Retina

Acute retinal necrosis is a progressive intraocular inflammatory syndrome characterized by diffuse necrotizing retinitis that can lead to a poor visual outcome, mainly from retinal detachment. The antiviral treatment approach for acute retinal necrosis varies as there are no established guidelines. We summarize the outcomes of acute retinal necrosis with available antiviral treatments. Electronic searches were conducted in PubMed/MEDLINE, EMBASE, Scopus, and Google Scholar for interventional and observational studies. Meta-analysis was performed to evaluate the pooled proportion of the predefined selected outcomes. This study was registered in PROSPERO (CRD42022320987). Thirty-four studies with a total of 963 participants and 1,090 eyes were included in the final analysis. The estimated varicella-zoster virus and herpes simplex virus polymerase chain reaction-positive cases were 63% (95% CI: 55-71%) and 35% (95% CI: 28-42%), respectively. The 3 main antiviral treatment approaches identified were oral antivirals alone, intravenous antivirals alone, and a combination of systemic (oral or intravenous) and intravitreal antivirals. The overall pooled estimated proportions of visual acuity improvement, recurrence, and retinal detachment were 37% (95% CI: 27-47%), 14% (95% CI: 8-21%), and 43% (95% CI: 38-50%), respectively. Patients treated with systemic and intravitreal antivirals showed a trend towards better visual outcomes than those treated with systemic antivirals (oral or intravenous) alone, even though this analysis was not statistically significant (test for subgroup differences P = 0.83).

PURPOSE: To evaluate ocular and retinal features of CRB1-associated early onset severe retinal dystrophy/Leber congenital amaurosis (EOSRD/LCA) for age-related changes. DESIGN: Retrospective cohort study. METHODS: Sixteen pediatric patients with biallelic CRB1 EOSRD/LCA who had been followed for up to 18 years were reviewed. Results of comprehensive ophthalmic examinations-including visual acuity, refractive error, dark-adapted visual threshold, Goldmann perimetry, and macular optical coherence tomography (OCT)-were analyzed for significant age-related changes using mixed-effects models. RESULTS: Visual acuity dark-adapted visual sensitivity, and area of seeing visual field (all subnormal from the earliest ages recorded) declined with increasing age. Hyperopia was stable through childhood and adolescence. In CRB1 EOSRD/LCA, OCT extrafoveal inner and outer laminar thicknesses exceeded those in controls but varied little with age, and foveal metrics (depth, breadth, thickness at rim) differed significantly from those in controls, but variations in foveal metrics were not associated with declines in acuity. CONCLUSIONS: From the youngest ages, retinal and visual function is significantly subnormal and becomes progressively compromized. A goal of future therapies should be intervention at young ages, when there is more function to be rescued.

PURPOSE: We developed an Infant Retinal Intelligent Diagnosis System (IRIDS), an automated system to aid early diagnosis and monitoring of infantile fundus diseases and health conditions to satisfy urgent needs of ophthalmologists. METHODS: We developed IRIDS by combining convolutional neural networks and transformer structures, using a dataset of 7697 retinal images (1089 infants) from four hospitals. It identifies nine fundus diseases and conditions, namely, retinopathy of prematurity (ROP) (mild ROP, moderate ROP, and severe ROP), retinoblastoma (RB), retinitis pigmentosa (RP), Coats disease, coloboma of the choroid, congenital retinal fold (CRF), and normal. IRIDS also includes depth attention modules, ResNet-18 (Res-18), and Multi-Axis Vision Transformer (MaxViT). Performance was compared to that of ophthalmologists using 450 retinal images. The IRIDS employed a five-fold cross-validation approach to generate the classification results. RESULTS: Several baseline models achieved the following metrics: accuracy, precision, recall, F1-score (F1), kappa, and area under the receiver operating characteristic curve (AUC) with best values of 94.62% (95% CI, 94.34%-94.90%), 94.07% (95% CI, 93.32%-94.82%), 90.56% (95% CI, 88.64%-92.48%), 92.34% (95% CI, 91.87%-92.81%), 91.15% (95% CI, 90.37%-91.93%), and 99.08% (95% CI, 99.07%-99.09%), respectively. In comparison, IRIDS showed promising results compared to ophthalmologists, demonstrating an average accuracy, precision, recall, F1, kappa, and AUC of 96.45% (95% CI, 96.37%-96.53%), 95.86% (95% CI, 94.56%-97.16%), 94.37% (95% CI, 93.95%-94.79%), 95.03% (95% CI, 94.45%-95.61%), 94.43% (95% CI, 93.96%-94.90%), and 99.51% (95% CI, 99.51%-99.51%), respectively, in multi-label classification on the test dataset, utilizing the Res-18 and MaxViT models. These results suggest that, particularly in terms of AUC, IRIDS achieved performance that warrants further investigation for the detection of retinal abnormalities. CONCLUSIONS: IRIDS identifies nine infantile fundus diseases and conditions accurately. It may aid non-ophthalmologist personnel in underserved areas in infantile fundus disease screening. Thus, preventing severe complications. The IRIDS serves as an example of artificial intelligence integration into ophthalmology to achieve better outcomes in predictive, preventive, and personalized medicine (PPPM / 3PM) in the treatment of infantile fundus diseases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-024-00350-y.

