A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography.

Importance: The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully automated and accurate convolutional neural network-based deep learning algorithm for predicting progression from iAMD to GA within 1 year from spectral-domain optical coherence tomography (SD-OCT) scans. Objective: To develop a deep-learning algorithm based on volumetric SD-OCT scans to predict the progression from iAMD to GA during the year following the scan. Design, Setting, and Participants: This retrospective cohort study included participants with iAMD at baseline and who either progressed or did not progress to GA within the subsequent 13 months. Participants were included from centers in 4 US states. Data set 1 included patients from the Age-Related Eye Disease Study 2 AREDS2 (Ancillary Spectral-Domain Optical Coherence Tomography) A2A study (July 2008 to August 2015). Data sets 2 and 3 included patients with imaging taken in routine clinical care at a tertiary referral center and associated satellites between January 2013 and January 2023. The stored imaging data were retrieved for the purpose of this study from July 1, 2022, to February 1, 2023. Data were analyzed from May 2021 to July 2023. Exposure: A position-aware convolutional neural network with proactive pseudointervention was trained and cross-validated on Bioptigen SD-OCT volumes (data set 1) and validated on 2 external data sets comprising Heidelberg Spectralis SD-OCT scans (data sets 2 and 3). Main Outcomes and Measures: Prediction of progression to GA within 13 months was evaluated with area under the receiver-operator characteristic curves (AUROC) as well as area under the precision-recall curve (AUPRC), sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Results: The study included a total of 417 patients: 316 in data set 1 (mean [SD] age, 74 [8]; 185 [59%] female), 53 in data set 2, (mean [SD] age, 83 [8]; 32 [60%] female), and 48 in data set 3 (mean [SD] age, 81 [8]; 32 [67%] female). The AUROC for prediction of progression from iAMD to GA within 1 year was 0.94 (95% CI, 0.92-0.95; AUPRC, 0.90 [95% CI, 0.85-0.95]; sensitivity, 0.88 [95% CI, 0.84-0.92]; specificity, 0.90 [95% CI, 0.87-0.92]) for data set 1. The addition of expert-annotated SD-OCT features to the model resulted in no improvement compared to the fully autonomous model (AUROC, 0.95; 95% CI, 0.92-0.95; P = .19). On an independent validation data set (data set 2), the model predicted progression to GA with an AUROC of 0.94 (95% CI, 0.91-0.96; AUPRC, 0.92 [0.89-0.94]; sensitivity, 0.91 [95% CI, 0.74-0.98]; specificity, 0.80 [95% CI, 0.63-0.91]). At a high-specificity operating point, simulated clinical trial recruitment was enriched for patients progressing to GA within 1 year by 8.3- to 20.7-fold (data sets 2 and 3). Conclusions and Relevance: The fully automated, position-aware deep-learning algorithm assessed in this study successfully predicted progression from iAMD to GA over a clinically meaningful time frame. The ability to predict imminent GA progression could facilitate clinical trials aimed at preventing the condition and could guide clinical decision-making regarding screening frequency or treatment initiation.

Phase 1 Clinical Trial of Elamipretide in Dry Age-Related Macular Degeneration and Noncentral Geographic Atrophy: ReCLAIM NCGA Study.

