Developing a Continuous Severity Scale for Macular Telangiectasia Type 2 Using Deep Learning and Implications for Disease Grading.

PURPOSE: Deep learning (DL) models have achieved state-of-the-art medical diagnosis classification accuracy. Current models are limited by discrete diagnosis labels, but could yield more information with diagnosis in a continuous scale. We developed a novel continuous severity scaling system for macular telangiectasia (MacTel) type 2 by combining a DL classification model with uniform manifold approximation and projection (UMAP). DESIGN: We used a DL network to learn a feature representation of MacTel severity from discrete severity labels and applied UMAP to embed this feature representation into 2 dimensions, thereby creating a continuous MacTel severity scale. PARTICIPANTS: A total of 2003 OCT volumes were analyzed from 1089 MacTel Project participants. METHODS: We trained a multiview DL classifier using multiple B-scans from OCT volumes to learn a previously published discrete 7-step MacTel severity scale. The classifiers' last feature layer was extracted as input for UMAP, which embedded these features into a continuous 2-dimensional manifold. The DL classifier was assessed in terms of test accuracy. Rank correlation for the continuous UMAP scale against the previously published scale was calculated. Additionally, the UMAP scale was assessed in the κ agreement against 5 clinical experts on 100 pairs of patient volumes. For each pair of patient volumes, clinical experts were asked to select the volume with more severe MacTel disease and to compare them against the UMAP scale. MAIN OUTCOME MEASURES: Classification accuracy for the DL classifier and κ agreement versus clinical experts for UMAP. RESULTS: The multiview DL classifier achieved top 1 accuracy of 63.3% (186/294) on held-out test OCT volumes. The UMAP metric showed a clear continuous gradation of MacTel severity with a Spearman rank correlation of 0.84 with the previously published scale. Furthermore, the continuous UMAP metric achieved κ agreements of 0.56 to 0.63 with 5 clinical experts, which was comparable with interobserver κ values. CONCLUSIONS: Our UMAP embedding generated a continuous MacTel severity scale, without requiring continuous training labels. This technique can be applied to other diseases and may lead to more accurate diagnosis, improved understanding of disease progression, and key imaging features for pathologic characteristics. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

A Novel Role for Corneal Pachymetry in Planning Cataract Surgery by Determining Changes in Spherical Equivalent Resulting from a Previous LASIK Treatment.

Objectives: To provide a metric to differentiate between hyperopic and myopic ablation of a prior LASIK treatment based on the corneal pachymetry profile after laser vision correction (LVC). Methods: Pachymetry data were retrospectively recovered from patients who had previous LASIK for refractive purposes between 2019 and 2020. Patients with any corneal disorder were excluded. Ablation spherical equivalent was predicted from the central to semiperipheral corneal thickness (CPT) ratio, both values were provided by using the Pentacam user interface software (UI), and values were computed from extracted raw pachymetry data. Results: Data of 157 eyes of 81 patients were collected, of which data were analysed for 73 eyes of 73 patients to avoid concurrence of measurements in both eyes per subject (42% female; mean age 40.9; SD 12.8). The CPT ratio cutoff for distinction between myopic and hyperopic LASIK was 0.86 for Pentacam UI data. Sensitivity and specificity were 0.7 and 0.95, respectively. Accuracy increased with computation of the CPT ratio based on extracted raw data with sensitivity and specificity of 0.87 and 0.99, respectively. There was a marked linear correlation between the CPT ratio and the ablation spherical equivalent (R2 = 0.93). Conclusions: CPT ratio cutoffs can correctly classify if a cornea previously had a hyperopic versus myopic LASIK surgery and estimate the ablation spherical equivalent of such treatment. This could prove useful for increased accuracy of intraocular lens (IOL) calculations for patients with no historical data of their prior LVC surgery at the time of cataract surgery planning.

Macular Telangiectasia Type 2: A Classification System Using MultiModal Imaging MacTel Project Report Number 10.

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.

Description of a patient cohort with Hereditary Sensory Neuropathy type 1 without retinal disease Macular Telangiectasia type 2 - implications for retinal screening in HSN1.