The fovea is a small region within the central retina that is responsible for our high acuity daylight vision. Chickens also have a high acuity area (HAA), and are one of the few species that enables studies of the mechanisms of HAA development, due to accessible embryonic tissue and methods to readily perturb gene expression. To enable such studies, we characterized the development of the chick HAA using single molecule fluorescent in situ hybridization (smFISH), along with more classical methods. We found that Fgf8 provides a molecular marker for the HAA throughout development and into adult stages, allowing studies of the cellular composition of this area over time. The radial dimension of the ganglion cell layer (GCL) was seen to be the greatest at the HAA throughout development, beginning during the period of neurogenesis, suggesting that genesis, rather than cell death, creates a higher level of retinal ganglion cells (RGCs) in this area. In contrast, the HAA acquired its characteristic high density of cone photoreceptors post-hatching, which is well after the period of neurogenesis. We also confirmed that rod photoreceptors are not present in the HAA. Analyses of cell death in the developing photoreceptor layer, where rods would reside, did not show apoptotic cells, suggesting that lack of genesis, rather than death, created the "rod-free zone" (RFZ). Quantification of each cone photoreceptor subtype showed an ordered mosaic of most cone subtypes. The changes in cellular densities and cell subtypes between the developing and mature HAA provide some answers to the overarching strategy used by the retina to create this area and provide a framework for future studies of the mechanisms underlying its formation.

PARTICIPANTS: This article includes 7293 infants (14 586 eyes) screened for ROP across 5 centers in the United States (Austin Retina Associates, Austin, TX; Bascom Palmer Eye Institute, Miami, FL; Beaumont Eye Institute, Royal Oak, MI; Massachusetts Eye and Ear, Boston, MA; and Stanford Byers Eye Institute, Stanford, CA). PURPOSE: To analyze the incidence and timing of treatment requiring retinopathy of prematurity (ROP) in extremely small premature infants. We hypothesize that the smaller the infant by gestational age and birthweight, the higher their likelihood of requiring treatment for ROP. DESIGN: Premature infants screened for Retinopathy of Prematurity from 2002-2022 were divided into cohorts based on the following criteria based on gestational age (GA) and birth weight (BW). "Micropremature infants" are infants born between 24-26 weeks GA and between 600-799 g BW. "Nanopremature infants" are born ≤ 24 weeks GA and ≤ 600 g BW. METHODS: Retrospective chart review. MAIN OUTCOME MEASURES: The incidence and timing of treatment-requiring ROP. RESULTS: We found that infants defined as nanopremature had a ∼63% chance of requiring treatment at an average postmenstrual age (PMA) of 36.6 weeks, whereas those defined as micropremature had a 30% chance of requiring treatment at an average PMA of 36.3 weeks. This significantly contrasts with the risk of all screened babies for ROP where the risk of requiring treatment was 8.5%. CONCLUSION: Micropremature and nanopremature infants are significantly more likely to require treatment for ROP. With demographic data matched to all 5 major US regions spanning the last decade, these results have the potential to inform neonatologists, pediatricians, and ophthalmologists of an important shift in the landscape of prematurity in the United States. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

In adult mammals, injured retinal ganglion cells (RGCs) fail to spontaneously regrow severed axons, resulting in permanent visual deficits. Robust axon growth, however, is observed after intra-ocular injection of particulate β-glucan isolated from yeast. Blood-borne myeloid cells rapidly respond to β-glucan, releasing numerous pro-regenerative factors. Unfortunately, the pro-regenerative effects are undermined by retinal damage inflicted by an overactive immune system. Here, we demonstrate that protection of the inflamed vasculature promotes immune-mediated RGC regeneration. In the absence of microglia, leakiness of the blood-retina barrier increases, pro-inflammatory neutrophils are elevated, and RGC regeneration is reduced. Functional ablation of the complement receptor 3 (CD11b/integrin-αM), but not the complement components C1q-/- or C3-/-, reduces ocular inflammation, protects the blood-retina barrier, and enhances RGC regeneration. Selective targeting of neutrophils with anti-Ly6G does not increase axogenic neutrophils but protects the blood-retina barrier and enhances RGC regeneration. Together, these findings reveal that protection of the inflamed vasculature promotes neuronal regeneration.