Purpose: Assess the safety, tolerability, and feasibility of subcutaneous administration of the mitochondrial-targeted drug elamipretide in patients with dry age-related macular degeneration (AMD) and noncentral geographic atrophy (NCGA) and to perform exploratory analyses of change in visual function. Design: Phase 1, single-center, open-label, 24-week clinical trial with preplanned NCGA cohort. Participants: Adults ≥ 55 years of age with dry AMD and NCGA. Methods: Participants received subcutaneous elamipretide 40-mg daily; safety and tolerability assessed throughout. Ocular assessments included normal-luminance best-corrected visual acuity (BCVA), low-luminance BCVA (LLBCVA), normal-luminance binocular reading acuity (NLBRA), low-luminance binocular reading acuity (LLBRA), spectral-domain OCT, fundus autofluorescence (FAF), and patient self-reported function by low-luminance questionnaire (LLQ). Main Outcome Measures: Primary end point was safety and tolerability. Prespecified exploratory end-points included changes in BCVA, LLBCVA, NLBRA, LLBRA, geographic atrophy (GA) area, and LLQ. Results: Subcutaneous elamipretide was highly feasible. All participants (n = 19) experienced 1 or more nonocular adverse events (AEs), but all AEs were either mild (73.7%) or moderate (26.3%); no serious AEs were noted. Two participants exited the study because of AEs (conversion to neovascular AMD, n = 1; intolerable injection site reaction, n = 1), 1 participant discontinued because of self-perceived lack of efficacy, and 1 participant chose not to continue with study visits. Among participants completing the study (n = 15), mean ± standard deviation (SD) change in BCVA from baseline to week 24 was +4.6 (5.1) letters (P = 0.0032), while mean change (SD) in LLBCVA was +5.4 ± 7.9 letters (P = 0.0245). Although minimal change in NLBRA occurred, mean ± SD change in LLBCVA was -0.52 ± 0.75 logarithm of the minimum angle of resolution units (P = 0.005). Mean ± SD change in GA area (square root transformation) from baseline to week 24 was 0.14 ± 0.08 mm by FAF and 0.13 ± 0.14 mm by OCT. Improvement was observed in LLQ for dim light reading and general dim light vision. Conclusions: Elamipretide seems to be well tolerated without serious AEs in patients with dry AMD and NCGA. Exploratory analyses demonstrated possible positive effect on visual function, particularly under low luminance. A Phase 2b trial is underway to evaluate elamipretide further in dry AMD and NCGA.

Phase 1 Clinical Trial of Elamipretide in Intermediate Age-Related Macular Degeneration and High-Risk Drusen: ReCLAIM High-Risk Drusen Study.

Purpose: To assess safety, tolerability, and feasibility of subcutaneous administration of the mitochondrial-targeted drug elamipretide in patients with intermediate age-related macular degeneration (AMD) and high-risk drusen (HRD) and to perform exploratory analyses of change in visual function. Design: Phase 1, single-center, open-label, 24-week clinical trial with preplanned HRD cohort. Participants: Adult patients ≥55 years of age with intermediate AMD and HRD. Methods: Participants received subcutaneous elamipretide 40 mg daily, with safety and tolerability assessed throughout the study. Ocular assessments included normal-luminance best-corrected visual acuity (BCVA), low-luminance best-corrected visual acuity (LLVA), normal-luminance binocular reading acuity (NLRA), low-luminance binocular reading acuity (LLRA), spectral-domain OCT, fundus autofluorescence (FAF), mesopic microperimetry, dark adaptation, and low-luminance questionnaire (LLQ). Main Outcome Measures: The primary end point was safety and tolerability. Prespecified exploratory end points included changes from baseline in BCVA, LLVA, NLRA, LLRA, retinal pigment epithelium (RPE)-drusen complex (DC) volume by OCT, FAF, mesopic microperimetry, dark adaptation, and LLQ results. Results: Subcutaneous administration of elamipretide was highly feasible. All participants with HRD (n = 21) experienced 1 or more adverse events (AEs), but all were mild (57%) or moderate (43%), with the most common events related to injection site reactions. No serious systemic AEs occurred. One participant discontinued because of injection site reaction, 1 participant withdrew because they did not wish to continue study visits, and 1 participant withdrew after experiencing transient visual impairment. Among the 18 participants who completed the study, mean change in BCVA from baseline to 24 weeks was +3.6 letters (P = 0.014) and LLVA was +5.6 letters (P = 0.004). Compared with baseline, mean NLRA improved by -0.11 logarithm of the minimum angle of resolution (logMAR) units (P = 0.001), and LLRA by -0.28 logMAR units (P < 0.0001). Significant improvements were found in 6 of 7 subscales of the LLQ (P <0.0015). No significant changes were observed for RPE-DC volume, FAF, mesopic microperimetry, or dark adaptation. Conclusions: Elamipretide appeared to be generally safe and well tolerated in treating intermediate AMD and HRD. Exploratory analyses demonstrate a positive effect on visual function, particularly under low-luminance conditions. Further study of elamipretide for treatment of intermediate AMD with HRD is warranted.

Multi-dimensional characterization of prediabetes in the Project Baseline Health Study.