Pathogenic variants in the genes encoding serine palmitoyl transferase (SPTLC1 or SPTLC2) are the most common causes of the rare peripheral nerve disorder Hereditary Sensory Neuropathy Type 1 (HSN1). Macular telangiectasia type 2 (MacTel), a retinal disorder associated with disordered serine-glycine metabolism, has been described in some patients with HSN1. This study aims to further investigate this association in a cohort of people with HSN1. Fourteen patients with a clinically and genetically confirmed diagnosis of HSN1 from the National Hospital for Neurology and Neurosurgery (NHNN, University College London Hospitals NHS Foundation Trust, London, United Kingdom) were recruited to the MacTel Registry, between July 2018 and April 2019. Two additional patients were identified from the dataset of the international clinical registry study (www.lmri.net). Ocular examination included fundus autofluorescence, blue light and infrared reflectance, macular pigment optical density mapping and optical coherence tomography. Twelve patients had a pathogenic variant in the SPTLC1 gene, with p.Cys133Trp in 11 cases (92%) and p.Cys133Tyr in one case (8%). Four patients had a variant in the SPTLC2 gene. None of the patients showed clinical evidence of MacTel. The link between HSN1 and MacTel seems more complex than can solely be explained by the genetic variants. An extension of the spectrum of SPTLC1/2-related disease with phenotypic pleiotropy is proposed. HSN1 patients should be screened for visual symptoms and referred for specialist retinal screening, but the association of the two diseases is likely to be variable and remains unexplained.

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.

Fundus Autofluorescence Imaging in Macular Telangiectasia Type 2: MacTel Study Report Number 9.

PURPOSE: To investigate the role of fundus autofluorescence (FAF) imaging in the diagnosis of macular telangiectasia type 2 (MacTel) and to describe disease-associated FAF patterns and their origin. DESIGN: Cross-sectional multicenter study METHODS: FAF images were collected from the multicenter MacTel Natural History Observation and Registry Study. In a first qualitative approach, common FAF phenotypes were defined and correlated with multimodal imaging. We then evaluated how many eyes showed FAF changes, and temporal vs nasal asymmetry of FAF changes was graded. Finally, 100 eyes of MacTel patients and 100 control eyes (50 normal eyes and 50 eyes with other macular diseases) were combined and 2 masked graders assessed the presence of MacTel based on FAF images alone. RESULTS: The study included 807 eyes of 420 patients (33 eyes were excluded owing to poor image quality). Loss of macular pigment, cystoid spaces, pigment plaques, neovascular membranes, and ectatic vascular changes commonly caused characteristic changes on FAF images. All MacTel patients had macular FAF changes in at least 1 eye. In 95% of eyes, these changes were more pronounced temporally than nasally. Common FAF patterns were increased (60%) and mixed/decreased FAF (38%) and/or visibility of vascular changes such as blunted vessels or ectatic capillaries (79%). Based on those features, high diagnostic performance was achieved for detection of the disease based on FAF alone (Youden index up to 0.91). CONCLUSIONS: The study demonstrates that MacTel is consistently associated with disease-specific changes on FAF imaging. Those changes are typically more pronounced in the temporal parafovea.

Identification of genetic factors influencing metabolic dysregulation and retinal support for MacTel, a retinal disorder.

Macular Telangiectasia Type 2 (MacTel) is a rare degenerative retinal disease with complex genetic architecture. We performed a genome-wide association study on 1,067 MacTel patients and 3,799 controls, which identified eight novel genome-wide significant loci (p < 5 × 10-8), and confirmed all three previously reported loci. Using MAGMA, eQTL and transcriptome-wide association analysis, we prioritised 48 genes implicated in serine-glycine biosynthesis, metabolite transport, and retinal vasculature and thickness. Mendelian randomization indicated a likely causative role of serine (FDR = 3.9 × 10-47) and glycine depletion (FDR = 0.006) as well as alanine abundance (FDR = 0.009). Polygenic risk scoring achieved an accuracy of 0.74 and was associated in UKBiobank with retinal damage (p = 0.009). This represents the largest genetic study on MacTel to date and further highlights genetically-induced systemic and tissue-specific metabolic dysregulation in MacTel patients, which impinges on retinal health.

Quantification of Key Retinal Features in Early and Late Age-Related Macular Degeneration Using Deep Learning.