Retinal detachment (RD) occurs when the neurosensory retina, the neurovascular tissue responsible for phototransduction, is separated from the underlying retinal pigment epithelium (RPE). Given the importance of the RPE for optimal retinal function, RD invariably leads to decreased vision. There are three main types of RD: rhegmatogenous, tractional and exudative (also termed serous) RD. In rhegmatogenous RD, one or more retinal breaks enable vitreous fluid to enter the subretinal space and separate the neurosensory retina from the RPE. In tractional RD, preretinal, intraretinal or subretinal membranes contract and exert tangential forces and elevate the retina from the underlying RPE. Finally, in exudative RD, an underlying inflammatory condition, vascular abnormality or the presence of a tumour causes exudative fluid to accumulate in the subretinal space, exceeding the osmotic pump function of the RPE. The surgical management of RD usually involves pars plana vitrectomy, scleral buckling or pneumatic retinopexy. The approach taken often depends on patient characteristics as well as on practitioner experience and clinical judgement. Advances in surgical technology and continued innovation have improved outcomes for many patients. However, even if retinal re-attachment is achieved, some patients still experience decreased vision or other visual symptoms, such as metamorphopsia, that diminish their quality of life. Continued research in the areas of neuroprotection and retinal biology as well as continued surgical innovation are necessary to enhance therapeutic options and outcomes for these patients.

IMPORTANCE: Large language models (LLMs) are revolutionizing medical diagnosis and treatment, offering unprecedented accuracy and ease surpassing conventional search engines. Their integration into medical assistance programs will become pivotal for ophthalmologists as an adjunct for practicing evidence-based medicine. Therefore, the diagnostic and treatment accuracy of LLM-generated responses compared with fellowship-trained ophthalmologists can help assess their accuracy and validate their potential utility in ophthalmic subspecialties. OBJECTIVE: To compare the diagnostic accuracy and comprehensiveness of responses from an LLM chatbot with those of fellowship-trained glaucoma and retina specialists on ophthalmological questions and real patient case management. DESIGN, SETTING, AND PARTICIPANTS: This comparative cross-sectional study recruited 15 participants aged 31 to 67 years, including 12 attending physicians and 3 senior trainees, from eye clinics affiliated with the Department of Ophthalmology at Icahn School of Medicine at Mount Sinai, New York, New York. Glaucoma and retina questions (10 of each type) were randomly selected from the American Academy of Ophthalmology's Commonly Asked Questions. Deidentified glaucoma and retinal cases (10 of each type) were randomly selected from ophthalmology patients seen at Icahn School of Medicine at Mount Sinai-affiliated clinics. The LLM used was GPT-4 (version dated May 12, 2023). Data were collected from June to August 2023. MAIN OUTCOMES AND MEASURES: Responses were assessed via a Likert scale for medical accuracy and completeness. Statistical analysis involved the Mann-Whitney U test and the Kruskal-Wallis test, followed by pairwise comparison. RESULTS: The combined question-case mean rank for accuracy was 506.2 for the LLM chatbot and 403.4 for glaucoma specialists (n = 831; Mann-Whitney U = 27976.5; P < .001), and the mean rank for completeness was 528.3 and 398.7, respectively (n = 828; Mann-Whitney U = 25218.5; P < .001). The mean rank for accuracy was 235.3 for the LLM chatbot and 216.1 for retina specialists (n = 440; Mann-Whitney U = 15518.0; P = .17), and the mean rank for completeness was 258.3 and 208.7, respectively (n = 439; Mann-Whitney U = 13123.5; P = .005). The Dunn test revealed a significant difference between all pairwise comparisons, except specialist vs trainee in rating chatbot completeness. The overall pairwise comparisons showed that both trainees and specialists rated the chatbot's accuracy and completeness more favorably than those of their specialist counterparts, with specialists noting a significant difference in the chatbot's accuracy (z = 3.23; P = .007) and completeness (z = 5.86; P < .001). CONCLUSIONS AND RELEVANCE: This study accentuates the comparative proficiency of LLM chatbots in diagnostic accuracy and completeness compared with fellowship-trained ophthalmologists in various clinical scenarios. The LLM chatbot outperformed glaucoma specialists and matched retina specialists in diagnostic and treatment accuracy, substantiating its role as a promising diagnostic adjunct in ophthalmology.