BACKGROUND: We examined multi-dimensional clinical and laboratory data in participants with normoglycemia, prediabetes, and diabetes to identify characteristics of prediabetes and predictors of progression from prediabetes to diabetes or reversion to no diabetes. METHODS: The Project Baseline Health Study (PBHS) is a multi-site prospective cohort study of 2502 adults that conducted deep clinical phenotyping through imaging, laboratory tests, clinical assessments, medical history, personal devices, and surveys. Participants were classified by diabetes status (diabetes [DM], prediabetes [preDM], or no diabetes [noDM]) at each visit based on glucose, HbA1c, medications, and self-report. Principal component analysis (PCA) was performed to create factors that were compared across groups cross-sectionally using linear models. Logistic regression was used to identify factors associated with progression from preDM to DM and for reversion from preDM to noDM. RESULTS: At enrollment, 1605 participants had noDM; 544 had preDM; and 352 had DM. Over 4 years of follow-up, 52 participants with preDM developed DM and 153 participants reverted to noDM. PCA identified 33 factors composed of clusters of clinical variables; these were tested along with eight individual variables identified a priori as being of interest. Six PCA factors and six a priori variables significantly differed between noDM and both preDM and DM after false discovery rate adjustment for multiple comparisons (q < 0.05). Of these, two factors (one comprising glucose measures and one of anthropometry and physical function) demonstrated monotonic/graded relationships across the groups, as did three a priori variables: ASCVD risk, coronary artery calcium, and triglycerides (q < 10-21 for all). Four factors were significantly different between preDM and noDM, but concordant or similar between DM and preDM: red blood cell indices (q = 8 × 10-10), lung function (q = 2 × 10-6), risks of chronic diseases (q = 7 × 10-4), and cardiac function (q = 0.001), along with a priori variables of diastolic function (q = 1 × 10-10), sleep efficiency (q = 9 × 10-6) and sleep time (q = 6 × 10-5). Two factors were associated with progression from prediabetes to DM: anthropometry and physical function (OR [95% CI]: 0.6 [0.5, 0.9], q = 0.04), and heart failure and c-reactive protein (OR [95% CI]: 1.4 [1.1, 1.7], q = 0.02). The anthropometry and physical function factor was also associated with reversion from prediabetes to noDM: (OR [95% CI]: 1.9 [1.4, 2.7], q = 0.02) along with a factor of white blood cell indices (OR [95% CI]: 0.6 [0.4, 0.8], q = 0.02), and the a priori variables ASCVD risk score (OR [95% CI]: 0.7 [0.6, 0.9] for each 0.1 increase in ASCVD score, q = 0.02) and triglycerides (OR [95% CI]: 0.9 [0.8, 1.0] for each 25 mg/dl increase, q = 0.05). CONCLUSIONS: PBHS participants with preDM demonstrated pathophysiologic changes in cardiac, pulmonary, and hematology measures and declines in physical function and sleep measures that precede DM; some changes predicted an increased risk of progression to DM. A factor with measures of anthropometry and physical function was the most important factor associated with progression to DM and reversion to noDM. Future studies may determine whether these changes elucidate pathways of progression to DM and related complications and whether they can be used to identify individuals at higher risk of progression to DM for targeted preventive interventions. Trial registration ClinicalTrials.gov NCT03154346.

Immunological Aspects of Age-Related Macular Degeneration.

Increasing evidence over the past two decades points to a pivotal role for immune mechanisms in age-related macular degeneration (AMD) pathobiology. In this chapter, we will explore immunological aspects of AMD, with a specific focus on how immune mechanisms modulate clinical phenotypes of disease and severity and how components of the immune system may serve as triggers for disease progression in both dry and neovascular AMD. We will briefly review the biology of the immune system, defining the role of immune mechanisms in chronic degenerative disease and differentiating from immune responses to acute injury or infection. We will explore current understanding of the roles of innate immunity (especially macrophages), antigen-specific immunity (T cells, B cells, and autoimmunity), immune amplifications systems, especially complement activity and the NLRP3 inflammasome, in the pathogenesis of both dry and neovascular AMD, reviewing data from pathology, experimental animal models, and clinical studies of AMD patients. We will also assess how interactions between the immune system and infectious pathogens could potentially modulate AMD pathobiology via alterations in in immune effector mechanisms. We will conclude by reviewing the paradigm of "response to injury," which provides a means to integrate various immunologic mechanisms along with nonimmune mechanisms of tissue injury and repair as a model to understand the pathobiology of AMD.

Incomplete response to Anti-VEGF therapy in neovascular AMD: Exploring disease mechanisms and therapeutic opportunities.

