available, (e) ultrawide fundus photography, (f) National Eye Institute Visual Function Questionnaire-25 and (g) acceptability of retinal screening questionnaire. The primary outcome is the proportion of people with SCD with visual impairment defined as logarithm of the minimum angle of resolution ≥0.3 in at least one eye. Secondary outcomes include the prevalence of each stage of SCR and presence of maculopathy by age and genotype; correlation of stage of SCR and maculopathy to severity of SCD; the impact of SCR and presence of maculopathy on vision-related quality of life; and the acceptability to patients of routine retinal imaging for SCR and maculopathy., Ethics and Dissemination: Ethical approval was obtained from the South Central-Oxford A Research Ethics Committee (REC 23/SC/0363). Findings will be reported through academic journals in ophthalmology and haematology., Competing Interests: Competing interests: CD reports receiving institutional research grant, consulting fees and speaker fees from Roche. KB and JT have received consulting and speaker fees from Roche., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Purpose: Periodontitis, a ubiquitous severe gum disease affecting the teeth and surrounding alveolar bone, can heighten systemic inflammation. We investigated the association between very severe periodontitis and early biomarkers of age-related macular degeneration (AMD), in individuals with no eye disease., Design: Cross-sectional analysis of the prospective community-based cohort United Kingdom (UK) Biobank., Participants: Sixty-seven thousand three hundred eleven UK residents aged 40 to 70 years recruited between 2006 and 2010 underwent retinal imaging., Methods: Macular-centered OCT images acquired at the baseline visit were segmented for retinal sublayer thicknesses. Very severe periodontitis was ascertained through a touchscreen questionnaire. Linear mixed effects regression modeled the association between very severe periodontitis and retinal sublayer thicknesses, adjusting for age, sex, ethnicity, socioeconomic status, alcohol consumption, smoking status, diabetes mellitus, hypertension, refractive error, and previous cataract surgery., Main Outcome Measures: Photoreceptor layer (PRL) and retinal pigment epithelium-Bruch's membrane (RPE-BM) thicknesses., Results: Among 36 897 participants included in the analysis, 1571 (4.3%) reported very severe periodontitis. Affected individuals were older, lived in areas of greater socioeconomic deprivation, and were more likely to be hypertensive, diabetic, and current smokers (all P < 0.001). On average, those with very severe periodontitis were hyperopic (0.05 ± 2.27 diopters) while those unaffected were myopic (-0.29 ± 2.40 diopters, P < 0.001). Following adjusted analysis, very severe periodontitis was associated with thinner PRL (-0.55 μm, 95% confidence interval [CI], -0.97 to -0.12; P  = 0.022) but there was no difference in RPE-BM thickness (0.00 μm, 95% CI, -0.12 to 0.13; P  = 0.97). The association between PRL thickness and very severe periodontitis was modified by age ( P < 0.001). Stratifying individuals by age, thinner PRL was seen among those aged 60 to 69 years with disease (-1.19 μm, 95% CI, -1.85 to -0.53; P < 0.001) but not among those aged < 60 years., Conclusions: Among those with no known eye disease, very severe periodontitis is statistically associated with a thinner PRL, consistent with incipient AMD. Optimizing oral hygiene may hold additional relevance for people at risk of degenerative retinal disease., Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (© 2024 by the American Academy of Ophthalmology.)

Introduction: To evaluate the effect pegcetacoplan, a C3 and C3b inhibitor, on the rate of progression of geographic atrophy (GA) as assessed by spectral domain optical coherence tomography (SD-OCT) using a split-person study design and deep-learning quantification., Methods: A post hoc analysis of phase 2 FILLY trial data comparing study (treated monthly, treated every other month and sham-treated) and fellow (untreated) eyes in a split-person study design was performed. This analysis included 288 eyes from 144 patients with bilateral GA from the FILLY phase 2 trial (Clinical Trials identifier: NCT02503332). Only patients with bilateral GA and without evidence of choroidal neovascularisation in either eye were included. Patient study eyes were treated with sham injections or with pegcetacoplan monthly (PM) or every other month (PEOM) for 12 months. SD-OCT scans of study and fellow eyes taken at baseline and 12 months were used for the analysis. The main outcomes were the annual change in the area of retinal pigment epithelial and outer retinal atrophy (RORA), its constituent features (photoreceptor degeneration [PRD], retinal pigment epithelium [RPE] loss, hypertransmission) and intact macula as compared to the untreated fellow eye., Results: Annual GA growth was reduced in eyes treated with PM versus untreated fellow eyes for OCT features, including RORA (study eye 0.792 vs. fellow eye 1.13 mm 2 ; P = 0.003), PRD (0.739 vs. 1.23 mm 2 ; P = 0.015), RPE-loss (0.789 vs. 1.17 mm 2 ; P = 0.007) and intact macula (- 0.735 vs. - 1.29 mm 2 ; P = 0.011). Similar (but not statistically significant) trends were observed with the PEOM treatment or when GA was quantified with fundus autofluorescence (FAF). The sham treatment demonstrated no effect. Pearson correlation coefficients showed concordance in the enlargement rate of GA between the study and fellow eyes in the sham (R = 0.64) and PEOM (R = 0.68) groups, but not in the PM group (R = 0.21)., Conclusions: Pegcetacoplan-treated eyes demonstrated a reduction in spatial GA progression compared to their untreated counterparts. This effect was more evident on OCT than with FAF., Trial Registration: Clinical Trials identifier: NCT02503332., (© 2023. The Author(s).)

Retinal diseases are a leading cause of blindness in developed countries, accounting for the largest share of visually impaired children, working-age adults (inherited retinal disease), and elderly individuals (age-related macular degeneration). These conditions need specialised clinicians to interpret multimodal retinal imaging, with diagnosis and intervention potentially delayed. With an increasing and ageing population, this is becoming a global health priority. One solution is the development of artificial intelligence (AI) software to facilitate rapid data processing. Herein, we review research offering decision support for the diagnosis, classification, monitoring, and treatment of retinal disease using AI. We have prioritised diabetic retinopathy, age-related macular degeneration, inherited retinal disease, and retinopathy of prematurity. There is cautious optimism that these algorithms will be integrated into routine clinical practice to facilitate access to vision-saving treatments, improve efficiency of healthcare systems, and assist clinicians in processing the ever-increasing volume of multimodal data, thereby also liberating time for doctor-patient interaction and co-development of personalised management plans., (© 2023. The Author(s).)

Purpose: Ophthalmic services are currently under considerable stress; in the UK, ophthalmology departments have the highest number of outpatient appointments of any department within the National Health Service. Recognising the need for intervention, several approaches have been trialled to tackle the high numbers of false-positive referrals initiated in primary care and seen face to face within the hospital eye service (HES). In this mixed-methods narrative synthesis, we explored interventions based on their clinical impact, cost and acceptability to determine whether they are clinically effective, safe and sustainable. A systematic literature search of PubMed, MEDLINE and CINAHL, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), was used to identify appropriate studies published between December 2001 and December 2022., Recent Findings: A total of 55 studies were reviewed. Four main interventions were assessed, where two studies covered more than one type: training and guidelines (n = 8), referral filtering schemes (n = 32), asynchronous teleophthalmology (n = 13) and synchronous teleophthalmology (n = 5). All four approaches demonstrated effectiveness for reducing false-positive referrals to the HES. There was sufficient evidence for stakeholder acceptance and cost-effectiveness of referral filtering schemes; however, cost comparisons involved assumptions. Referral filtering and asynchronous teleophthalmology reported moderate levels of false-negative cases (2%-20%), defined as discharged patients requiring HES monitoring., Summary: The effectiveness of interventions varied depending on which outcome and stakeholder was considered. More studies are required to explore stakeholder opinions around all interventions. In order to maximise clinical safety, it may be appropriate to combine more than one approach, such as referral filtering schemes with virtual review of discharged patients to assess the rate of false-negative cases. The implementation of a successful intervention is more complex than a 'one-size-fits-all' approach and there is potential space for newer types of interventions, such as artificial intelligence clinical support systems within the referral pathway., (© 2023 The Authors. Ophthalmic and Physiological Optics published by John Wiley & Sons Ltd on behalf of College of Optometrists.)