PURPOSE: We sought to develop and validate a deep learning model for segmentation of 13 features associated with neovascular and atrophic age-related macular degeneration (AMD). DESIGN: Development and validation of a deep-learning model for feature segmentation. METHODS: Data for model development were obtained from 307 optical coherence tomography volumes. Eight experienced graders manually delineated all abnormalities in 2712 B-scans. A deep neural network was trained with these data to perform voxel-level segmentation of the 13 most common abnormalities (features). For evaluation, 112 B-scans from 112 patients with a diagnosis of neovascular AMD were annotated by 4 independent observers. The main outcome measures were Dice score, intraclass correlation coefficient, and free-response receiver operating characteristic curve. RESULTS: On 11 of 13 features, the model obtained a mean Dice score of 0.63 ± 0.15, compared with 0.61 ± 0.17 for the observers. The mean intraclass correlation coefficient for the model was 0.66 ± 0.22, compared with 0.62 ± 0.21 for the observers. Two features were not evaluated quantitatively because of a lack of data. Free-response receiver operating characteristic analysis demonstrated that the model scored similar or higher sensitivity per false positives compared with the observers. CONCLUSIONS: The quality of the automatic segmentation matches that of experienced graders for most features, exceeding human performance for some features. The quantified parameters provided by the model can be used in the current clinical routine and open possibilities for further research into treatment response outside clinical trials.

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

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. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? One-in-four randomized controlled trials in ophthalmology are single-armed, which poses challenges for interpreting their efficacy relative to standard of care. Recent conceptual advances in the methods of causal inference and in the emulation of target trials suggests that the standard-of-care arms representing the counterfactual intervention can be approximated with observational data. WHAT QUESTION DID THIS STUDY ADDRESS? How real-world cohorts representing the counterfactual intervention can aid the interpretation of single-armed ophthalmological trials. WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? Our study highlights how real-world cohorts representing the counterfactual intervention could aid the interpretation of single-armed ophthalmological trials when undertaken in accord with the target trial framework. HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE? External counterfactual arms could reduce the time and cost to reach potential regulatory approval.

HYPERREFLECTIVITY ON OPTICAL COHERENCE TOMOGRAPHY IN MACULAR TELANGIECTASIA TYPE 2.

PURPOSE: To define, characterize, and classify hyperreflectivity on optical coherence tomography and report its prevalence in macular telangiectasia Type 2. METHODS: In a primary cross-sectional analysis, multimodal imaging data were retrospectively analyzed. The definition of hyperreflectivity and neovascularization on optical coherence tomography followed optical coherence tomography angiography-based criteria. Eyes were graded for the presence of hyperreflectivity and neovascularization and further categorized into three classes based on position and extent of hyperreflectivity. In a secondary analysis, eyes were reviewed for ≥24 months using optical coherence tomography imaging. RESULTS: Three hundred and twenty-two eyes from 161 patients were analyzed in the cross-sectional analysis. Hyperreflectivity was found in 177 (55%) and neovascular membranes in 49 (15%) eyes. Hyperreflectivity correlated significantly with parameters indicative of disease progression. In the longitudinal analysis, 206 eyes from 103 patients were reviewed over a mean of 35.6 months. 17/86 eyes (20%) showed a de novo development of hyperreflectivity. 8/29 eyes (28%) with preexistent intraretinal hyperreflectivity developed outer retinal hyperreflectivity. A high proportion of eyes with outer retinal hyperreflectivity (17/52 [33%]) developed neovascular membranes. CONCLUSION: Hyperreflectivity represents a common finding in macular telangiectasia Type 2 but lacks a uniform definition. We propose a hyperreflectivity grading scale that may help to estimate disease progression and identify eyes at risk for developing neovascular membranes.

WITHDRAWN: Hyper-reflectivity on optical coherence tomography in macular telangiectasia type 2.

Ahead of Print article withdrawn by publisher.

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.

[Artificial intelligence in ophthalmology : Guidelines for physicians for the critical evaluation of studies]. / Künstliche Intelligenz in der Augenheilkunde : Leitfaden für Ärzte zur kritischen Bewertung von Studien.