Intravitreal anti-vascular endothelial growth factor (VEGF) drugs have revolutionized the treatment of neovascular age-related macular degeneration (NVAMD). However, many patients suffer from incomplete response to anti-VEGF therapy (IRT), which is defined as (1) persistent (plasma) fluid exudation; (2) unresolved or new hemorrhage; (3) progressive lesion fibrosis; and/or (4) suboptimal vision recovery. The first three of these collectively comprise the problem of persistent disease activity (PDA) in spite of anti-VEGF therapy. Meanwhile, the problem of suboptimal vision recovery (SVR) is defined as a failure to achieve excellent functional visual acuity of 20/40 or better in spite of sufficient anti-VEGF treatment. Thus, incomplete response to anti-VEGF therapy, and specifically PDA and SVR, represent significant clinical unmet needs. In this review, we will explore PDA and SVR in NVAMD, characterizing the clinical manifestations and exploring the pathobiology of each. We will demonstrate that PDA occurs most frequently in NVAMD patients who develop high-flow CNV lesions with arteriolarization, in contrast to patients with capillary CNV who are highly responsive to anti-VEGF therapy. We will review investigations of experimental CNV and demonstrate that both types of CNV can be modeled in mice. We will present and consider a provocative hypothesis: formation of arteriolar CNV occurs via a distinct pathobiology, termed neovascular remodeling (NVR), wherein blood-derived macrophages infiltrate the incipient CNV lesion, recruit bone marrow-derived mesenchymal precursor cells (MPCs) from the circulation, and activate MPCs to become vascular smooth muscle cells (VSMCs) and myofibroblasts, driving the development of high-flow CNV with arteriolarization and perivascular fibrosis. In considering SVR, we will discuss the concept that limited or poor vision in spite of anti-VEGF may not be caused simply by photoreceptor degeneration but instead may be associated with photoreceptor synaptic dysfunction in the neurosensory retina overlying CNV, triggered by infiltrating blood-derived macrophages and mediated by Müller cell activation Finally, for each of PDA and SVR, we will discuss current approaches to disease management and treatment and consider novel avenues for potential future therapies.

Deep learning-based single-shot prediction of differential effects of anti-VEGF treatment in patients with diabetic macular edema.

Anti-vascular endothelial growth factor (VEGF) agents are widely regarded as the first line of therapy for diabetic macular edema (DME) but are not universally effective. An automatic method that can predict whether a patient is likely to respond to anti-VEGF therapy can avoid unnecessary trial and error treatment strategies and promote the selection of more effective first-line therapies. The objective of this study is to automatically predict the efficacy of anti-VEGF treatment of DME in individual patients based on optical coherence tomography (OCT) images. We performed a retrospective study of 127 subjects treated for DME with three consecutive injections of anti-VEGF agents. Patients' retinas were imaged using spectral-domain OCT (SD-OCT) before and after anti-VEGF therapy, and the total retinal thicknesses before and after treatment were extracted from OCT B-scans. A novel deep convolutional neural network was designed and evaluated using pre-treatment OCT scans as input and differential retinal thickness as output, with 5-fold cross-validation. The group of patients responsive to anti-VEGF treatment was defined as those with at least a 10% reduction in retinal thickness following treatment. The predictive performance of the system was evaluated by calculating the precision, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The algorithm achieved an average AUC of 0.866 in discriminating responsive from non-responsive patients, with an average precision, sensitivity, and specificity of 85.5%, 80.1%, and 85.0%, respectively. Classification precision was significantly higher when differentiating between very responsive and very unresponsive patients. The proposed automatic algorithm accurately predicts the response to anti-VEGF treatment in DME patients based on OCT images. This pilot study is a critical step toward using non-invasive imaging and automated analysis to select the most effective therapy for a patient's specific disease condition.

Aldosterone as a mediator of severity in retinal vascular disease: Evidence and potential mechanisms.