Background and Objectives: Cadaveric studies have shown disease-related neurodegeneration and other morphological abnormalities in the retina of individuals with Parkinson disease (PD); however, it remains unclear whether this can be reliably detected with in vivo imaging. We investigated inner retinal anatomy, measured using optical coherence tomography (OCT), in prevalent PD and subsequently assessed the association of these markers with the development of PD using a prospective research cohort., Methods: This cross-sectional analysis used data from 2 studies. For the detection of retinal markers in prevalent PD, we used data from AlzEye, a retrospective cohort of 154,830 patients aged 40 years and older attending secondary care ophthalmic hospitals in London, United Kingdom, between 2008 and 2018. For the evaluation of retinal markers in incident PD, we used data from UK Biobank, a prospective population-based cohort where 67,311 volunteers aged 40-69 years were recruited between 2006 and 2010 and underwent retinal imaging. Macular retinal nerve fiber layer (mRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layer (INL) thicknesses were extracted from fovea-centered OCT. Linear mixed-effects models were fitted to examine the association between prevalent PD and retinal thicknesses. Hazard ratios for the association between time to PD diagnosis and retinal thicknesses were estimated using frailty models., Results: Within the AlzEye cohort, there were 700 individuals with prevalent PD and 105,770 controls (mean age 65.5 ± 13.5 years, 51.7% female). Individuals with prevalent PD had thinner GCIPL (-2.12 μm, 95% CI -3.17 to -1.07, p = 8.2 × 10 -5 ) and INL (-0.99 μm, 95% CI -1.52 to -0.47, p = 2.1 × 10 -4 ). The UK Biobank included 50,405 participants (mean age 56.1 ± 8.2 years, 54.7% female), of whom 53 developed PD at a mean of 2,653 ± 851 days. Thinner GCIPL (hazard ratio [HR] 0.62 per SD increase, 95% CI 0.46-0.84, p = 0.002) and thinner INL (HR 0.70, 95% CI 0.51-0.96, p = 0.026) were also associated with incident PD., Discussion: Individuals with PD have reduced thickness of the INL and GCIPL of the retina. Involvement of these layers several years before clinical presentation highlight a potential role for retinal imaging for at-risk stratification of PD., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Patients with macular pathology, including that caused by age-related macular degeneration and diabetic macular oedema, must attend frequent in-clinic monitoring appointments to detect onset of disease activity requiring treatment and to monitor progression of existing disease. In-person clinical monitoring places a significant burden on patients, caregivers and healthcare systems and is limited in that it only provides clinicians with a snapshot of the patient's disease status. The advent of remote monitoring technologies offers the potential for patients to test their own retinal health at home in collaboration with clinicians, reducing the need for in-clinic appointments. In this review we discuss visual function tests, both existing and novel, that have the potential for remote use and consider their suitability for discriminating the presence of disease and progression of disease. We then review the clinical evidence supporting the use of mobile applications for monitoring of visual function from clinical development through to validation studies and real-world implementation. This review identified seven app-based visual function tests: four that have already received some form of regulatory clearance and three under development. The evidence included in this review shows that remote monitoring offers great potential for patients with macular pathology to monitor their condition from home, reducing the need for burdensome clinic visits and expanding clinicians' understanding of patients' retinal health beyond traditional clinical monitoring. In order to instil confidence in the use of remote monitoring in both patients and clinicians further longitudinal real-world studies are now warranted., (© 2023. The Author(s).)

Purpose: In the UK, ophthalmology has the highest number of outpatient appointments within the National Health Service. False-positive referrals from primary care are one of the main factors contributing to the oversubscription of hospital eye services (HESs). We reviewed the accuracy of referrals originating from primary care optometrists and contributing factors, such as condition type and years since registration., Recent Findings: Of the 31 studies included in the review, 22 were retrospective analyses of referrals and appointments at the HES. Eight were prospective studies, and one used online clinical vignettes. Seven assessed the accuracy of referrals for all ocular conditions. The remaining studies focused on glaucoma (n = 11), cataracts (n = 7), emergency conditions (n = 4), neovascular age-related macular degeneration (n = 1) and paediatric binocular vision (n = 1). The diagnostic agreement for suspected emergency ocular conditions was the lowest, with only 21.1% of referrals considered to require urgent attention in one study. For glaucoma, the first-visit discharge rate was high (16.7%-48%). Optometrist referral accuracy was overall 18.6% higher than General Medical Practitioners'; however, the two mainly referred different ocular conditions. Female optometrists made more false-positive referrals than males (p = 0.008). The proportion of false positives decreased by 6.2% per year since registration (p < 0.001)., Summary: There was significant variation in referral accuracy across different ocular conditions, partly due to differences when defining accurate referrals. Optometrists working in primary care are generally more limited in their resources than the HES. Thus, choosing the cautious option of referral when they are unsure could be in the patients' best interests. The possible effect of increased use of advanced imaging on referrals requires evaluation. Although interventions such as refinement schemes have been put in place, these vary across regions, and their approaches such as virtual referral triaging may reduce unnecessary HES face-to-face appointments and promote communication between primary and secondary care., (© 2023 The Authors. Ophthalmic and Physiological Optics published by John Wiley & Sons Ltd on behalf of College of Optometrists.)

Background/objectives: This study aims to describe the grading methods and baseline characteristics for UK Biobank (UKBB) participants who underwent retinal imaging in 2009-2010, and to characterise individuals with retinal features suggestive of age-related macular degeneration (AMD), glaucoma and retinopathy., Methods: Non-mydriatic colour fundus photographs and macular optical coherence tomography (OCT) scans were manually graded by Central Administrative Research Facility certified graders and quality assured by clinicians of the Network of Ophthalmic Reading Centres UK. Captured retinal features included those associated with AMD (≥1 drusen, pigmentary changes, geographic atrophy or exudative AMD; either imaging modality), glaucoma (≥0.7 cup-disc ratio, ≥0.2 cup-disc ratio difference between eyes, other abnormal disc features; photographs only) and retinopathy (characteristic features of diabetic retinopathy with or without microaneurysms; either imaging modality). Suspected cases of these conditions were characterised with reference to diagnostic records, physical and biochemical measurements., Results: Among 68,514 UKBB participants who underwent retinal imaging, the mean age was 57.3 years (standard deviation 8.2), 45.7% were men and 90.6% were of White ethnicity. A total of 64,367 participants had gradable colour fundus photographs and 68,281 had gradable OCT scans in at least one eye. Retinal features suggestive of AMD and glaucoma were identified in 15,176 and 2184 participants, of whom 125 (0.8%) and 188 (8.6%), respectively, had a recorded diagnosis. Of 264 participants identified to have retinopathy with microaneurysms, 251 (95.1%) had either diabetes or hypertension., Conclusions: This dataset represents a valuable addition to what is currently available in UKBB, providing important insights to both ocular and systemic health., (© 2022. The Author(s).)

Importance: Diabetic macular edema (DME) is a major cause of vision loss in patients with diabetes mellitus. Intravitreal dexamethasone is a treatment option for patients unsuitable for or non-responsive to anti-angiogenic agents., Objective: To quantify visual and anatomical outcomes from an initial intravitreal dexamethasone injection over the expected 6-month period of dexamethasone release by the implant. Design and enrolment: This is a retrospective cohort study using electronic medical records of patients reviewed between 1 January 2012 and 1 April 2022., Setting: A tertiary eye-care center in London, United Kingdom; Moorfields Eye Hospital National Healthcare System Foundation Trust., Participants: The cohort comprised 418 adult patients with DME who received an initial treatment of 700 µg intravitreal dexamethasone in the study period. Of these, 240 patients met the inclusion criteria of ≥2 hospital visits following initial injection (≥1 beyond 6 months) and no previous ocular corticosteroid treatment or missing assessment at baseline., Exposure(s): Intravitreal dexamethasone implant (700 µg)., Main Outcome(s) and Measure(s): Probability of a positive visual outcome, defined as ≥5 or ≥10 Early Treatment Diabetic Retinopathy Study (ETDRS)-letter gain after treatment when compared to baseline (Kaplan-Meier models)., Results: From the initial intravitreal dexamethasone injection alone, we observed a >75% chance of gaining ≥5 ETDRS letters and >50% chance of gaining ≥10 ETDRS letters within 6 months. There was less than a 50% chance of sustaining either positive visual outcome beyond 4 months., Conclusions and Relevance: Most patients can be expected to have a positive visual outcome following an initial injection of dexamethasone implants that subsides within 4 months. Real-world re-treatment was observed to be delayed until after visual benefits were lost in half of the cohort. Further research will be needed to study the effects of delays in re-treatment.

