Automated Detection of Glaucoma With Interpretable Machine Learning Using Clinical Data and Multimodal Retinal Images

PURPOSE

To develop a multimodal model to automate glaucoma detection DESIGN: Development of a machine-learning glaucoma detection model METHODS: We selected a study cohort from the UK Biobank data set with 1193 eyes of 863 healthy subjects and 1283 eyes of 771 subjects with glaucoma. We trained a multimodal model that combines multiple deep neural nets, trained on macular optical coherence tomography volumes and color fundus photographs, with demographic and clinical data. We performed an interpretability analysis to identify features the model relied on to detect glaucoma. We determined the importance of different features in detecting glaucoma using interpretable machine learning methods. We also evaluated the model on subjects who did not have a diagnosis of glaucoma on the day of imaging but were later diagnosed (progress-to-glaucoma [PTG]).

RESULTS

Results show that a multimodal model that combines imaging with demographic and clinical features is highly accurate (area under the curve 0.97). Interpretation of this model highlights biological features known to be related to the disease, such as age, intraocular pressure, and optic disc morphology. Our model also points to previously unknown or disputed features, such as pulmonary function and retinal outer layers. Accurate prediction in PTG highlights variables that change with progression to glaucoma-age and pulmonary function.

CONCLUSIONS

The accuracy of our model suggests distinct sources of information in each imaging modality and in the different clinical and demographic variables. Interpretable machine learning methods elucidate subject-level prediction and help uncover the factors that lead to accurate predictions, pointing to potential disease mechanisms or variables related to the disease.

Uncovering of intraspecies macular heterogeneity in cynomolgus monkeys using hybrid machine learning optical coherence tomography image segmentation

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.

Effect of ethnicity and other sociodemographic factors on attendance at diabetic eye screening: a 12-month retrospective cohort study

OBJECTIVES

To examine the association of sociodemographic characteristics with attendance at diabetic eye screening in a large ethnically diverse urban population.

DESIGN

Retrospective cohort study.

SETTING

Screening visits in the North East London Diabetic Eye Screening Programme (NELDESP).

PARTICIPANTS

84 449 people with diabetes aged 12 years or older registered in the NELDESP and scheduled for screening between 1 April 2017 and 31 March 2018.

MAIN OUTCOME MEASURE

Attendance at diabetic eye screening appointments.

RESULTS

The mean age of people with diabetes was 60 years (SD 14.2 years), 53.4% were men, 41% South Asian, 29% White British and 17% Black; 83.4% attended screening. Black people with diabetes had similar levels of attendance compared with White British people. However, South Asian, Chinese and 'Any other Asian' background ethnicities showed greater odds of attendance compared with White British. When compared with their respective reference group, high levels of deprivation, younger age, longer duration of diabetes and worse visual acuity, were all associated with non-attendance. There was a higher likelihood of attendance per quintile improvement in deprivation (OR, 1.06; 95% CI, 1.03 to 1.08), with increasing age (OR per decade, 1.17; 95% CI, 1.15 to 1.19), with better visual acuity (OR per Bailey-Lovie chart line 1.12; 95% CI, 1.11 to 1.14) and with longer time of NELDESP registration (OR per year, 1.02; 95% CI, 1.01 to 1.03).

CONCLUSION

Ethnic differences in diabetic eye screening uptake, though small, are evident. Despite preconceptions, a higher likelihood of screening attendance was observed among Asian ethnic groups when compared with the White ethnic group. Poorer socioeconomic profile was associated with higher likelihood of non-attendance for screening. Further work is needed to understand how to target individuals at risk of non-attendance and reduce inequalities.

Evolving Treatment Patterns and Outcomes of Neovascular Age-Related Macular Degeneration Over a Decade

PURPOSE

Management of neovascular age-related macular degeneration (nAMD) has evolved over the last decade with several treatment regimens and medications. This study describes the treatment patterns and visual outcomes over 10 years in a large cohort of patients.

DESIGN

Retrospective analysis of electronic health records from 27 National Health Service secondary care healthcare providers in the UK.

PARTICIPANTS

Treatment-naïve patients receiving at least 3 intravitreal anti-vascular endothelial growth factor (VEGF) injections for nAMD in their first 6 months of follow-up were included. Patients with missing data for age or gender and those aged less than 55 years were excluded.