Diabetic retinopathy (DR) and retinal vein occlusion (RVO) are the two most common retinal vascular diseases and are major causes of vision loss and blindness worldwide. Recent and ongoing development of medical therapies including anti-vascular endothelial growth factor and corticosteroid drugs for treatment of these diseases have greatly improved the care of afflicted patients. However, severe manifestations of retinal vascular disease result in persistent macular edema, progressive retinal ischemia and incomplete visual recovery. Additionally, choroidal vascular diseases including neovascular age-related macular degeneration (NVAMD) and central serous chorioretinopathy (CSCR) cause vision loss for which current treatments are incompletely effective in some cases and highly burdensome in others. In recent years, aldosterone has gained attention as a contributor to the various deleterious effects of retinal and choroidal vascular diseases via a variety of mechanisms in several retinal cell types. The following is a review of the role of aldosterone in retinal and choroidal vascular diseases as well as our current understanding of the mechanisms by which aldosterone mediates these effects.

Evaluation of a Remote Diagnosis Imaging Model vs Dilated Eye Examination in Referable Macular Degeneration.

Importance: In improving clinical outcomes, developing a sustainable, transformative care delivery model is important for accessible, efficient, low-cost, high-quality community-based imaging and diagnosis of retinal diseases. Objective: To test the feasibility and accuracy of the remote diagnosis imaging model as a clinical screening tool to facilitate the identification of referable macular degeneration. Design, Setting, and Participants: A nonrandomized study of 159 patients was conducted in sites with a relatively high disease prevalence (Duke University Health System endocrinology clinic and 2 Duke University Health System assisted living centers in North Carolina). All patients underwent remote diagnosis imaging, defined as color fundus photography (CFP) and optical coherence tomography (OCT) of nondilated pupils, acquired by nonexpert imagers using a retinal imaging device located at the point of service. The criterion standard examination was defined as a traditional dilated eye examination performed by retinal specialists. Deidentified remote diagnosis images were graded for interpretability and presence of referable macular degeneration, defined as any condition requiring a retinal specialist attention. Data analysis was performed from November 20, 2015, to February 10, 2019. Main Outcomes and Measures: Primary outcome was feasibility of the remote retinal imaging. Secondary outcomes were operational characteristics and diagnostic and referral accuracy. Results: Of the 159 patients included in the study, the mean (SD) age of enrolled participants was 65 (17) years, with a female to male ratio of 1.3 to 1. Most patients were white (111 [69.8%]), 44 were black patients (27.7%), approximately 1% were Asian patients and Hispanic patients, and 2 patients declined to disclose their race/ethnicity. Thirty-five eyes (22.0%) were determined to require referral to the retinal specialist by criterion standard examination. Remote diagnosis image interpretability was better when OCT was used compared with CFP (241 [96.4%] vs 164 [65.6%]). Remote diagnosis had high diagnostic accuracy in identifying referable macular degeneration: OCT and CFP both had 94% sensitivity (95% CI, 84%-98%), and OCT had specificity higher than for CFP (93% [95% CI, 87%-96% ] vs 63% [95% CI, 53%-71%]). Substantial agreement was found between the criterion standard and OCT (κ = 0.83; 95% CI, 0.76-0.91; P < .001) and between the criterion standard and CFP (κ = 0.76; 95% CI, 0.64-0.87; P < .001). The nonvalidated patient satisfaction survey revealed that 122 participants (76.7%; mean score, 4.16; 95% CI, 3.98-4.35) preferred remote imaging over the standard care examination. Conclusions and Relevance: Remote diagnosis imaging and a standard examination by a retinal specialist appeared equivalent in identifying referable macular degeneration in patients with high disease prevalence; these results may assist in delivering timely treatment and seem to warrant future research into additional metrics.

Aldosterone Exposure Causes Increased Retinal Edema and Severe Retinopathy Following Laser-Induced Retinal Vein Occlusion in Mice.