Importance: The potential association of schizophrenia with distinct retinal changes is of clinical interest but has been challenging to investigate because of a lack of sufficiently large and detailed cohorts., Objective: To investigate the association between retinal biomarkers from multimodal imaging (oculomics) and schizophrenia in a large real-world population., Design, Setting, and Participants: This cross-sectional analysis used data from a retrospective cohort of 154 830 patients 40 years and older from the AlzEye study, which linked ophthalmic data with hospital admission data across England. Patients attended Moorfields Eye Hospital, a secondary care ophthalmic hospital with a principal central site, 4 district hubs, and 5 satellite clinics in and around London, United Kingdom, and had retinal imaging during the study period (January 2008 and April 2018). Data were analyzed from January 2022 to July 2022., Main Outcomes and Measures: Retinovascular and optic nerve indices were computed from color fundus photography. Macular retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (mGC-IPL) thicknesses were extracted from optical coherence tomography. Linear mixed-effects models were used to examine the association between schizophrenia and retinal biomarkers., Results: A total of 485 individuals (747 eyes) with schizophrenia (mean [SD] age, 64.9 years [12.2]; 258 [53.2%] female) and 100 931 individuals (165 400 eyes) without schizophrenia (mean age, 65.9 years [13.7]; 53 253 [52.8%] female) were included after images underwent quality control and potentially confounding conditions were excluded. Individuals with schizophrenia were more likely to have hypertension (407 [83.9%] vs 49 971 [48.0%]) and diabetes (364 [75.1%] vs 28 762 [27.6%]). The schizophrenia group had thinner mGC-IPL (-4.05 μm, 95% CI, -5.40 to -2.69; P = 5.4 × 10-9), which persisted when investigating only patients without diabetes (-3.99 μm; 95% CI, -6.67 to -1.30; P = .004) or just those 55 years and younger (-2.90 μm; 95% CI, -5.55 to -0.24; P = .03). On adjusted analysis, retinal fractal dimension among vascular variables was reduced in individuals with schizophrenia (-0.14 units; 95% CI, -0.22 to -0.05; P = .001), although this was not present when excluding patients with diabetes., Conclusions and Relevance: In this study, patients with schizophrenia had measurable differences in neural and vascular integrity of the retina. Differences in retinal vasculature were mostly secondary to the higher prevalence of diabetes and hypertension in patients with schizophrenia. The role of retinal features as adjunct outcomes in patients with schizophrenia warrants further investigation.

Background/objectives: In healthcare research investigating complex interventions, gaps in understanding of processes can be filled by using qualitative methods alongside a quantitative approach. The aim of this mixed-methods pilot trial was to provide feasibility evidence comparing two treatment regimens for neovascular age-related macular degeneration (nAMD) to inform a future large-scale randomised controlled trial (RCT)., Subjects/methods: Forty-four treatment-naïve nAMD patients were followed over 24 months and randomised to one of two treatment regimens: standard care (SC) or treat and extend (T&E). The primary objective evaluated feasibility of the MATE trial via evaluations of screening logs for recruitment rates, nonparticipation and screen fails, whilst qualitative in-depth interviews with key study staff evaluated the recruitment phase and running of the trial. The secondary objective assessed changes in visual acuity and central retinal thickness (CRT) between the two treatment arms., Results: The overall recruitment rate was 3.07 participants per month with a 40.8% non-participation rate, 18.51% screen-failure rate and 15% withdrawal/non-completion rate. Key themes in the recruitment phase included human factors, protocol-related issues, recruitment processes and challenges. Both treatment regimens showed a trend towards a visual acuity gain at month 12 which was not maintained at month 24, whilst CRT reduced similarly in both regimens over the same time period. These were achieved with one less treatment following a T&E regimen., Conclusion: This mixed-methodology, pilot RCT achieved its pre-defined recruitment, nonparticipation and screen failure rates, thus deeming it a success. With some minor protocol amendments, progression to a large-scale RCT will be achievable., (© 2023. The Author(s).)

Introduction: Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients by molecular genetic testing is the first step towards effective care and patient management. However, genetic diagnosis is currently slow, expensive and not widely accessible. The aim of the current project is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service., Methods and Analysis: The data-only retrospective cohort study involves a target sample size of 10 000 participants, which has been derived based on the number of participants with IRD at three leading UK eye hospitals: Moorfields Eye Hospital (MEH), Oxford University Hospital (OUH) and Liverpool University Hospital (LUH), as well as a Japanese hospital, the Tokyo Medical Centre (TMC). Eye2Gene aims to predict causative genes from retinal images of patients with a diagnosis of IRD. For this purpose, 36 most common causative IRD genes have been selected to develop a training dataset for the software to have enough examples for training and validation for detection of each gene. The Eye2Gene algorithm is composed of multiple deep convolutional neural networks, which will be trained on MEH IRD datasets, and externally validated on OUH, LUH and TMC., Ethics and Dissemination: This research was approved by the IRB and the UK Health Research Authority (Research Ethics Committee reference 22/WA/0049) 'Eye2Gene: accelerating the diagnosis of IRDs' Integrated Research Application System (IRAS) project ID: 242050. All research adhered to the tenets of the Declaration of Helsinki. Findings will be reported in an open-access format., Competing Interests: Competing interests: Neither the chief investigator (NP) nor any of the coinvestigators have any direct personal involvement (financial, shareholder or personal) with the NIHR that may give rise to a conflict of interest. As has been disclosed to the study sponsor (UCL) and the funder (NIHR), NP and IM are shareholders at Phenopolis, which is one of the two subcontractors mentioned above (WP6). Phenopolis will provide professional software development services for Eye2Gene., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: The aim of this study was to describe features of disease activity in patients with treated stable macular neovascularisation (MNV) in neovascular age related macular degeneration (nAMD) using optical coherence tomography angiography (OCTA)., Methods: Thirty-two eyes of 32 patients with nAMD were included in this prospective, observational study. These patients were undergoing treatment with aflibercept on a treat-and-extend regimen attending an extension to a 12-week treatment interval., Results: All subjects had no macular haemorrhage and no structural OCT markers of active MNV activity at the index 12-week treatment extension visit. 31/32 OCTA images were gradeable without significant imaging artefact. The mean MNV size was 3.6mm 2  ± 4.6mm 2 and 27 (87.1%) had detectable MNV blood flow. 29/31 (93.5%) subjects had MNV with mature phenotypes including 10 non-specific, 10 tangle and 3 deadtree phenotypes. MNV halo and MNV central feeder vessel were noted in 18 (58.1%) and 19 (61.3%) of subjects respectively; only 1 (3.2%) subject was noted to have a MNV capillary fringe., Conclusions: MNV blood flow is still detectable using OCTA in the majority of subjects in this study with treated stable MNV. OCTA features associated included MNV mature phenotype, MNV feeder vessel, MNV halo and absence of capillary fringe., (© 2023. The Author(s).)

Purpose: The purpose of this study was to investigate the association between glycated hemoglobin (HbA1c) levels and retinal sub-layer thicknesses in people with and without diabetes., Methods: We included 41,453 UK Biobank participants aged 40 to 69 years old. Diabetes status was defined by self-report of diagnosis or use of insulin. Participants were categorized into groups: (1) those with HbA1c <48 mmol/mol were subdivided into quintiles according to normal range of HbA1c; (2) those previously diagnosed with diabetes with no evidence of diabetic retinopathy; and (3) undiagnosed diabetes: >48 mmol/mol. Total macular and retinal sub-layer thicknesses were derived from spectral-domain optical coherence tomography (SD-OCT) images. Multivariable linear regression was used to evaluate the associations between diabetes status and retinal layer thickness., Results: Compared with participants in the second quintile of the normal HbA1c range, those in the fifth quintile had a thinner photoreceptor layer thickness (-0.33 µm, P = 0.006). Participants with diagnosed diabetes had a thinner macular retinal nerve fiber layer (mRNFL; -0.58 µm, P < 0.001), photoreceptor layer thickness (-0.94 µm, P < 0.001), and total macular thickness (-1.61 µm, P < 0.001), whereas undiagnosed diabetes participants had a reduced photoreceptor layer thickness (-1.22 µm, P = 0.009) and total macular thickness (-2.26 µm, P = 0.005). Compared to participants without diabetes, those with diabetes had a thinner mRNFL (-0.50 µm, P < 0.001), photoreceptor layer thickness (-0.77 µm, P < 0.001), and total macular thickness (-1.36 µm, P < 0.001)., Conclusions: Participants with higher HbA1c in the normal range had marginally thinner photoreceptor thickness, whereas those with diabetes (including undiagnosed diabetes) had meaningfully thinner retinal sublayer and total macular thickness., Translational Relevance: We showed that early retinal neurodegeneration occurs in people whose HbA1c levels are below the current diabetes diagnostic threshold; this might impact the management of pre-diabetes individuals.