METHODS

Eyes with at least 3 years of follow-up were grouped by years of treatment initiation, and 3-year outcomes were compared between the groups. Data were generated during routine clinical care between September 2008 and December 2018.

MAIN OUTCOME MEASURES

Visual acuity (VA), number of injections, and number of visits.

RESULTS

A total of 15 810 eyes of 13 705 patients receiving 195 104 injections were included. Visual acuity improved from baseline during the first year, but decreased thereafter, resulting in loss of visual gains. This trend remained consistent throughout the past decade. Although an increasing proportion of eyes remained in the driving standard, this was driven by better presenting VA over the decade. The number of injections decreased substantially between the first and subsequent years, from a mean of 6.25 in year 1 to 3 in year 2 and 2.5 in year 3, without improvement over the decade. In a multivariable regression analysis, final VA improved by 0.24 letters for each year since 2008, and younger age and baseline VA were significantly associated with VA at 3 years.

CONCLUSIONS

Our findings show that despite improvement in functional VA over the years, primarily driven by improving baseline VA, patients continue to lose vision after the first year of treatment, with only marginal change over the past decade. The data suggest these results may be related to suboptimal treatment patterns, which have not improved over the years. Rethinking treatment strategies may be warranted, possibly on a national level or through the introduction of longer-acting therapies.

Foveal structure and visual function in nanophthalmos and posterior microphthalmos

BACKGROUND/AIMS

The reason for visual impairment in patients with nanophthalmos and posterior microphthalmos is not completely understood. Therefore, this study aims to investigate foveal structure, and the impact of demographic, clinical and imaging parameters on best-corrected visual acuity (BCVA) in these conditions.

METHODS

Sixty-two eyes of 33 patients with nanophthalmos (n=40) or posterior microphthalmos (n=22), and 114 eyes of healthy controls with high-resolution retinal imaging including spectral-domain or swept-source optical coherence tomography images were included in this cross-sectional case-control study. Foveal retinal layer thickness was determined by two independent readers. A mixed-effect model was used to perform structure-function correlations and predict the BCVA based on subject-specific variables.

RESULTS

Most patients (28/33) had altered foveal structure associated with loss of foveal avascular zone and impaired BCVA. However, widening of outer nuclear layer, lengthening of photoreceptor outer segments, normal distribution of macular pigment and presence of Henle fibres were consistently found. Apart from the presence of choroidal effusion, which had significant impact on BCVA, the features age, refractive error, axial length and retinal layer thickness at the foveal centre explained 61.7% of the variability of BCVA.

CONCLUSION

This study demonstrates that choroidal effusion, age, refractive error, axial length and retinal layer thickness are responsible for the majority of interindividual variability of BCVA as well as the morphological foveal heterogeneity in patients with nanophthalmos or posterior microphthalmos. This might give further insights into the physiology of foveal development and the process of emmetropisation, and support clinicians in the assessment of these disease entities.

Real world evidence on 5661 patients treated for macular oedema secondary to branch retinal vein occlusion with intravitreal anti-vascular endothelial growth factor, intravitreal dexamethasone or macular laser

BACKGROUND/AIMS

Clinical trials suggest anti-vascular endothelial growth factor is more effective than intravitreal dexamethasone as treatment for macular oedema secondary to branch retinal vein occlusion. This study asks if 'real world' data from a larger and more diverse population, followed for a longer period, also support this conclusion.

METHODS

Data collected to support routine care at 27 NHS (National Health Service) Trusts between February 2002 and September 2017 contained 5661 treatment-naive patients with a single mode of treatment for macular oedema secondary to branch retinal vein occlusion and no history of cataract surgery either during or recently preceding the treatment. Number of treatment visits and change in visual acuity from baseline was plotted for three treatment groups (anti-vascular endothelial growth factor (anti-VEGF), intravitreal dexamethasone, macular laser) for up to 3 years.

RESULTS

Mean baseline visual acuity was 57.1/53.1/62.3 letters in the anti-VEGF/dexamethasone/macular laser groups, respectively. This changed to 66.72 (+9.6)/57.6 (+4.5)/63.2 (+0.9) at 12 months. Adequate numbers allowed analysis at 18 months for all groups (66.6 (+9.5)/56.1 (+3.0)/60.8 (-1.5)) and for anti-VEGF at 36 months (68.0, +10.9) Mean number of treatments were 5.1/1.5/1.2 at 12 months, 5.9/1.7/1.2 at 18 months for all three groups and 10.3 at 36 months for anti-VEGF.