BACKGROUND: Empirical models have been an integral part of everyday clinical practice in ophthalmology since the introduction of the Sanders-Retzlaff-Kraff (SRK) formula. Recent developments in the field of statistical learning (artificial intelligence, AI) now enable an empirical approach to a wide range of ophthalmological questions with an unprecedented precision. OBJECTIVE: Which criteria must be considered for the evaluation of AI-related studies in ophthalmology? MATERIAL AND METHODS: Exemplary prediction of visual acuity (continuous outcome) and classification of healthy and diseased eyes (discrete outcome) using retrospectively compiled optical coherence tomography data (50 eyes of 50 patients, 50 healthy eyes of 50 subjects). The data were analyzed with nested cross-validation (for learning algorithm selection and hyperparameter optimization). RESULTS: Based on nested cross-validation for training, visual acuity could be predicted in the separate test data-set with a mean absolute error (MAE, 95% confidence interval, CI of 0.142 LogMAR [0.077; 0.207]). Healthy versus diseased eyes could be classified in the test data-set with an agreement of 0.92 (Cohen's kappa). The exemplary incorrect learning algorithm and variable selection resulted in an MAE for visual acuity prediction of 0.229 LogMAR [0.150; 0.309] for the test data-set. The drastic overfitting became obvious on comparison of the MAE with the null model MAE (0.235 LogMAR [0.148; 0.322]). CONCLUSION: Selection of an unsuitable measure of the goodness-of-fit, inadequate validation, or withholding of a null or reference model can obscure the actual goodness-of-fit of AI models. The illustrated pitfalls can help clinicians to identify such shortcomings.

Systemic lipid dysregulation is a risk factor for macular neurodegenerative disease.

Macular Telangiectasia type 2 (MacTel) is an uncommon bilateral retinal disease, in which glial cell and photoreceptor degeneration leads to central vision loss. The causative disease mechanism is largely unknown, and no treatment is currently available. A previous study found variants in genes associated with glycine-serine metabolism (PSPH, PHGDH and CPS1) to be associated with MacTel, and showed low levels of glycine and serine in the serum of MacTel patients. Recently, a causative role of deoxysphingolipids in MacTel disease has been established. However, little is known about possible other metabolic dysregulation. Here we used a global metabolomics platform in a case-control study to comprehensively profile serum from 60 MacTel patients and 58 controls. Analysis of the data, using innovative computational approaches, revealed a detailed, disease-associated metabolic profile with broad changes in multiple metabolic pathways. This included alterations in the levels of several metabolites that are directly or indirectly linked to glycine-serine metabolism, further validating our previous genetic findings. We also found changes unrelated to PSPH, PHGDH and CPS1 activity. Most pronounced, levels of several lipid groups were altered, with increased phosphatidylethanolamines being the most affected lipid group. Assessing correlations between different metabolites across our samples revealed putative functional connections. Correlations between phosphatidylethanolamines and sphingomyelin, and glycine-serine and sphingomyelin, observed in controls, were reduced in MacTel patients, suggesting metabolic re-wiring of sphingomyelin metabolism in MacTel patients. Our findings provide novel insights into metabolic changes associated with MacTel and implicate altered lipid metabolism as a contributor to this retinal neurodegenerative disease.

Macular Telangiectasia Type 2: Visual Acuity, Disease End Stage, and the MacTel Area: MacTel Project Report Number 8.

PURPOSE: To report the visual acuity measures from the macular telangiectasia type 2 (MacTel) registry and to investigate and describe phenotypic findings in eyes with substantial vision loss resulting from MacTel. DESIGN: Cross-sectional multicenter study. PARTICIPANTS: Participants in the MacTel Natural History Observation Registration Study. METHODS: Best-corrected visual acuity (BCVA) data, retinal imaging data, and clinical data were accessed from the MacTel Study databases in May 2019. MAIN OUTCOME MEASURES: Frequency distribution of BCVA and its relationship to age; morphologic changes in eyes with very late disease stages, defined by a BCVA of 20/200 or worse; average retinal thickness of macular subfields on OCT; and dimensions of the area affected by MacTel (i.e., the MacTel area). RESULTS: Best-corrected visual acuity was 20/50 or worse in 37.3% and 20/200 or worse in 3.8% of 4449 eyes of 2248 patients; 18.4% and 0.7% of all patients showed bilateral BCVA of 20/50 or worse and 20/200 or worse, respectively. Asymmetry between right and left eyes was present (median BCVA, 71 letters vs. 74 letters), a finding supported by more advanced morphologic changes in right eyes. Participant age correlated with BCVA, but the effect size was small. If a neovascularization or macular hole were present, bilateral occurrence was frequent (33% or 17%, respectively), and BCVA was better than 20/200 (79% or 78%, respectively) or 20/50 or better (26% or 13%, respectively). Eyes with advanced disease (BCVA, ≤20/200) showed the following characteristics: (1) atrophy of the foveal photoreceptor layer with or without associated subretinal fibrosis; (2) an affected area, termed MacTel area, limited to a horizontal diameter not exceeding the distance between the temporal optic disc margin and foveal center, and the vertical diameter not exceeding approximately 0.8 times this distance (exceptions were eyes with large active or inactive neovascular membranes); (3) reduced retinal thickness measures within the MacTel area; and (4) less frequent retinal greying and more frequent hyperpigmentations compared with eyes that have better BCVA. CONCLUSIONS: Severe vision loss is rare in MacTel and is related to photoreceptor atrophy in most people. Results indicate disease asymmetry with slightly worse vision and more advanced disease manifestation in right eyes. MacTel-related neurodegeneration does not spread beyond the limits of the MacTel area.