Introduction: Neovascular age-related macular degeneration (nAMD) management is one of the largest single-disease contributors to hospital outpatient appointments. Partial automation of nAMD treatment decisions could reduce demands on clinician time. Established artificial intelligence (AI)-enabled retinal imaging analysis tools, could be applied to this use-case, but are not yet validated for it. A primary qualitative investigation of stakeholder perceptions of such an AI-enabled decision tool is also absent. This multi-methods study aims to establish the safety and efficacy of an AI-enabled decision tool for nAMD treatment decisions and understand where on the clinical pathway it could sit and what factors are likely to influence its implementation., Methods and Analysis: Single-centre retrospective imaging and clinical data will be collected from nAMD clinic visits at a National Health Service (NHS) teaching hospital ophthalmology service, including judgements of nAMD disease stability or activity made in real-world consultant-led-care. Dataset size will be set by a power calculation using the first 127 randomly sampled eligible clinic visits. An AI-enabled retinal segmentation tool and a rule-based decision tree will independently analyse imaging data to report nAMD stability or activity for each of these clinic visits. Independently, an external reading centre will receive both clinical and imaging data to generate an enhanced reference standard for each clinic visit. The non-inferiority of the relative negative predictive value of AI-enabled reports on disease activity relative to consultant-led-care judgements will then be tested. In parallel, approximately 40 semi-structured interviews will be conducted with key nAMD service stakeholders, including patients. Transcripts will be coded using a theoretical framework and thematic analysis will follow., Ethics and Dissemination: NHS Research Ethics Committee and UK Health Research Authority approvals are in place (21/NW/0138). Informed consent is planned for interview participants only. Written and oral dissemination is planned to public, clinical, academic and commercial stakeholders., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Purpose: To develop a severity classification for macular telangiectasia type 2 (MacTel) disease using multimodal imaging., Design: An algorithm was used on data from a prospective natural history study of MacTel for classification development., Subjects: A total of 1733 participants enrolled in an international natural history study of MacTel., Methods: The Classification and Regression Trees (CART), a predictive nonparametric algorithm used in machine learning, analyzed the features of the multimodal imaging important for the development of a classification, including reading center gradings of the following digital images: stereoscopic color and red-free fundus photographs, fluorescein angiographic images, fundus autofluorescence images, and spectral-domain (SD)-OCT images. Regression models that used least square method created a decision tree using features of the ocular images into different categories of disease severity., Main Outcome Measures: The primary target of interest for the algorithm development by CART was the change in best-corrected visual acuity (BCVA) at baseline for the right and left eyes. These analyses using the algorithm were repeated for the BCVA obtained at the last study visit of the natural history study for the right and left eyes., Results: The CART analyses demonstrated 3 important features from the multimodal imaging for the classification: OCT hyper-reflectivity, pigment, and ellipsoid zone loss. By combining these 3 features (as absent, present, noncentral involvement, and central involvement of the macula), a 7-step scale was created, ranging from excellent to poor visual acuity. At grade 0, 3 features are not present. At the most severe grade, pigment and exudative neovascularization are present. To further validate the classification, using the Generalized Estimating Equation regression models, analyses for the annual relative risk of progression over a period of 5 years for vision loss and for progression along the scale were performed., Conclusions: This analysis using the data from current imaging modalities in participants followed in the MacTel natural history study informed a classification for MacTel disease severity featuring variables from SD-OCT. This classification is designed to provide better communications to other clinicians, researchers, and patients., Financial Disclosures: Proprietary or commercial disclosure may be found after the references.

Purpose: Rare disease diagnosis is challenging in medical image-based artificial intelligence due to a natural class imbalance in datasets, leading to biased prediction models. Inherited retinal diseases (IRDs) are a research domain that particularly faces this issue. This study investigates the applicability of synthetic data in improving artificial intelligence-enabled diagnosis of IRDs using generative adversarial networks (GANs)., Design: Diagnostic study of gene-labeled fundus autofluorescence (FAF) IRD images using deep learning., Participants: Moorfields Eye Hospital (MEH) dataset of 15 692 FAF images obtained from 1800 patients with confirmed genetic diagnosis of 1 of 36 IRD genes., Methods: A StyleGAN2 model is trained on the IRD dataset to generate 512 × 512 resolution images. Convolutional neural networks are trained for classification using different synthetically augmented datasets, including real IRD images plus 1800 and 3600 synthetic images, and a fully rebalanced dataset. We also perform an experiment with only synthetic data. All models are compared against a baseline convolutional neural network trained only on real data., Main Outcome Measures: We evaluated synthetic data quality using a Visual Turing Test conducted with 4 ophthalmologists from MEH. Synthetic and real images were compared using feature space visualization, similarity analysis to detect memorized images, and Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) score for no-reference-based quality evaluation. Convolutional neural network diagnostic performance was determined on a held-out test set using the area under the receiver operating characteristic curve (AUROC) and Cohen's Kappa (κ)., Results: An average true recognition rate of 63% and fake recognition rate of 47% was obtained from the Visual Turing Test. Thus, a considerable proportion of the synthetic images were classified as real by clinical experts. Similarity analysis showed that the synthetic images were not copies of the real images, indicating that copied real images, meaning the GAN was able to generalize. However, BRISQUE score analysis indicated that synthetic images were of significantly lower quality overall than real images ( P < 0.05). Comparing the rebalanced model (RB) with the baseline (R), no significant change in the average AUROC and κ was found (R-AUROC = 0.86[0.85-88], RB-AUROC = 0.88[0.86-0.89], R-k = 0.51[0.49-0.53], and RB-k = 0.52[0.50-0.54]). The synthetic data trained model (S) achieved similar performance as the baseline (S-AUROC = 0.86[0.85-87], S-k = 0.48[0.46-0.50])., Conclusions: Synthetic generation of realistic IRD FAF images is feasible. Synthetic data augmentation does not deliver improvements in classification performance. However, synthetic data alone deliver a similar performance as real data, and hence may be useful as a proxy to real data. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references., (© 2022 by the American Academy of Ophthalmology. Published by Elsevier Inc.)

Geographic atrophy (GA) is a vision-threatening manifestation of age-related macular degeneration (AMD), one of the leading causes of blindness globally. Objective, rapid, reliable, and scalable quantification of GA from optical coherence tomography (OCT) retinal scans is necessary for disease monitoring, prognostic research, and clinical endpoints for therapy development. Such automatically quantified biomarkers on OCT are likely to further elucidate structure-function correlation in GA and thus the pathophysiological mechanisms of disease development and progression. In this work, we aimed to predict visual function with machine-learning applied to automatically acquired quantitative imaging biomarkers in GA. A post-hoc analysis of data from a clinical trial and routine clinical care was conducted. A deep-learning automated segmentation model was applied on OCT scans from 476 eyes (325 patients) with GA. A separate machine learning prediction model (Random Forest) used the resultant quantitative OCT (qOCT) biomarkers to predict cross-sectional visual acuity under standard (VA) and low luminance (LLVA). The primary outcome was regression coefficient (r 2 ) and mean absolute error (MAE) for cross-sectional VA and LLVA in Early Treatment Diabetic Retinopathy Study (ETDRS) letters. OCT parameters were predictive of VA (r 2 0.40 MAE 11.7 ETDRS letters) and LLVA (r 2 0.25 MAE 12.1). Normalised random forest feature importance, as a measure of the predictive value of the three constituent features of GA; retinal pigment epithelium (RPE)-loss, photoreceptor degeneration (PDR), hypertransmission and their locations, was reported both on voxel-level heatmaps and ETDRS-grid subfields. The foveal region (46.5%) and RPE-loss (31.1%) had greatest predictive importance for VA. For LLVA, however, non-foveal regions (74.5%) and PDR (38.9%) were most important. In conclusion, automated qOCT biomarkers demonstrate predictive significance for VA and LLVA in GA. LLVA is itself predictive of GA progression, implying that the predictive qOCT biomarkers provided by our model are also prognostic., (© 2022. The Author(s).)

Purpose: To assess intrapupillary space (IPS) changes in healthy subjects with regard to decreased iris motility in patients with pseudoexfoliation glaucoma (PEXG) or non-arteritic anterior ischaemic optic neuropathy (NAION) in a feasibility study in a clinical environment., Methods: Scotopic and photopic IPS measurements using three-dimensionally rendered swept-source optical coherence tomography (SS-OCT) data were obtained and compared for all subjects. Intrapupillary space (IPS) parameters were evaluated such as absolute volumetric differences, relative light response for volumetric ratios and pupillary ejection fraction (PEF) for functional contraction measurements., Results: From a total of 122 IPS from 66 subjects, 106 IPS were eligible for comparison providing values for 72 normal, 30 PEXG and 4 NAION eyes. In healthy, PEXG and NAION subjects, scotopic overall mean IPS was 8.90, 3.45 and 4.16 mm 3 , and photopic overall mean IPS was 0.87, 0.74 and 1.13 mm 3 , respectively. Three-dimensional contractility showed a mean absolute difference of 8.03 mm 3 for normals (defined as 100% contractility), 2.72 mm 3 for PEXG (33.88% of normal) and 3.03 mm 3 for NAION (38.50% of normal) with a relative light response ratio between scotopic and photopic volumes of 10.26 (100%), 4.69 (45.70%) and 3.67 (35.78%), respectively. Pupillary ejection fraction (PEF) showed a contractile pupillary emptying of 88.11% for normals, 76.92% for PEXG and 70.91% for NAION patients., Conclusion: This 3D pupillometry OCT assessment allows for quantitative measurements of pupil function, contractility and response to light. More specifically, PEF is presented as a potential (neuro)-pupillary outcome measure that could be useful in the monitoring of ophthalmic disorders that affect pupillary function., (© 2021 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.)