Purpose: To determine the effects of aldosterone exposure on retinal edema and retinopathy in a mouse model of retinal vein occlusion (RVO). Methods: RVO was induced immediately following intravenous injection of Rose bengal (66 mg/kg) using a 532-nm wavelength laser to place three to seven applications at 80 mW and 50-µm spot size directed at the superior retinal vein one disc diameter away from the nerve. Negative control consisted of placing an equal number of laser spots without targeting the vein. Male and female C57BL/6J mice aged 7 to 9 months with confirmed absence of Crb1rd8 were used. Aldosterone pellets releasing a daily dose of 0.83 µg/day were implanted subcutaneously 4 weeks prior to RVO. Retinal imaging by optical coherence tomography (OCT) was performed using a Micron IV rodent imaging system. Retinas were analyzed by immunohistochemistry using standard techniques. Retinal imaging and tissue analysis were performed 2, 4, and 7 days following RVO. Comparisons were made using Student's t-test, ANOVA, and Pearson's χ2. Results: RVO caused retinal edema in the form of cystic spaces and retinal thickening detectable by both OCT and histology. RVO also caused Müller glia (MG) dysfunction manifest as upregulated glial fibrillary acidic protein (GFAP) and altered localization of aquaporin 4 (AQP4) and Kir4.1. Treatment with aldosterone caused a significant increase in retinal edema and more severe retinopathy manifest as retinal whitening and extensive intraretinal hemorrhage. MG dysfunction was more severe and persistent in aldosterone-treated mice. Finally, aldosterone greatly increased the number of infiltrating mononuclear phagocytes following RVO. Conclusions: Systemic aldosterone exposure causes a more severe RVO phenotype manifest as increased severity and duration of retinal edema and more severe retinopathy. The effects of aldosterone may be mediated by MG dysfunction and increased infiltration of mononuclear phagocytes. This suggests that small increases in aldosterone levels may be a risk factor for severe RVO.

A Quantitative Approach to Predict Differential Effects of Anti-VEGF Treatment on Diffuse and Focal Leakage in Patients with Diabetic Macular Edema: A Pilot Study.

PURPOSE: We use semiautomated segmentation of fluorescein angiography (FA) to determine whether anti-vascular endothelial growth factor (VEGF) treatment for diabetic macular edema (DME) differentially affects microaneurysm (MA)-associated leakage, termed focal leakage, versus non-MA-associated leakage, termed diffuse leakage. METHODS: We performed a retrospective study of 29 subjects treated with at least three consecutive injections of anti-VEGF agents for DME (mean 4.6 injections; range, 3-10) who underwent Heidelberg FA before and after anti-VEGF therapy. Inclusion criteria were macula center involving DME and at least 3 consecutive anti-VEGF injections. Exclusion criteria were macular edema due to cause besides DME, anti-VEGF within 3 months of initial FA, concurrent treatment for DME besides anti-VEGF, and macular photocoagulation within 1 year. At each time point, total leakage was semiautomatically segmented using a modified version of our previously published software. Microaneurysms were identified by an expert grader and leakage within a 117 µm radius of each MA was classified as focal leakage. Remaining leakage was classified as diffuse leakage. The absolute and percent changes in total, diffuse, and focal leakage were calculated for each subject. RESULTS: Mean pretreatment total leakage was 8.2 mm2 and decreased by a mean of 40.1% (P < 0.0001; 95% confidence interval [CI], [-28.6, -52.5]) following treatment. Diffuse leakage decreased by a mean of 45.5% (P < 0.0001; 95% CI, [-31.3, -59.6]) while focal leakage decreased by 17.9% (P = 0.02; 95% CI, [-1.0, -34.8]). The difference in treatment response between focal and diffuse leakage was statistically significant (P = 0.01). CONCLUSIONS: Anti-VEGF treatment for DME results in decreased diffuse leakage but had relatively little effect on focal leakage as assessed by FA. This suggests that diffuse leakage may be a marker of VEGF-mediated pathobiology. Patients with predominantly focal leakage may be less responsive to anti-VEGF therapy. TRANSLATIONAL RELEVANCE: Fluorescein angiography can define focal and diffuse subtypes of diabetic macular edema and these may respond differently to anti-VEGF treatment.

Intravitreal Anti-VEGF Injections Reduce Aqueous Outflow Facility in Patients With Neovascular Age-Related Macular Degeneration.

Purpose: We assess the effect of intravitreal anti-VEGF injections on tonographic outflow facility. Methods: Patients with age-related macular degeneration who had received unilateral intravitreal anti-VEGF injections were recruited into two groups, those with ≤10 and those with ≥20 total anti-VEGF injections. Intraocular pressure and tonographic outflow facility of injected and uninjected fellow eyes were measured and compared between groups. Risk factors for development of reduced outflow facility also were assessed. Results: Outflow facility was 12% lower in the injected eyes of patients who received ≥20 anti-VEGF injections, compared to contralateral uninjected eyes (P = 0.02). In contrast, there was no facility reduction for patients with ≤10 anti-VEGF injections (P = 0.4). In patients with ocular hypertension in the uninjected eye (IOP > 21 mm Hg, n = 5), the outflow facility of injected eyes was on average 46% lower (P = 0.01) than in the uninjected fellow eyes. This was significantly greater than the difference observed in patients with IOP ≤ 21 mm Hg in the uninjected eye (P = 2 × 10-4). In patients with ocular hypertension in the injected eye (n = 6) the differences in facility and IOP between contralateral eyes were significantly greater than in patients with IOP ≤ 21 mm Hg in the injected eye (P = 2 × 10-4 and P = 7 × 10-4, respectively). Conclusions: Chronic anti-VEGF injections significantly reduce outflow facility in patients with AMD. The greatest facility reduction is observed in patients with baseline ocular hypertension. Ophthalmologists who administer anti-VEGF injections should be aware of these findings and monitor patients closely for changes in IOP or evidence of glaucoma, especially in those with pre-existing ocular hypertension.