Effect of Face-Down Positioning vs Support-the-Break Positioning After Macula-Involving Retinal Detachment Repair: The PostRD Randomized Clinical Trial.

Importance: A lack of consensus exists with regard to the optimal positioning regimen for patients after macula-involving retinal detachment (RD) repair. Objective: To evaluate the effect of face-down positioning vs support-the-break positioning on retinal displacement and distortion after macula-involving RD repair. Design, Setting, and Participants: A prospective 6-month single-masked randomized clinical trial was conducted at a multicenter tertiary referral setting from May 16, 2016, to May 1, 2018. Inclusion criteria were fovea-involving rhegmatogenous RD; central visual loss within 14 days; patients undergoing primary vitrectomy and gas surgery, under local anesthetic; patients able to give written informed consent; and 18 years old and older. Analysis was conducted following a modified intention-to-treat principle, with patients experiencing a redetachment or failure to attach the macula being excluded from analysis. Interventions: Participants were randomized 1:1 to receive face-down positioning or support-the-break positioning for a 24-hour period postoperatively. Positioning compliance was not monitored. Main Outcomes and Measures: The proportion of patients with retinal displacement on autofluorescence imaging at 6 months postoperatively. Secondary outcomes included proportion of patients with displacement at 2 months; amplitude of displacement at 2 and 6 months; corrected Early Treatment Diabetic Retinopathy Study visual acuity; objective Distortion Scores; and quality of life questionnaire scores at 6 months. Results: Of the 262 randomized patients, 239 were analyzed (171 male [71.5%]; mean [SD] age, 60.8 [9.8] years). At 6 months, retinal displacement was detected in 42 of 100 (42%) in the face-down positioning group vs 58 of 103 (56%) in the support-the-break positioning group (odds ratio, 1.77; 95%CI, 1.01-3.11; P = .04). The degree of displacement was lower in the face-down group. Groups were similar in corrected visual acuity (face-down, 74 letters vs support-the-break, 75 letters), objective D Chart Distortion Scores (range: 0, no distortion to 41.6, severe distortion; with face-down at 4.5 vs support-the-break at 4.2), and quality of life scores (face-down 89.3 vs support-the-break 89.0) at 2 and 6 months. Retinal redetachment rate was similar in both groups (face-down group, 12.2% and support-the-break group, 13.7%). Retinal folds were less common in the face-down positioning group vs the support-the-break positioning group (5.3% vs 13.5%, respectively; odds ratio, 2.8; 95% CI, 1.2-7.4; P = .03). Binocular diplopia was more common in the support-the-break group compared with the face-down positioning group (7.6% vs 1.5%, respectively; odds ratio, 5.3; 95% CI, 1.3-24.6; P = .03). Amplitude of displacement was associated with worse visual acuity (r = -0.5; P < .001) and distortion (r = 0.28; P = .008). Conclusions and Relevance: In this study, findings suggest that face-down positioning was associated with a reduction in the rate and amplitude of postoperative retinal displacement after macula-involving RD repair and with a reduction in binocular diplopia. No association was found with visual acuity or postoperative distortion. Trial Registration: ClinicalTrials.gov Identifier: NCT02748538.

Novel biomarker of sphericity and cylindricity indices in volume-rendering optical coherence tomography angiography in normal and diabetic eyes: a preliminary study.