Purpose: Neovascular age-related macular degeneration (nAMD) is a major global cause of blindness. Whilst anti-vascular endothelial growth factor (anti-VEGF) treatment is effective, response varies considerably between individuals. Thus, patients face substantial uncertainty regarding their future ability to perform daily tasks. In this study, we evaluate the performance of an automated machine learning (AutoML) model which predicts visual acuity (VA) outcomes in patients receiving treatment for nAMD, in comparison to a manually coded model built using the same dataset. Furthermore, we evaluate model performance across ethnic groups and analyse how the models reach their predictions., Methods: Binary classification models were trained to predict whether patients' VA would be 'Above' or 'Below' a score of 70 one year after initiating treatment, measured using the Early Treatment Diabetic Retinopathy Study (ETDRS) chart. The AutoML model was built using the Google Cloud Platform, whilst the bespoke model was trained using an XGBoost framework. Models were compared and analysed using the What-if Tool (WIT), a novel model-agnostic interpretability tool., Results: Our study included 1631 eyes from patients attending Moorfields Eye Hospital. The AutoML model (area under the curve [AUC], 0.849) achieved a highly similar performance to the XGBoost model (AUC, 0.847). Using the WIT, we found that the models over-predicted negative outcomes in Asian patients and performed worse in those with an ethnic category of Other. Baseline VA, age and ethnicity were the most important determinants of model predictions. Partial dependence plot analysis revealed a sigmoidal relationship between baseline VA and the probability of an outcome of 'Above'., Conclusion: We have described and validated an AutoML-WIT pipeline which enables clinicians with minimal coding skills to match the performance of a state-of-the-art algorithm and obtain explainable predictions., (© 2022. The Author(s).)

Purpose: To generate a prognostic model to predict keratoconus progression to corneal crosslinking (CXL)., Design: Retrospective cohort study., Methods: We recruited 5025 patients (9341 eyes) with early keratoconus between January 2011 and November 2020. Genetic data from 926 patients were available. We investigated both keratometry or CXL as end points for progression and used the Royston-Parmar method on the proportional hazards scale to generate a prognostic model. We calculated hazard ratios (HRs) for each significant covariate, with explained variation and discrimination, and performed internal-external cross validation by geographic regions., Results: After exclusions, model fitting comprised 8701 eyes, of which 3232 underwent CXL. For early keratoconus, CXL provided a more robust prognostic model than keratometric progression. The final model explained 33% of the variation in time to event: age HR (95% CI) 0.9 (0.90-0.91), maximum anterior keratometry 1.08 (1.07-1.09), and minimum corneal thickness 0.95 (0.93-0.96) as significant covariates. Single-nucleotide polymorphisms (SNPs) associated with keratoconus (n=28) did not significantly contribute to the model. The predicted time-to-event curves closely followed the observed curves during internal-external validation. Differences in discrimination between geographic regions was low, suggesting the model maintained its predictive ability., Conclusions: A prognostic model to predict keratoconus progression could aid patient empowerment, triage, and service provision. Age at presentation is the most significant predictor of progression risk. Candidate SNPs associated with keratoconus do not contribute to progression risk., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Purpose: To describe the frequency of long-term morphologic features and their relationships with visual function in participants who exited the Inhibition of VEGF in Age-Related Choroidal Neovascularisation (IVAN; ISRCTN92166560) trial., Design: Multicenter cohort study up to 7 years after enrollment., Participants: Patients enrolled in the IVAN trial, excluding participants who died or withdrew during the trial., Methods: Multimodal fundus images, best-corrected visual acuity (BCVA), and low-luminance visual acuity (LLVA) were obtained for a subset of 199 participants who attended a research visit. Clinical sites (n = 20) also provided all visual acuity and clinical information from usual care records for 532 participants and submitted the most recent color, OCT, and other fundus images for 468 participants to a reading center., Main Outcome Measures: Assessed the following from the most recent images: intralesional macular atrophy (ILMA) within the footprint of the neovascular lesion; hyperreflective material (HRM); intraretinal fluid (IRF); subretinal fluid (SRF); pigment epithelial detachment (PED); and disorganized retinal outer layers (DROLs). Cross-sectional relationships between morphologic features and BCVA/LLVA were estimated., Results: Intralesional macular atrophy was present in 31.8% of the study eyes at IVAN exit (mean follow-up, 1.96 years) and 89.5% at the most recent imaging visit (mean follow-up, 6.18 years). Hyperreflective material, IRF, SRF, PED, and DROLs were present in 78.8%, 47.7%, 7.6%, 94.5%, and 55% of the study eyes, respectively. In the subset with complete imaging data, in eyes without DROL, the BCVA was worst in the thinnest outer fovea tertile (thinnest minus middle and thickest tertiles, -19.7 and -19.5 letters, respectively), whereas in eyes with DROL, the BCVA was worst in the thickest (thinnest and middle tertiles minus thickest, 12.5 and 12.2, respectively). Regression models showed that the presence of ILMA and HRM was independently associated with BCVA (22 letters worse [95% confidence interval {CI}, -11.2 to -32.8; P < 0.001] and 9.8 letters worse [95% CI, -0.1 to -19.4; P = 0.047], respectively). Subretinal fluid and foveal PED were associated with better BCVA (5.9 letters [95% CI, -7.9 to 19.7; P = 0.399] and 6.4 letters [95% CI, -1.1 to 14.0; P = 0.094], respectively). The model with LLVA was similar. A sensitivity analysis involving the entire eligible cohort yielded similar estimates., Conclusions: Macular atrophy and HRM were common after 7 years of follow-up and strongly associated with visual outcomes., (Crown Copyright © 2022. Published by Elsevier Inc. All rights reserved.)

Introduction: Novel teleophthalmology technologies have the potential to reduce unnecessary and inaccurate referrals between community optometry practices and hospital eye services and as a result improve patients' access to appropriate and timely eye care. However, little is known about the acceptability and facilitators and barriers to the implementations of these technologies in real life., Methods and Analysis: A theoretically informed, qualitative study will explore patients' and healthcare professionals' perspectives on teleophthalmology and Artificial Intelligence Decision Support System models of care. A combination of situated observations in community optometry practices and hospital eye services, semistructured qualitative interviews with patients and healthcare professionals and self-audiorecordings of healthcare professionals will be conducted. Participants will be purposively selected from 4 to 5 hospital eye services and 6-8 affiliated community optometry practices. The aim will be to recruit 30-36 patients and 30 healthcare professionals from hospital eye services and community optometry practices. All interviews will be audiorecorded, with participants' permission, and transcribed verbatim. Data from interviews, observations and self-audiorecordings will be analysed thematically and will be informed by normalisation process theory and an inductive approach., Ethics and Dissemination: Ethical approval has been received from London-Bromley research ethics committee. Findings will be reported through academic journals and conferences in ophthalmology, health services research, management studies and human-computer interaction., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Aims: To describe past trends and future projections for the number of intravitreal injections being administered at a large tertiary hospital in London, United Kingdom., Methods: Retrospective data from Moorfields Eye Hospital were collected using the electronic medical record system. Descriptive statistics were used to visualise overall trends. Time series forecasting was used to predict the number of injections that will be administered up to and including the year 2029., Results: The number of injections has increased nearly 11-fold from 2009 to 2019, with a total of 44,924 injections delivered in 2019. The majority of injections were given for the treatment of neovascular age-related macular degeneration. Aflibercept formed 87% of injections administered in 2019. The number of injections is predicted to continue to increase every year, with nearly 83,000 injections forecasted in the year 2029., Conclusion: The demand for intravitreal injections has increased substantially over the last decade and is predicted to further increase. Healthcare systems will need to adapt to accommodate the high demand. Other solutions may include longer-acting therapies to reduce the treatment burden., (© 2021. The Author(s).)

Background/objectives: To re-evaluate diabetic papillopathy using optical coherence tomography (OCT) for quantitative analysis of the peripapillary retinal nerve fibre layer (pRNFL), macular ganglion cell layer (mGCL) and inner nuclear layer (mINL) thickness., Subjects/methods: In this retrospective observational case series between June 2008 and July 2019 at Moorfields Eye hospital, 24 eyes of 22 patients with diabetes and optic disc swelling with confirmed diagnosis of NAION or diabetic papillopathy by neuro-ophthalmological assessment were included for evaluation of the pRNFL, mGCL and mINL thicknesses after resolution of optic disc swelling., Results: The mean age of included patients was 56.5 (standard deviation (SD) ± 14.85) years with a mean follow-up duration of 216 days. Thinning of pRNFL (mean: 66.26, SD ± 31.80 µm) and mGCL (mean volume: 0.27 mm 3 , SD ± 0.09) were observed in either group during follow-up, the mINL volume showed no thinning with 0.39 ± 0.05 mm 3 . The mean decrease in visual acuity was 4.13 (SD ± 14.27) ETDRS letters with a strong correlation between mGCL thickness and visual acuity (rho 0.74, p < 0.001)., Conclusion: After resolution of acute optic disc swelling, atrophy of pRNFL and mGCL became apparent in all cases of diabetic papillopathy and diabetic NAION, with preservation of mINL volumes. Analysis of OCT did not provide a clear diagnostic distinction between both entities. We suggest a diagnostic overlay with the degree of pRNFL and mGCL atrophy of prognostic relevance for poor visual acuity independent of the semantics of terminology., (© 2021. The Author(s).)