CONCLUSIONS

Visual acuity improvements were higher and more sustained with anti-VEGF. Higher treatment burden occurred with anti-VEGF but this reduced over 36 months. Patients with better vision at baseline than those in the clinical trials maintained high levels of vision with both anti-VEGF and dexamethasone.

Contextualizing single-arm trials with real-world data: An emulated target trial comparing therapies for neovascular age-related macular degeneration

Abstract

One‐in‐four ophthalmology trials are single‐armed, which poses challenges to their interpretation. We demonstrate how real‐world cohorts used as external/synthetic control arms can contextualize such trials. We herein emulated a target trial on the intention‐to‐treat efficacy of off‐label bevacizumab (q6w) pro re nata relative to fixed‐interval aflibercept (q8w) for improving week 54 visual acuity of eyes affected by neovascular age‐related macular degeneration. The bevacizumab arm (n = 65) was taken from the ABC randomized controlled trial. A total of 4,471 aflibercept‐treated eyes aligning with the ABC trial eligibility were identified from electronic health records and synthetic control arms were created by emulating randomization conditional on age, sex, and baseline visual read via exact matching and propensity score methods. We undertook an inferiority analysis on mean difference at 54 weeks; outcomes regression on achieving a change in visual acuity of greater than or equal to 15, greater than or equal to 10, and less than or equal to −15 Early Treatment Diabetic Retinopathy (ETDRS) letters at week 54; and a time‐to‐event analysis on achieving a change in visual acuity of greater than or equal to 15, greater than or equal to 10, and less than or equal to −15 ETDRS letters by week 54. The findings suggest off‐label bevacizumab to be neither inferior nor superior to licensed aflibercept. Our study highlights how real‐world cohorts representing the counterfactual intervention could aid the interpretation of single‐armed trials when analyzed in accord to the target trial framework.

Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence

Machine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image segmentation was enhanced with a Traceable Relevance Explainability (T-REX) technique. The proposed application was based on three components: ground truth generation by multiple graders, calculation of Hamming distances among graders and the machine learning algorithm, as well as a smart data visualization ('neural recording'). An overall average variability of 1.75% between the human graders and the algorithm was found, slightly minor to 2.02% among human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visualized. The convolutional neural network balanced between graders and allowed for modifiable predictions dependent on the compartment. Using the proposed T-REX setup, machine learning processes could be rendered more transparent and understandable, possibly leading to optimized applications.

Intravitreal ranibizumab for the management of serous maculopathy secondary to optic disc coloboma-associated choroidal neovascularisation

We report the case of a 19-year-old patient with symptomatic unilateral serous maculopathy associated with an optic nerve coloboma. Fluorescein angiography detected a focal late leak at the temporal edge of the coloboma which was later found to correspond with an area of choroidal neovascularisation on optical coherence tomography angiography. A course of intravitreal ranibizumab achieved good clinical and structural response. This report contributes to the evidence that maculopathies associated with cavitary optic nerve anomalies may in some instances result from choroidal neovascularisation. It also highlights the importance of angiography to identify potential choroidal neovascular membranes, particularly in the absence of haemorrhages and neovascular membranes on fundus examination and conventional optical coherence tomography.

A virtual-clinic pathway for patients referred from a national diabetes eye screening programme reduces service demands whilst maintaining quality of care

Aim

To evaluate the potential of an integrated virtual medical retina clinic in secondary care for diabetic patients screened and referred by the UK National Diabetic Eye Screening Program (DESP).

Methods

This retrospective cohort study included diabetic patients referred by the DESP to either a virtual or a traditional doctor’s appointment (face-to-face, F2F) at the Moorfields Eye Hospital NHS Foundation Trust (London, UK) between January 2015 and December 2018. The primary outcome was the proportion of patients that qualified for a virtual-clinic appointment according to hospital guidance. Secondary outcomes included the rate of attendance, mean time from DESP referral to initial hospital appointment, mean time-to-discharge and -to-treatment of either panretinal photocoagulation or intravitreal injection of anti-vascular endothelial growth factor.