PURPOSE: Preliminary to evaluate geometric indices (vessel sphericity and cylindricity) for volume-rendered optical coherence tomography angiography (OCTA) in healthy and diabetic eyes. METHODS: Twenty-six eyes of 13 healthy subjects and 12 eyes of patients with central ischemic, non-proliferative diabetic retinopathy were included. OCTA volume and surface area of the foveal vessels were measured and compared to determine OCTA sphericity and cylindricity indices and surface efficiency (SE). RESULTS: The overall average OCTA volume in healthy was 0.49 ± 0.09 mm3 (standard deviation [SD]), compared to 0.44 ± 0.07 mm3 (SD) in the diabetic eyes (difference in means 0.06 mm3, p = 0.054). The overall average OCTA surface area in the healthy eyes was 87.731 ± 9.51 mm2 (SD), compared to 76.65 ± 13.67 mm2 (SD) in the diabetic eyes (difference in means 11.08 mm2, p = 0.021). In relation to total foveolar tissue volume, the proportion of blood vessels was 22% in healthy individuals and only 20% in diabetics. The difference between the groups was more pronounced with respect to the total OCTA surface area, with a decrease of 13% in diabetics. A diabetic eye was most likely using geometric vessel indices analysis if the sphericity value was ≥ 0.190, with a cylindricity factor of ≥ 0.001. Reproducibility of the method was good. CONCLUSIONS: A method for OCTA surface area and volume measurements was developed. The application of the novel OCTA sphericity and cylindricity indices could be suitable as temporal biomarker to characterize stable disease or disease progression and may contribute to a better understanding in the evolution of diabetic retinopathy.

Postretinal Detachment Retinal Displacement: How Best to Detect It?

PURPOSE: The reported incidence of postretinal detachment (RD) macular displacement varies markedly (14-72%). This may in part be due to the imaging modalities used. We compared the ability of 2 types of fundus autofluorescence (FAF) imaging modalities to detect this phenomenon. METHODS: Prospective study of 70 eyes with macula-involving RDs. 8 weeks postoperatively, patients underwent FAF imaging with 2 machines: a confocal scanning laser ophthalmoscope (cSLO) and a digital fundus camera (FC). Images were graded for the presence of hyperautofluorescent RPE (retinal pigment epithelium) ghost vessels, indicative of retinal displacement, by 2 masked, independent graders. RESULTS: In total, 87.1% of FC images were gradable versus 88.6% of cSLO images. Retinal displacement was detectable in 61.4% of FC images versus 52.8% of cSLO images. Vessel shift often appeared more autofluorescent on FC imaging, but choroidal vessels were more visible. Cohen's agreement between the imaging modalities was 0.50, rated as moderate agreement. For both imaging modalities, the inter- and intragrader agreement was substantial, representing good test-retest reliability. CONCLUSIONS: Detection of post-RD retinal displacement was similar between FC and cSLO FAF imaging, with only moderate agreement between both modalities.

DARK ADAPTATION IN MACULAR TELANGIECTASIA TYPE 2.

PURPOSE: To evaluate dark adaptation (DA) in patients with macular telangiectasia Type 2 (MacTel). METHODS: After a local photobleach (4 × 4° size, 83% bleach), DA was measured using a test stimulus (2° diameter) projected at 5° eccentricity horizontal from the foveal center within the temporal parafovea. Cone plateau, rod intercept time, and rod recovery rate (S2) were calculated from the resulting DA curves. Findings were correlated with disease stages (according to Gass and Blodi), the area of ellipsoid zone loss in optical coherence tomography, and macular pigment loss ("MP-Classes 1-3"). RESULTS: Fifty-nine eyes of 59 patients were compared with 18 eyes of 18 healthy controls. Dark adaptation was significantly impaired in patients with MacTel. Although differences were most pronounced for parameters indicating rod-mediated recovery, cone-mediated recovery was also decreased, yet to a lesser extent. Dark adaptation parameters were only weakly associated with disease stages and ellipsoid zone loss. A better association was found between rod-mediated recovery (S2 and rod intercept time) and macular pigment loss (Kendall's tau for rod intercept time: 0.69 and S2: -0.51; both P < 0.0001). CONCLUSION: Dark adaptation is significantly impaired in patients with MacTel. Our results indicate an association of reduced macular pigment and rod dysfunction in MacTel.