Enhanced visualization of peripheral retinal vasculature with wavefront sensorless adaptive optics optical coherence tomography angiography in diabetic patients.

Optical coherence tomography angiography (OCTA) is a promising technique for non-invasive visualization of vessel networks in the human eye. We debut a system capable of acquiring wide field-of-view (>70°) OCT angiograms without mosaicking. Additionally, we report on enhancing the visualization of peripheral microvasculature using wavefront sensorless adaptive optics (WSAO). We employed a fast WSAO algorithm that enabled wavefront correction in <2 s by iterating the mirror shape at the speed of OCT B-scans rather than volumes. Also, we contrasted ∼7° field-of-view OCTA angiograms acquired in the periphery with and without WSAO correction. On average, WSAO improved the sharpness of microvasculature by 65% in healthy eyes and 38% in diseased eyes. Preliminary observations demonstrated that the location of 7° images could be identified directly from the wide field-of-view angiogram. A pilot study on a normal subject and patients with diabetic retinopathy showed the impact of utilizing WSAO for OCTA when visualizing peripheral vasculature pathologies.

Classical dendritic cells mediate fibrosis directly via the retinoic acid pathway in severe eye allergy.

Fibrosis is a shared end-stage pathway to lung, liver, and heart failure. In the ocular mucosa (conjunctiva), fibrosis leads to blindness in trachoma, pemphigoid, and allergy. The indirect fibrogenic role of DCs via T cell activation and inflammatory cell recruitment is well documented. However, here we demonstrate that DCs can directly induce fibrosis. In the mouse model of allergic eye disease (AED), classical CD11b+ DCs in the ocular mucosa showed increased activity of aldehyde dehydrogenase (ALDH), the enzyme required for retinoic acid synthesis. In vitro, CD11b+ DC-derived ALDH was associated with 9-cis-retinoic acid ligation to retinoid x receptor (RXR), which induced conjunctival fibroblast activation. In vivo, stimulating RXR led to rapid onset of ocular mucosal fibrosis, whereas inhibiting ALDH activity in DCs or selectively depleting DCs markedly reduced fibrosis. Collectively, these data reveal a profibrotic ALDH-dependent pathway by DCs and uncover a role for DC retinoid metabolism.

Semiautomatic Segmentation of Rim Area Focal Hyperautofluorescence Predicts Progression of Geographic Atrophy Due to Dry Age-Related Macular Degeneration.

PURPOSE: To develop image analysis software usable by nonexpert graders to segment geographic atrophy (GA) from dry AMD and to quantify rim area focal hyperautofluorescence (RAFH) surrounding GA on fundus autofluorescence (FAF) images. To compare the GA progression predictions based on RAFH with those of a validated qualitative classification system. METHODS: Retrospective analysis of serial FAF images from 49 eyes of 30 subjects with GA was performed using MATLAB-based software (MathWorks, Natick, MA, USA). Correlation between RAFH and progression of GA was analyzed using Spearman correlation. Comparisons of lesion growth rate between RAFH tertiles used generalized estimating equations and Kruskal-Wallis testing. Interobserver variability in lesion size, growth rate and RAFH were compared between two expert and one nonexpert grader using Bland-Altman statistics. RESULTS: Rim area focal hyperautofluorescence was positively correlated with GA progression rate (ρ = 0.49, P < 0.001). Subjects in the middle or highest RAFH tertile were at greater risk of progression (P = 0.005 and P = 0.001, respectively). Mean difference in RAFH was 0.012 between expert and -0.005 to 0.017 between expert and nonexperts. Mean difference in lesion size (mm2) was 0.11 between expert and -0.29 to 0.41 between expert and nonexperts. Mean difference in lesion growth rate (mm2/mo) was 0.0098 between expert and -0.027 to 0.037 between expert and nonexperts. Risk stratification based on RAFH tertile was 96% identical across all graders. CONCLUSIONS: Our semiautomated image analysis software facilitates stratification of progression risk based on RAFH and enabled a nonexpert grader with minimal training to obtain results comparable to expert graders. Predictions based on RAFH were similar to those of a validated qualitative classification system.