Results

We included 12,563 patients in this study. While 8833 patients (70.7%) would have qualified for a virtual appointment according to local triage guidance, only 2306 (18.4%) were referred to a virtual consultation due to capacity constraints. For routine referrals, mean time to the first hospital appointment was 66.9 days with a standard deviation of ±35.9 and 80.9 ± 44.4 days for a virtual and a F2F consultation, respectively. The mean time from referral to discharge to community was 71.7 ± 30.8 and 86.3 ± 37.0 days for a virtual and a F2F consultation, respectively. We did not observe a statistically significant difference in the mean time-to-treatment in the sub-cohort that required intravitreal therapy for maculopathy (virtual clinics: 220.7 ± 84.8; F2F: 178.0 days ± 80.7; p value > 0.05). Moreover, we observed a non-inferior attendance rate in virtual as compared to F2F clinics.

Conclusion

A significant proportion of diabetic patients referred to a F2F clinic could initially be managed in a virtual clinic. Increasing the adoption of virtual clinics in the management of diabetic patients that do not need long-term management or monitoring in secondary services may help alleviate service demands without diminishing quality of clinical care. Collectively, our analyses suggest that virtual consultations are a faster and clinically appropriate alternative for a substantial proportion of diabetic patients.

Longitudinal Assessment of Remnant Foveal Cone Structure in a Case Series of Early Macular Telangiectasia Type 2

Purpose

To determine the extent of remnant cone structure within early foveal ellipsoid zone (EZ) lesions in macular telangiectasia type 2 longitudinally using both confocal and split detector adaptive optics scanning light ophthalmoscopy (AOSLO).

Methods

Spectral domain optical coherence tomography (SDOCT), confocal and split detector AOSLO were acquired from seven patients (10 eyes) with small (early) EZ lesions on SDOCT secondary to macular telangiectasia type 2 at baseline, 6 months, and 12 months. The presence of cone structure on AOSLO in areas of EZ loss as well as cones at 1° eccentricity, and their change over time were quantified.

Results

By split detector AOSLO, remnant cone structure was identified within and on the borders of all foveal EZ lesions. Within the extent of these lesions, cone spacing ranged from 4.97 to 9.95 µm at baseline, 5.30 to 6.10 µm at 6 months, and 4.99 to 7.12 µm at 12 months. Four eyes with significantly smaller EZ lesions showed evidence of recovery of EZ reflectivity on SDOCT B-scans. Remnant cone structure was identified in some areas where EZ reflectivity recovered at the following time point. Eyes that showed recovery of EZ reflectivity had a continuous external limiting membrane.

Conclusions

Remnant cone structure can persist within small SDOCT-defined EZ lesions, which can wax and wane in appearance over time. AOSLO can help to inform the interpretation of SDOCT imaging.

Translational Relevance

The absence of EZ in early macular telangiectasia type 2 and other retinal conditions needs careful interpretation because it does not always indicate an absence of underlying cone structure. The integrity of the external limiting membrane may better predict the presence of remnant cone structure and recovery of EZ reflectivity.

Validation of virtual reality orbitometry bridges digital and physical worlds

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

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients

Background/aims

Human grading of digital images from diabetic retinopathy (DR) screening programmes represents a significant challenge, due to the increasing prevalence of diabetes. We evaluate the performance of an automated artificial intelligence (AI) algorithm to triage retinal images from the English Diabetic Eye Screening Programme (DESP) into test-positive/technical failure versus test-negative, using human grading following a standard national protocol as the reference standard.

Methods

Retinal images from 30 405 consecutive screening episodes from three English DESPs were manually graded following a standard national protocol and by an automated process with machine learning enabled software, EyeArt v2.1. Screening performance (sensitivity, specificity) and diagnostic accuracy (95% CIs) were determined using human grades as the reference standard.

Results

Sensitivity (95% CIs) of EyeArt was 95.7% (94.8% to 96.5%) for referable retinopathy (human graded ungradable, referable maculopathy, moderate-to-severe non-proliferative or proliferative). This comprises sensitivities of 98.3% (97.3% to 98.9%) for mild-to-moderate non-proliferative retinopathy with referable maculopathy, 100% (98.7%,100%) for moderate-to-severe non-proliferative retinopathy and 100% (97.9%,100%) for proliferative disease. EyeArt agreed with the human grade of no retinopathy (specificity) in 68% (67% to 69%), with a specificity of 54.0% (53.4% to 54.5%) when combined with non-referable retinopathy.