Aim: To examine the associations of air pollution with both self-reported age-related macular degeneration (AMD), and in vivo measures of retinal sublayer thicknesses., Methods: We included 115 954 UK Biobank participants aged 40-69 years old in this cross-sectional study. Ambient air pollution measures included particulate matter, nitrogen dioxide (NO 2 ) and nitrogen oxides (NO x ). Participants with self-reported ocular conditions, high refractive error (< -6 or > +6 diopters) and poor spectral-domain optical coherence tomography (SD-OCT) image were excluded. Self-reported AMD was used to identify overt disease. SD-OCT imaging derived photoreceptor sublayer thickness and retinal pigment epithelium (RPE) layer thickness were used as structural biomarkers of AMD for 52 602 participants. We examined the associations of ambient air pollution with self-reported AMD and both photoreceptor sublayers and RPE layer thicknesses., Results: After adjusting for covariates, people who were exposed to higher fine ambient particulate matter with an aerodynamic diameter <2.5 µm (PM 2.5 , per IQR increase) had higher odds of self-reported AMD (OR=1.08, p=0.036), thinner photoreceptor synaptic region (β=-0.16 µm, p=2.0 × 10 -5 ), thicker photoreceptor inner segment layer (β=0.04 µm, p=0.001) and thinner RPE (β=-0.13 µm, p=0.002). Higher levels of PM 2.5 absorbance and NO 2 were associated with thicker photoreceptor inner and outer segment layers, and a thinner RPE layer. Higher levels of PM 10 (PM with an aerodynamic diameter <10 µm) was associated with thicker photoreceptor outer segment and thinner RPE, while higher exposure to NO x was associated with thinner photoreceptor synaptic region., Conclusion: Greater exposure to PM 2.5 was associated with self-reported AMD, while PM 2.5 , PM 2.5 absorbance, PM 10 , NO 2 and NO x were all associated with differences in retinal layer thickness., Competing Interests: Competing interests: CR reports employment by Topcon Healthcare Solutions, Inc, outside the submitted work. PJF reports personal fees from Allergan, Carl Zeiss, Google/DeepMind and Santen, a grant from Alcon, outside the submitted work. PJP reports grants from Topcon Inc, outside the submitted work., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Computer vision, understood as the area of science that trains computers to interpret digital images through both artificial intelligence (AI) and classical algorithms, has significantly advanced the analysis and interpretation of optical coherence tomography (OCT) in retina research. The aim of this review is to summarise the recent advances of computer vision in imaging processing in uveitis, with a particular focus in optical coherence tomography images., Material and Methods: Literature review., Results: The development of computer vision to assist uveitis diagnosis and prognosis is still undergoing, but important efforts have been made in the field., Conclusion: The automatising of image processing in uveitis could be fundamental to establish objective and standardised outcomes for future clinical trials. In addition, it could help to better understand the disease and its progression.

Purpose: Retinal signatures of systemic disease ('oculomics') are increasingly being revealed through a combination of high-resolution ophthalmic imaging and sophisticated modelling strategies. Progress is currently limited not mainly by technical issues, but by the lack of large labelled datasets, a sine qua non for deep learning. Such data are derived from prospective epidemiological studies, in which retinal imaging is typically unimodal, cross-sectional, of modest number and relates to cohorts, which are not enriched with subpopulations of interest, such as those with systemic disease. We thus linked longitudinal multimodal retinal imaging from routinely collected National Health Service (NHS) data with systemic disease data from hospital admissions using a privacy-by-design third-party linkage approach., Participants: Between 1 January 2008 and 1 April 2018, 353 157 participants aged 40 years or older, who attended Moorfields Eye Hospital NHS Foundation Trust, a tertiary ophthalmic institution incorporating a principal central site, four district hubs and five satellite clinics in and around London, UK serving a catchment population of approximately six million people., Findings to Date: Among the 353 157 individuals, 186 651 had a total of 1 337 711 Hospital Episode Statistics admitted patient care episodes. Systemic diagnoses recorded at these episodes include 12 022 patients with myocardial infarction, 11 735 with all-cause stroke and 13 363 with all-cause dementia. A total of 6 261 931 retinal images of seven different modalities and across three manufacturers were acquired from 1 54 830 patients. The majority of retinal images were retinal photographs (n=1 874 175) followed by optical coherence tomography (n=1 567 358)., Future Plans: AlzEye combines the world's largest single institution retinal imaging database with nationally collected systemic data to create an exceptional large-scale, enriched cohort that reflects the diversity of the population served. First analyses will address cardiovascular diseases and dementia, with a view to identifying hidden retinal signatures that may lead to earlier detection and risk management of these life-threatening conditions., Competing Interests: Competing interests: SKW is funded through a Medical Research Council Clinical Research Training Fellowship (MR/TR000953/1). NP is funded by a Moorfields Eye Charity Career Development Award (R190031A). HM is supported by the National Institute for Health Research’s (NIHR) Comprehensive Biomedical Research Centre (BRC) at University College London Hospitals. SEP receives support from the NIHR BRC at Barts. KB has received speaker fees from Novartis, Bayer, Alimera, Allergan, Roche and Heidelberg; meeting or travel fees from Novartis and Bayer; compensation for being on an advisory board from Novartis and Bayer; consulting fees from Novartis and Roche and research support from Apellis, Novartis and Bayer. AP receives financial support from the NIHR BRC based at Moorfields Eye Hospital (MEH) NHS Foundation Trust and UCL Institute of Ophthalmology; is part of the Steering Committee of the Advanced Nerve and Glaucoma Imaging (ANGI) network which is sponsored by ZEISS and Steering Committee of the OCTiMS Study which is sponsored by Novartis and reports speaker fees from Heidelberg Engineering. JSR receives support from the NIHR as a senior investigator and via the NIHR BRCs at MEH and Great Ormond Street Hospital. AKD is director of INSIGHT, the HDRUK Health Data Research Hub for Eye Health. PAK is supported by a Moorfields Eye Charity Career Development Award (R190028A) and a UK Research & Innovation Future Leaders Fellowship (MR/T019050/1); receives research support from Apellis; is a consultant for DeepMind, Roche, Novartis, Apellis and Bitfount; is an equity owner in Big Picture Medical and has received speaker fees from Heidelberg Engineering, Topcon, Allergan, Roche and Bayer, meeting or travel fees from Novartis and Bayer and compensation for being on an advisory board from Novartis and Bayer., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: To describe the clinical outcomes following implementation of a high-volume medical retina virtual clinic utilising a diagnostic hub., Methods: Retrospective consecutive case-series of all patients attending the medical retina virtual clinics at Moorfields Eye Hospital (City Road) for 6 weeks from September 21, 2020., Results: In 6 weeks, 1006 patients attended the medical retina virtual clinics, which included an appointment in the diagnostic hub followed by an assessment asynchronously the following working day. The vast majority of patients were follow-up attendances (969, 96.3%) with much fewer new patient attendances (37, 3.7%). The most common diagnoses made overall were diabetic retinopathy (457, 45.4%), age-related macular degeneration (208, 20.7%) and retinal vein occlusion (80, 8.0%). The majority of patient (643, 63.9%) outcomes were follow-up in the medical retina virtual clinics including 313 (31.1%) with OCT-only pathway and 330 (32.8%) with OCT and widefield fundus imaging. Routine follow-up requested after virtual assessment included 320 (31.8%) with a 3-4 month review and 267 (26.5%) with a 6 months assessment. Only 62 patients (6.2%) were asked to return for face-to-face assessment within 2 weeks., Conclusions: We describe a new high-volume medical retina virtual clinic utilising a diagnostic hub in which more than 1000 patients were seen and assessed asynchronously. Most patients were assessed as suitable for routine follow-up in this virtual pathway and only a small proportion required urgent reviews (within 2 weeks). In the COVID-19 era, this form of high-volume virtual clinic has the potential to review patients efficiently and safely., (© 2021. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)