Retinal Artery-Vein Classification via Topology Estimation.

We propose a novel, graph-theoretic framework for distinguishing arteries from veins in a fundus image. We make use of the underlying vessel topology to better classify small and midsized vessels. We extend our previously proposed tree topology estimation framework by incorporating expert, domain-specific features to construct a simple, yet powerful global likelihood model. We efficiently maximize this model by iteratively exploring the space of possible solutions consistent with the projected vessels. We tested our method on four retinal datasets and achieved classification accuracies of 91.0%, 93.5%, 91.7%, and 90.9%, outperforming existing methods. Our results show the effectiveness of our approach, which is capable of analyzing the entire vasculature, including peripheral vessels, in wide field-of-view fundus photographs. This topology-based method is a potentially important tool for diagnosing diseases with retinal vascular manifestation.

Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema.

We present a fully automatic algorithm to identify fluid-filled regions and seven retinal layers on spectral domain optical coherence tomography images of eyes with diabetic macular edema (DME). To achieve this, we developed a kernel regression (KR)-based classification method to estimate fluid and retinal layer positions. We then used these classification estimates as a guide to more accurately segment the retinal layer boundaries using our previously described graph theory and dynamic programming (GTDP) framework. We validated our algorithm on 110 B-scans from ten patients with severe DME pathology, showing an overall mean Dice coefficient of 0.78 when comparing our KR + GTDP algorithm to an expert grader. This is comparable to the inter-observer Dice coefficient of 0.79. The entire data set is available online, including our automatic and manual segmentation results. To the best of our knowledge, this is the first validated, fully-automated, seven-layer and fluid segmentation method which has been applied to real-world images containing severe DME.

Fully automatic segmentation of fluorescein leakage in subjects with diabetic macular edema.

PURPOSE: To create and validate software to automatically segment leakage area in real-world clinical fluorescein angiography (FA) images of subjects with diabetic macular edema (DME). METHODS: Fluorescein angiography images obtained from 24 eyes of 24 subjects with DME were retrospectively analyzed. Both video and still-frame images were obtained using a Heidelberg Spectralis 6-mode HRA/OCT unit. We aligned early and late FA frames in the video by a two-step nonrigid registration method. To remove background artifacts, we subtracted early and late FA frames. Finally, after postprocessing steps, including detection and inpainting of the vessels, a robust active contour method was utilized to obtain leakage area in a 1500-µm-radius circular region centered at the fovea. Images were captured at different fields of view (FOVs) and were often contaminated with outliers, as is the case in real-world clinical imaging. Our algorithm was applied to these images with no manual input. Separately, all images were manually segmented by two retina specialists. The sensitivity, specificity, and accuracy of manual interobserver, manual intraobserver, and automatic methods were calculated. RESULTS: The mean accuracy was 0.86 ± 0.08 for automatic versus manual, 0.83 ± 0.16 for manual interobserver, and 0.90 ± 0.08 for manual intraobserver segmentation methods. CONCLUSIONS: Our fully automated algorithm can reproducibly and accurately quantify the area of leakage of clinical-grade FA video and is congruent with expert manual segmentation. The performance was reliable for different DME subtypes. This approach has the potential to reduce time and labor costs and may yield objective and reproducible quantitative measurements of DME imaging biomarkers.

Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.

We present a novel fully automated algorithm for the detection of retinal diseases via optical coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of oriented gradient descriptors as feature vectors of a support vector machine based classifier. The spectral domain OCT data sets used for cross-validation consisted of volumetric scans acquired from 45 subjects: 15 normal subjects, 15 patients with dry age-related macular degeneration (AMD), and 15 patients with diabetic macular edema (DME). Our classifier correctly identified 100% of cases with AMD, 100% cases with DME, and 86.67% cases of normal subjects. This algorithm is a potentially impactful tool for the remote diagnosis of ophthalmic diseases.