Conclusion

The algorithm demonstrated safe levels of sensitivity for high-risk retinopathy in a real-world screening service, with specificity that could halve the workload for human graders. AI machine learning and deep learning algorithms such as this can provide clinically equivalent, rapid detection of retinopathy, particularly in settings where a trained workforce is unavailable or where large-scale and rapid results are needed.

Feasibility and Safety of a Coaxial Dual-Wavelength Optical Coherence Tomography Apparatus

PURPOSE

To evaluate the feasibility and safety of a coaxial dual-wavelength optical coherence tomography (OCT) device (marked as Hydra-OCT).

METHODS

Healthy participants without ocular pathology underwent retinal imaging using the Hydra-OCT allowing for simultaneous measurement of retinal scanning of 840 and 1,072 nm wavelength. Before and after measurement, best-corrected visual acuity and patients' comfort were assessed. Representative OCT images from both wavelengths were compared by 5 independent graders using a subjective grading scheme.

RESULTS

A total of 30 eyes of 30 participants (8 females and 22 males) with a mean age of 26.5 years (range from 19 to 55 years) were included. Dual-wavelength image acquisition was made possible in each subject. The participant's effort and comfort assessment using the Hydra-OCT imaging revealed an equivalent value as compared to the commercially available OCT machine. No adverse events were reported, and visual acuity was not altered by the Hydra-OCT. Imaging between the systems was comparable.

CONCLUSIONS

This study provides evidence for the feasibility and safety of a coaxial dual-wavelength OCT imaging method under real-life conditions. The novel Hydra-OCT imaging device may offer additional insights into the pathology of retinal and choroidal diseases.

Diagnostic accuracy of diabetic retinopathy grading by an artificial intelligence-enabled algorithm compared with a human standard for wide-field true-colour confocal scanning and standard digital retinal images

BACKGROUND

Photographic diabetic retinopathy screening requires labour-intensive grading of retinal images by humans. Automated retinal image analysis software (ARIAS) could provide an alternative to human grading. We compare the performance of an ARIAS using true-colour, wide-field confocal scanning images and standard fundus images in the English National Diabetic Eye Screening Programme (NDESP) against human grading.

METHODS

Cross-sectional study with consecutive recruitment of patients attending annual diabetic eye screening. Imaging with mydriasis was performed (two-field protocol) with the EIDON platform (CenterVue, Padua, Italy) and standard NDESP cameras. Human grading was carried out according to NDESP protocol. Images were processed by EyeArt V.2.1.0 (Eyenuk Inc, Woodland Hills, California). The reference standard for analysis was the human grade of standard NDESP images.

RESULTS

We included 1257 patients. Sensitivity estimates for retinopathy grades were: EIDON images; 92.27% (95% CI: 88.43% to 94.69%) for any retinopathy, 99% (95% CI: 95.35% to 100%) for vision-threatening retinopathy and 100% (95% CI: 61% to 100%) for proliferative retinopathy. For NDESP images: 92.26% (95% CI: 88.37% to 94.69%) for any retinopathy, 100% (95% CI: 99.53% to 100%) for vision-threatening retinopathy and 100% (95% CI: 61% to 100%) for proliferative retinopathy. One case of vision-threatening retinopathy (R1M1) was missed by the EyeArt when analysing the EIDON images, but identified by the human graders. The EyeArt identified all cases of vision-threatening retinopathy in the standard images.

CONCLUSION

EyeArt identified diabetic retinopathy in EIDON images with similar sensitivity to standard images in a large-scale screening programme, exceeding the sensitivity threshold recommended for a screening test. Further work to optimise the identification of 'no retinopathy' and to understand the differential lesion detection in the two imaging systems would enhance the use of these two innovative technologies in a diabetic retinopathy screening setting.

Progression of Retinopathy Secondary to Maternally Inherited Diabetes and Deafness - Evaluation of Predicting Parameters

PURPOSE

To investigate the prognostic value of demographic, functional, and imaging parameters on retinal pigment epithelium (RPE) atrophy progression secondary to maternally inherited diabetes and deafness (MIDD) and to evaluate the application of these factors in clinical trial design.