Importance: Telemedicine is accelerating the remote detection and monitoring of medical conditions, such as vision-threatening diseases. Meaningful deployment of smartphone apps for home vision monitoring should consider the barriers to patient uptake and engagement and address issues around digital exclusion in vulnerable patient populations., Objective: To quantify the associations between patient characteristics and clinical measures with vision monitoring app uptake and engagement., Design, Setting, and Participants: In this cohort and survey study, consecutive adult patients attending Moorfields Eye Hospital receiving intravitreal injections for retinal disease between May 2020 and February 2021 were included., Exposures: Patients were offered the Home Vision Monitor (HVM) smartphone app to self-test their vision. A patient survey was conducted to capture their experience. App data, demographic characteristics, survey results, and clinical data from the electronic health record were analyzed via regression and machine learning., Main Outcomes and Measures: Associations of patient uptake, compliance, and use rate measured in odds ratios (ORs)., Results: Of 417 included patients, 236 (56.6%) were female, and the mean (SD) age was 72.8 (12.8) years. A total of 258 patients (61.9%) were active users. Uptake was negatively associated with age (OR, 0.98; 95% CI, 0.97-0.998; P = .02) and positively associated with both visual acuity in the better-seeing eye (OR, 1.02; 95% CI, 1.00-1.03; P = .01) and baseline number of intravitreal injections (OR, 1.01; 95% CI, 1.00-1.02; P = .02). Of 258 active patients, 166 (64.3%) fulfilled the definition of compliance. Compliance was associated with patients diagnosed with neovascular age-related macular degeneration (OR, 1.94; 95% CI, 1.07-3.53; P = .002), White British ethnicity (OR, 1.69; 95% CI, 0.96-3.01; P = .02), and visual acuity in the better-seeing eye at baseline (OR, 1.02; 95% CI, 1.01-1.04; P = .04). Use rate was higher with increasing levels of comfort with use of modern technologies (β = 0.031; 95% CI, 0.007-0.055; P = .02). A total of 119 patients (98.4%) found the app either easy or very easy to use, while 96 (82.1%) experienced increased reassurance from using the app., Conclusions and Relevance: This evaluation of home vision monitoring for patients with common vision-threatening disease within a clinical practice setting revealed demographic, clinical, and patient-related factors associated with patient uptake and engagement. These insights inform targeted interventions to address risks of digital exclusion with smartphone-based medical devices.

Introduction: Recent years have witnessed an upsurge of demand in eye care services in the UK. With a large proportion of patients referred to Hospital Eye Services (HES) for diagnostics and disease management, the referral process results in unnecessary referrals from erroneous diagnoses and delays in access to appropriate treatment. A potential solution is a teleophthalmology digital referral pathway linking community optometry and HES., Methods and Analysis: The HERMES study (Teleophthalmology-enabled and artificial intelligence-ready referral pathway for community optometry referrals of retinal disease: a cluster randomised superiority trial with a linked diagnostic accuracy study) is a cluster randomised clinical trial for evaluating the effectiveness of a teleophthalmology referral pathway between community optometry and HES for retinal diseases. Nested within HERMES is a diagnostic accuracy study, which assesses the accuracy of an artificial intelligence (AI) decision support system (DSS) for automated diagnosis and referral recommendation. A postimplementation, observational substudy, a within-trial economic evaluation and discrete choice experiment will assess the feasibility of implementation of both digital technologies within a real-life setting. Patients with a suspicion of retinal disease, undergoing eye examination and optical coherence tomography (OCT) scans, will be recruited across 24 optometry practices in the UK. Optometry practices will be randomised to standard care or teleophthalmology. The primary outcome is the proportion of false-positive referrals (unnecessary HES visits) in the current referral pathway compared with the teleophthalmology referral pathway. OCT scans will be interpreted by the AI DSS, which provides a diagnosis and referral decision and the primary outcome for the AI diagnostic study is diagnostic accuracy of the referral decision made by the Moorfields-DeepMind AI system. Secondary outcomes relate to inappropriate referral rate, cost-effectiveness analyses and human-computer interaction (HCI) analyses., Ethics and Dissemination: Ethical approval was obtained from the London-Bromley Research Ethics Committee (REC 20/LO/1299). Findings will be reported through academic journals in ophthalmology, health services research and HCI., Trial Registration Number: ISRCTN18106677 (protocol V.1.1)., Competing Interests: Competing interests: PAK has previously been consultant for Google DeepMind., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: Choroidal naevi are a common incidental finding prompting specialist referrals to ocular oncology. Rarely, such lesions have sufficient suspicious features to diagnose a small melanoma. The aim of the study is to show that 'virtual' imaging-based pathways are a safe and efficient option to manage such referrals., Methods: A prospective cohort study at the Manchester Royal Eye Hospital and Moorfields Eye Hospital between June 2016 and July 2017 of the management decision of 400 patients reviewed by an ophthalmologist in a face-to-face consultation (gold standard) supported by fundus photography, optical coherence tomography, autofluorescence (AF) and B-mode ultrasound. The images were also read independently by blinded graders (non-medical) and blinded ophthalmologists, and a management decision was made based on image review alone (virtual pathway). The two pathways were compared for safety., Results: The agreement for management decisions between face-to-face and virtual pathways was 83.1% (non-medical) and 82.6% (medical). There were more over-referrals in the virtual pathway (non-medical 24.3%, medical 23.3% of gold standard discharge) and only two under-referrals (10.5% of gold standard referrals), both borderline cases with minimal clinical risk. The agreement for risk factors of growth (orange pigment, subretinal fluid, hyper-AF) ranged between 82.3% and 97.3%., Conclusions: We prospectively validated a virtual clinic model for the safe management of choroidal naevi. Such a model of care is feasible with low rate of under-referral. An over-referral rate of almost 24% from the vitrual pathway needs to be factored into designing such pathways in conjunction with evidence on their cost-effectiveness., Competing Interests: Competing interests: None of the authors have any financial disclosures or conflicts of interest to declare., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Keratoconus is a disorder characterized by progressive thinning and distortion of the cornea. If detected at an early stage, corneal collagen cross-linking can prevent disease progression and further visual loss. Although advanced forms are easily detected, reliable identification of subclinical disease can be problematic. Several different machine learning algorithms have been used to improve the detection of subclinical keratoconus based on the analysis of multiple types of clinical measures, such as corneal imaging, aberrometry, or biomechanical measurements., Objective: The aim of this study is to survey and critically evaluate the literature on the algorithmic detection of subclinical keratoconus and equivalent definitions., Methods: For this systematic review, we performed a structured search of the following databases: MEDLINE, Embase, and Web of Science and Cochrane Library from January 1, 2010, to October 31, 2020. We included all full-text studies that have used algorithms for the detection of subclinical keratoconus and excluded studies that did not perform validation. This systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations., Results: We compared the measured parameters and the design of the machine learning algorithms reported in 26 papers that met the inclusion criteria. All salient information required for detailed comparison, including diagnostic criteria, demographic data, sample size, acquisition system, validation details, parameter inputs, machine learning algorithm, and key results are reported in this study., Conclusions: Machine learning has the potential to improve the detection of subclinical keratoconus or early keratoconus in routine ophthalmic practice. Currently, there is no consensus regarding the corneal parameters that should be included for assessment and the optimal design for the machine learning algorithm. We have identified avenues for further research to improve early detection and stratification of patients for early treatment to prevent disease progression., (©Howard Maile, Ji-Peng Olivia Li, Daniel Gore, Marcello Leucci, Padraig Mulholland, Scott Hau, Anita Szabo, Ismail Moghul, Konstantinos Balaskas, Kaoru Fujinami, Pirro Hysi, Alice Davidson, Petra Liskova, Alison Hardcastle, Stephen Tuft, Nikolas Pontikos. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 13.12.2021.)