This case-control study compared autoimmune retinopathy (AIR) outcomes in patients treated with intravenous immunoglobulin (IVIg) vs. those with no therapy. IVIg was associated with preservation of visual acuity and electroretinography parameters at longer term follow-up.

IMPORTANCE: Machine learning (ML) algorithms have the potential to identify eyes with early diabetic retinopathy (DR) at increased risk for disease progression. OBJECTIVE: To create and validate automated ML models (autoML) for DR progression from ultra-widefield (UWF) retinal images. DESIGN, SETTING AND PARTICIPANTS: Deidentified UWF images with mild or moderate nonproliferative DR (NPDR) with 3 years of longitudinal follow-up retinal imaging or evidence of progression within 3 years were used to develop automated ML models for predicting DR progression in UWF images. All images were collected from a tertiary diabetes-specific medical center retinal image dataset. Data were collected from July to September 2022. EXPOSURE: Automated ML models were generated from baseline on-axis 200° UWF retinal images. Baseline retinal images were labeled for progression based on centralized reading center evaluation of baseline and follow-up images according to the clinical Early Treatment Diabetic Retinopathy Study severity scale. Images for model development were split 8-1-1 for training, optimization, and testing to detect 1 or more steps of DR progression. Validation was performed using a 328-image set from the same patient population not used in model development. MAIN OUTCOMES AND MEASURES: Area under the precision-recall curve (AUPRC), sensitivity, specificity, and accuracy. RESULTS: A total of 1179 deidentified UWF images with mild (380 [32.2%]) or moderate (799 [67.8%]) NPDR were included. DR progression was present in half of the training set (590 of 1179 [50.0%]). The model's AUPRC was 0.717 for baseline mild NPDR and 0.863 for moderate NPDR. On the validation set for eyes with mild NPDR, sensitivity was 0.72 (95% CI, 0.57-0.83), specificity was 0.63 (95% CI, 0.57-0.69), prevalence was 0.15 (95% CI, 0.12-0.20), and accuracy was 64.3%; for eyes with moderate NPDR, sensitivity was 0.80 (95% CI, 0.70-0.87), specificity was 0.72 (95% CI, 0.66-0.76), prevalence was 0.22 (95% CI, 0.19-0.27), and accuracy was 73.8%. In the validation set, 6 of 9 eyes (75%) with mild NPDR and 35 of 41 eyes (85%) with moderate NPDR progressed 2 steps or more were identified. All 4 eyes with mild NPDR that progressed within 6 months and 1 year were identified, and 8 of 9 (89%) and 17 of 20 (85%) with moderate NPDR that progressed within 6 months and 1 year, respectively, were identified. CONCLUSIONS AND RELEVANCE: This study demonstrates the accuracy and feasibility of automated ML models for identifying DR progression developed using UWF images, especially for prediction of 2-step or greater DR progression within 1 year. Potentially, the use of ML algorithms may refine the risk of disease progression and identify those at highest short-term risk, thus reducing costs and improving vision-related outcomes.

PURPOSE: To investigate the impact of anti-VEGF therapy on vascular metrics in eyes with macular edema secondary to central retinal vein occlusion (CRVO) using wider field swept-source OCT angiography (WF SS-OCTA). METHODS: We included 23 eyes with macular edema associated with non-ischemic CRVO from 22 patients treated with anti-VEGF therapy (median number of injections: 5 [2-9]). Changes in vessel density (VD), vessel skeletonized density (VSD), and foveal avascular zone (FAZ) parameters were measured using WF SS-OCTA. Visual acuity (VA) and central subfield thickness (CST) were also measured. RESULTS: Median CST decreased significantly from 369 µm (305-531) to 267 µm (243-300, p < 0.001). VD and VSD parameters in 12 × 12 mm images showed significant reductions. For instance, VSD in the whole retina decreased from a median of 13.37 (11.22-13.74) to 11.29 (9.36-12.97, p = 0.013). Additionally, a significant increase in FAZ circularity was found, suggesting improved microvascular integrity. Significant inverse correlations were found between the number of anti-VEGF injections and all VSD and VD parameters on the 12 × 12 mm images (p < 0.05). Notably, the reductions in VSD and VD on 12 × 12 mm angiograms in the deep capillary plexus (DCP) after each injection significantly correlated with increased logMAR VA (worse VA). CONCLUSION: Anti-VEGF therapy in CRVO patients not only mitigates macular edema but also alters the overall microvascular morphology and functionality as revealed by WF SS-OCTA.