DESIGN

Retrospective observational case series.

METHODS

Thirty-five eyes of 20 patients (age range, 24.9-75.9 years) with genetically proven MIDD and demarcated RPE atrophy on serial fundus autofluorescence (AF) images were included. Lesion size and shape-descriptive parameters were longitudinally determined by 2 independent readers. A linear mixed-effect model was used to predict the lesion enlargement rate based on baseline variables. Sample size calculations were performed to model the power in a simulated interventional study.

RESULTS

The mean follow-up time was 4.27 years. The mean progression rate of RPE atrophy was 2.33 mm²/year, revealing a dependence on baseline lesion size (+0.04 [0.02-0.07] mm²/year/mm², P < .001), which was absent after square root transformation. The fovea was preserved in the majority of patients during the observation time. In the case of foveal involvement, the loss of visual acuity lagged behind central RPE atrophy in AF images. Sex, age, and number of atrophic foci predicted future progression rates with a cross-validated mean absolute error of 0.13 mm/year and to reduce the required sample size for simulated interventional trials.

CONCLUSIONS

Progressive RPE atrophy could be traced in all eyes using AF imaging. Shape-descriptive factors and patients' baseline characteristics had significant prognostic value, guiding appropriate subject selection and sample size in future interventional trial design.

The Usefulness of Serum Biomarkers in the Early Stages of Diabetic Retinopathy: Results of the EUROCONDOR Clinical Trial

The main aim of this study was to evaluate the ability of serum biomarkers to predict the worsening of retinal neurodysfunction in subjects with type 2 diabetes. For this purpose, we measured selected molecules (N-epsilon-carboxy methyl lysine (CML), laminin P1 (Lam-P1), and asymmetric dimethylarginine (ADMA)) in the serum of 341 participants of the EUROCONDOR study at baseline, 24, and 48 weeks. Retinal neurodysfunction was assessed by measuring implicit time (IT) using multifocal electroretinography, and structural changes were examined by spectral domain–optical coherence tomography. The values of IT at baseline were directly correlated with baseline serum concentrations of CML (r = 0.135, p = 0.013). Furthermore, in the placebo group, increase in CML concentration throughout follow-up correlated with the IT (r = 0.20; p = 0.03). Baseline serum levels of CML also correlated with macular retinal thickness (RT) (r = 0.231; p < 0.001). Baseline Lam-P1 levels correlated with the increase of the RT at the end of follow-up in the placebo group (r = 0.22; p = 0.016). We provide evidence that CML may be a biomarker of both retinal neurodysfunction and RT, whereas Lam-P1 was associated with RT only. Therefore, circulating levels of these molecules could provide a complementary tool for monitoring the early changes of diabetic retinopathy (DR).

Comparison of true-colour wide-field confocal scanner imaging with standard fundus photography for diabetic retinopathy screening

BACKGROUND

Screening of diabetic retinopathy (DR) reduces blindness by early identification of retinopathy. This study compares DR grades derived from a two-field imaging protocol from two imaging platforms, one providing a single 60-degree horizontal field of view (FOV) and the other, a standard 45-degree FOV.

METHODS

Cross-sectional study which included 1257 diabetic patients aged ≥18 years attending their DR screening visit in the English National Diabetic Eye Screening Programme (NDESP). Patients with maculopathy (M1), preproliferative (R2) or proliferative DR (R3) were referred to an ophthalmologist. Patients with ungradable images (U) are examined in a slit-lamp biomicroscopy clinic. Image acquisition under mydriasis of two images per eye was carried out with the EIDON and with standard fundus cameras. Evaluation was performed by masked graders.

RESULTS

Agreement after consensus with kappa statistic was 0.89 (quadratic weights (95% CI 0.87 to 0.92)) for NDESP severity grade, 0.88 (quadratic weights (95% CI 0.82 to 0.94)) for referable disease and 0.92 (linear weights (95% CI 0.88 to 0.95)) for maculopathy. The EIDON detected clinically relevant DR features outside the 45-degree fields in two patients (0.16%): one with intraretinal microvascular abnormalities (IRMAs) and one with neovascularisation. In eight patients (0.64%), the EIDON allowed DR feature visualisation inside the 45-degree fields that were not identified in the NDESP images: three patients (0.24%) with IRMA and five patients (0.40%) with maculopathy. The rates of ungradable encounters were 12 (0.95%) and 13 (1.03%) with the EIDON and NDESP images, respectively.