Background: To describe 10-year trends in visual outcomes, anatomical outcomes and treatment burden of patients receiving antivascular endothelial growth factor (anti-VEGF) therapy for neovascular age-related macular degeneration (nAMD)., Methods: Retrospective cohort study of treatment-naïve, first-affected eyes with nAMD started on ranibizumab before January 1, 2009. The primary outcome was time to best-corrected visual acuity (BCVA) falling ≤35 ETDRS letters after initiating anti-VEGF therapy. Secondary outcomes included time to BCVA reaching ≥70 letters, proportion of eyes with BCVA ≥70 and ≤35 letters in 10 years, mean trend of BCVA and central retinal thickness over 10 years, and mean number of injections., Results: For our cohort of 103 patients, Kaplan-Meier analyses demonstrated median time to BCVA reaching ≤35 and ≥70 letters were 37.8 (95% CI 22.2 to 65.1) and 8.3 (95% CI 4.8 to 20.9) months after commencing anti-VEGF therapy, respectively. At the final follow-up, BCVA was ≤35 letters and ≥70 letters in 41.1% and 21%, respectively, in first-affected eyes, while this was the case for 5.4% and 48.2%, respectively, in a patient's better-seeing eye. Mean injection number was 37.0±24.2 per eye and 53.6±30.1 at patient level (63.1% of patients required injections in both eyes)., Conclusions: The chronicity of nAMD disease and its management highlights the importance of long-term visual prognosis. Our analyses suggest that one in five patients will retain good vision (BCVA ≥70 ETDRS letters) in the first-affected eye at 10 years after starting anti-VEGF treatment; yet, one in two patients will have good vision in their better-seeing eye. Moreover, our data suggest that early treatment of nAMD is associated with better visual outcomes., (© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: To assess inter-device agreement in optical coherence tomography-derived retinal thickness measurements in patients with known macular conditions between spectral-domain and swept-source optical coherence tomography (OCT)., Methods: Two hundred seventy-two subjects were included in the study. They consisted of 91 male (33.5%) and 181 female (66.5%) subjects, and 132 left (48.5%) and 140 right (51.5%) eyes. Each subject underwent spectral-domain OCT (SD-OCT, Spectralis, Heidelberg Engineering; RTVue XR Avanti XR HD, Optovue) and swept-source OCT (SS-OCT; DRI-OCT-1, Atlantis, Topcon) in a single imaging session performed by the same clinical trial-certified technician. The comparison of retinal thickness reproducibility between devices was performed using Bland-Altman analyses and across the entire data set using the intraclass correlation coefficient (ICC)., Results: The ICC of the retinal thickness measurements (95% confidence interval) made using all three OCT instruments was 0.81 (0.77-0.84). The mean difference in mean retinal thickness between Spectralis SD-OCT and Topcon SS-OCT was 59.1 μm (95% limit of agreement [LoA] -21.7 to 139.8 μm). The mean difference in mean retinal thickness between Optovue SD-OCT and Topcon SS-OCT was 21.8 μm (95% LoA -34.7  to 78.3 μm)., Conclusions: Retinal layer thickness measurements vary between SS-OCT and SD-OCT devices. We describe inter-device agreement in retinal thickness between SS-OCT and SD-OCT in patients with macular conditions. Clinicians should be aware of the differences in retinal thickness values when imaging patients using different OCT devices and should consider using the same OCT device model in order to monitor clinical change., Trial Registration: ClinicalTrials.gov Identifier (NCT02828215)., (© 2021. The Author(s).)

Purpose: To evaluate the predictive usefulness of quantitative imaging biomarkers, acquired automatically from OCT scans, of cross-sectional and future visual outcomes of patients with neovascular age-related macular degeneration (AMD) starting anti-vascular endothelial growth factor (VEGF) therapy., Design: Retrospective cohort study., Participants: Treatment-naive, first-treated eyes of patients with neovascular AMD between 2007 and 2017 at Moorfields Eye Hospital (a large, United Kingdom single center) undergoing anti-VEGF therapy., Methods: Automatic segmentation was carried out by applying a deep learning segmentation algorithm to 137 379 OCT scans from 6467 eyes of 3261 patients with neovascular AMD. After applying selection criteria, 926 eyes of 926 patients were analyzed., Main Outcome Measures: Correlation coefficients (R 2 values) and mean absolute error (MAE) between quantitative OCT (qOCT) parameters and cross-sectional visual function, as well as the predictive value of these parameters for short-term visual change, that is, incremental visual acuity (VA) resulting from an individual injection, as well as VA at distant time points (up to 12 months after baseline)., Results: Visual acuity at distant time points could be predicted: R 2  = 0.80 (MAE, 5.0 Early Treatment Diabetic Retinopathy Study [ETDRS] letters) and R 2  = 0.7 (MAE, 7.2 ETDRS letters) after injection at 3 and at 12 months after baseline (P < 0.001 for both), respectively. Best performing models included both baseline qOCT parameters and treatment response. Furthermore, we present proof-of-principle evidence that the incremental change in VA from an injection can be predicted: R 2  = 0.14 (MAE, 5.6 ETDRS letters) for injection 2 and R 2  = 0.11 (MAE, 5.0 ETDRS letters) for injection 3 (P < 0.001 for both)., Conclusions: Automatic segmentation enables rapid acquisition of quantitative and reproducible OCT biomarkers with potential to inform treatment decisions in the care of neovascular AMD. This furthers development of point-of-care decision-aid systems for personalized medicine., (Copyright © 2021 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

The fovea is a depression in the center of the macula and is the site of the highest visual acuity. Optical coherence tomography (OCT) has contributed considerably in elucidating the pathologic changes in the fovea and is now being considered as an accompanying imaging method in drug development, such as antivascular endothelial growth factor and its safety profiling. Because animal numbers are limited in preclinical studies and automatized image evaluation tools have not yet been routinely employed, essential reference data describing the morphologic variations in macular thickness in laboratory cynomolgus monkeys are sparse to nonexistent. A hybrid machine learning algorithm was applied for automated OCT image processing and measurements of central retina thickness and surface area values. Morphological variations and the effects of sex and geographical origin were determined. Based on our findings, the fovea parameters are specific to the geographic origin. Despite morphological similarities among cynomolgus monkeys, considerable variations in the foveolar contour, even within the same species but from different geographic origins, were found. The results of the reference database show that not only the entire retinal thickness, but also the macular subfields, should be considered when designing preclinical studies and in the interpretation of foveal data., (© 2021. The Author(s).)

Background/objectives: Abnormal retinal neovascularization caused by ischemic retinal vein occlusion (RVO) is a frequent cause of visually significant vitreous hemorrhage. The early detection of new vessels may be challenging and often requires the use of invasive tests such as fundus fluorescein angiography (FA). We demonstrate the use of wide-field optical coherence tomography angiography (WF-OCTA) in the detection and characterization of neovascularization secondary to ischemic RVO., Subjects/methods: We conducted a retrospective observational case series of patients diagnosed with ischemic RVO between August 2018 and March 2019, who underwent WF-SS-OCTA imaging (PLEX Elite 9000, Carl Zeiss Meditec). We performed real-life montage imaging, covering the involved area and compared the findings of WF-SS-OCTA to standard clinical examination and when available, ultrawide-field fluorescein angiography (UWF-FA, Optos 200TX)., Results: In the included 39 eyes with ischemic RVO, neovascularization elsewhere (NVE) was encountered in 16 of 39 eyes (41%) on WF-OCTA and were characterized as sea-fan type vessels and nodular type vessels, based on their appearance and localization. NVE was identified in 4/39 eyes on standard clinical examination, equating to a detection rate of 10.3%. All were of a sea-fan morphology. In one case, NVE found on WF-OCTA was not observed on UWF-FA, which was a nodular type. Neovascularization of the disc (NVD) was detected in one eye., Conclusions: WF-OCTA may become a useful noninvasive tool in the detection of neovascularization in patients with ischemic RVO. Furthermore, the characterization of different morphologies of neovascularization detected by WF-OCTA could be of clinical relevance., (© 2020. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)

Importance: Quantitative volumetric measures of retinal disease in optical coherence tomography (OCT) scans are infeasible to perform owing to the time required for manual grading. Expert-level deep learning systems for automatic OCT segmentation have recently been developed. However, the potential clinical applicability of these systems is largely unknown., Objective: To evaluate a deep learning model for whole-volume segmentation of 4 clinically important pathological features and assess clinical applicability., Design, Setting, Participants: This diagnostic study used OCT data from 173 patients with a total of 15 558 B-scans, treated at Moorfields Eye Hospital. The data set included 2 common OCT devices and 2 macular conditions: wet age-related macular degeneration (107 scans) and diabetic macular edema (66 scans), covering the full range of severity, and from 3 points during treatment. Two expert graders performed pixel-level segmentations of intraretinal fluid, subretinal fluid, subretinal hyperreflective material, and pigment epithelial detachment, including all B-scans in each OCT volume, taking as long as 50 hours per scan. Quantitative evaluation of whole-volume model segmentations was performed. Qualitative evaluation of clinical applicability by 3 retinal experts was also conducted. Data were collected from June 1, 2012, to January 31, 2017, for set 1 and from January 1 to December 31, 2017, for set 2; graded between November 2018 and January 2020; and analyzed from February 2020 to November 2020., Main Outcomes and Measures: Rating and stack ranking for clinical applicability by retinal specialists, model-grader agreement for voxelwise segmentations, and total volume evaluated using Dice similarity coefficients, Bland-Altman plots, and intraclass correlation coefficients., Results: Among the 173 patients included in the analysis (92 [53%] women), qualitative assessment found that automated whole-volume segmentation ranked better than or comparable to at least 1 expert grader in 127 scans (73%; 95% CI, 66%-79%). A neutral or positive rating was given to 135 model segmentations (78%; 95% CI, 71%-84%) and 309 expert gradings (2 per scan) (89%; 95% CI, 86%-92%). The model was rated neutrally or positively in 86% to 92% of diabetic macular edema scans and 53% to 87% of age-related macular degeneration scans. Intraclass correlations ranged from 0.33 (95% CI, 0.08-0.96) to 0.96 (95% CI, 0.90-0.99). Dice similarity coefficients ranged from 0.43 (95% CI, 0.29-0.66) to 0.78 (95% CI, 0.57-0.85)., Conclusions and Relevance: This deep learning-based segmentation tool provided clinically useful measures of retinal disease that would otherwise be infeasible to obtain. Qualitative evaluation was additionally important to reveal clinical applicability for both care management and research.