CONCLUSION

The EIDON identifies a small number of additional patients with referable disease which are not detected with standard imaging. This is due to the EIDON finding disease outside the standard FOV and greater clarity finding disease within the standard FOV.

Binocular Inhibition of Reading in Macular Telangiectasia Type 2

Purpose

To assess the presence of binocular gain in macular telangiectasia type 2 (MacTel) and its correlation to paracentral scotomas.

Methods

Sixty-eight patients with MacTel were consecutively recruited for a cross-sectional analysis. Best-corrected visual acuity (BCVA), reading acuity, and reading speed were tested monocularly and binocularly. Macular retinal sensitivity was examined with fundus-controlled perimetry (microperimetry). Scotomas were quantified by their size, their depth, and their proximity to the fovea.

Results

Binocular reading speed and acuity were lower than monocular reading speed and acuity in the functionally better eye (142 vs. 159 words per minute and 0.43 vs. 0.28 log reading acuity determination, P < 0.001). Magnitude of binocular inhibition of reading speed was correlated to the degree of interocular functional difference (R2 = 0.61, P < 0.001). This correlation was not found for reading acuity or BCVA (R2 < 0.03). Binocular reading speed was negatively correlated to size of right and left eye scotomas, with bigger effect size for left eye scotomas. The magnitude of binocular inhibition was correlated to size of left eye scotomas, but not of right eye scotomas. When both eyes had similar scotoma characteristics, the right eye was more frequently the better reading eye.

Conclusions

We provide evidence for the presence of binocular inhibition of reading performance in MacTel, likely due to binocular rivalry. This may result from the characteristic paracentral scotomas in noncorresponding retinal fields and, in particular, a disruptive projection of scotomas in reading direction arising from the left eyes. Patients may benefit from occluding one eye while reading.

Progression characteristics of ellipsoid zone loss in macular telangiectasia type 2

PURPOSE

To investigate the progression characteristics of ellipsoid zone (EZ) loss in eyes with macular telangiectasia type 2 (MacTel) as reflected by area and linear measurements, and their relevance for visual acuity.

METHODS

Participants were selected from the MacTel Study cohort. Linear and area measurements of EZ loss were performed in Spectral-Domain Optical Coherence Tomograph (SD-OCT) volume scans. Progression characteristics and correlations between linear and area measurements were analysed using linear mixed effects models.

RESULTS

A total of 134 eyes of 70 patients were included (85 eyes with follow-up, mean 4.7 years, range: 1.4-8 years). Ellipsoid zone (EZ) loss significantly progressed at a mean annual increment of 0.057 mm² (p = 0.005). The progression rate was non-linear and interacted significantly with initial EZ lesion size indicating an exponential growth before reaching a plateau. There was a strong heterogeneity in area sizes between fellow eyes. EZ break length had a significant linear effect on EZ break area (b = 1.06, p < 0.001) and could predict it. The location of the EZ break had a significant impact on visual acuity.

CONCLUSION

Ellipsoid zone (EZ) loss in MacTel has a non-linear progression characteristic, and its rate depends on area size at baseline, which must be taken into account at sample selection in clinical trials. Our results show a good correlation of linear and area measures of EZ loss and a segregation of best-corrected visual acuity by EZ location, which may help routine clinical practice.

Serine and Lipid Metabolism in Macular Disease and Peripheral Neuropathy

BACKGROUND

Identifying mechanisms of diseases with complex inheritance patterns, such as macular telangiectasia type 2, is challenging. A link between macular telangiectasia type 2 and altered serine metabolism has been established previously.

METHODS

Through exome sequence analysis of a patient with macular telangiectasia type 2 and his family members, we identified a variant in SPTLC1 encoding a subunit of serine palmitoyltransferase (SPT). Because mutations affecting SPT are known to cause hereditary sensory and autonomic neuropathy type 1 (HSAN1), we examined 10 additional persons with HSAN1 for ophthalmologic disease. We assayed serum amino acid and sphingoid base levels, including levels of deoxysphingolipids, in patients who had macular telangiectasia type 2 but did not have HSAN1 or pathogenic variants affecting SPT. We characterized mice with low serine levels and tested the effects of deoxysphingolipids on human retinal organoids.

RESULTS

Two variants known to cause HSAN1 were identified as causal for macular telangiectasia type 2: of 11 patients with HSAN1, 9 also had macular telangiectasia type 2. Circulating deoxysphingolipid levels were 84.2% higher among 125 patients with macular telangiectasia type 2 who did not have pathogenic variants affecting SPT than among 94 unaffected controls. Deoxysphingolipid levels were negatively correlated with serine levels, which were 20.6% lower than among controls. Reduction of serine levels in mice led to increases in levels of retinal deoxysphingolipids and compromised visual function. Deoxysphingolipids caused photoreceptor-cell death in retinal organoids, but not in the presence of regulators of lipid metabolism.

CONCLUSIONS

Elevated levels of atypical deoxysphingolipids, caused by variant SPTLC1 or SPTLC2 or by low serine levels, were risk factors for macular telangiectasia type 2, as well as for peripheral neuropathy. (Funded by the Lowy Medical Research Institute and others.).

Validation of automated artificial intelligence segmentation of optical coherence tomography images

PURPOSE

To benchmark the human and machine performance of spectral-domain (SD) and swept-source (SS) optical coherence tomography (OCT) image segmentation, i.e., pixel-wise classification, for the compartments vitreous, retina, choroid, sclera.

METHODS

A convolutional neural network (CNN) was trained on OCT B-scan images annotated by a senior ground truth expert retina specialist to segment the posterior eye compartments. Independent benchmark data sets (30 SDOCT and 30 SSOCT) were manually segmented by three classes of graders with varying levels of ophthalmic proficiencies. Nine graders contributed to benchmark an additional 60 images in three consecutive runs. Inter-human and intra-human class agreement was measured and compared to the CNN results.

RESULTS

The CNN training data consisted of a total of 6210 manually segmented images derived from 2070 B-scans (1046 SDOCT and 1024 SSOCT; 630 C-Scans). The CNN segmentation revealed a high agreement with all grader groups. For all compartments and groups, the mean Intersection over Union (IOU) score of CNN compartmentalization versus group graders' compartmentalization was higher than the mean score for intra-grader group comparison.

CONCLUSION

The proposed deep learning segmentation algorithm (CNN) for automated eye compartment segmentation in OCT B-scans (SDOCT and SSOCT) is on par with manual segmentations by human graders.

Feasibility of support vector machine learning in age-related macular degeneration using small sample yielding sparse optical coherence tomography data

PURPOSE

A retrospective pilot study is conducted to demonstrate the utility of a novel support vector machine learning (SVML) algorithm in a small three-dimensional (3D) sample yielding sparse optical coherence tomography (spOCT) data for the automatic monitoring of neovascular (wet) age-related macular degeneration (wAMD).

METHODS

From the anti-vascular endothelial growth factor injection database, 588 consecutive pairs of OCT volumes (57.624 B-scans) were selected in 70 randomly chosen wAMD patients treated with ranibizumab. The SVML algorithm was applied to 183 OCT volume pairs (17.934 B-scans) in 30 patients. Four independent, diagnosis-blinded retina specialists indicated whether wAMD activity was present between 100 pairs of consecutive OCT volumes (9800 B-scans) in the remaining 40 patients for comparison with the SVML algorithm and a non-complex baseline algorithm using only retinal thickness. The SVML algorithm was assessed using inter-observer variability and receiver operating characteristic (ROC) analyses.

RESULTS

The retina specialists showed an average Cohen's κ of 0.57 ± 0.13 (minimum: 0.41, maximum: 0.83). The average κ between the proposed algorithm and the retina specialists was 0.62 ± 0.05 and 0.43 ± 0.14 between the baseline algorithm and the retina specialists. Using each of the four retina specialists as the reference, the proposed method showed a superior area under the ROC curve of 0.91 ± 0.03 compared to the ROC 0.81 ± 0.05 shown by the baseline algorithm.

CONCLUSION

The SVML algorithm was as effective as the retina specialists were in detecting activity in wAMD. Support vector machine learning (SVML) may be a useful monitoring tool in wAMD suited for small samples that yield sparse OCT data possibly derived from self-measuring OCT-robots.