Performance of Automated Machine Learning in Predicting Outcomes of Pneumatic Retinopexy.

Purpose: Automated machine learning (AutoML) has emerged as a novel tool for medical professionals lacking coding experience, enabling them to develop predictive models for treatment outcomes. This study evaluated the performance of AutoML tools in developing models predicting the success of pneumatic retinopexy (PR) in treatment of rhegmatogenous retinal detachment (RRD). These models were then compared with custom models created by machine learning (ML) experts. Design: Retrospective multicenter study. Participants: Five hundred and thirty nine consecutive patients with primary RRD that underwent PR by a vitreoretinal fellow at 6 training hospitals between 2002 and 2022. Methods: We used 2 AutoML platforms: MATLAB Classification Learner and Google Cloud AutoML. Additional models were developed by computer scientists. We included patient demographics and baseline characteristics, including lens and macula status, RRD size, number and location of breaks, presence of vitreous hemorrhage and lattice degeneration, and physicians' experience. The dataset was split into a training (n = 483) and test set (n = 56). The training set, with a 2:1 success-to-failure ratio, was used to train the MATLAB models. Because Google Cloud AutoML requires a minimum of 1000 samples, the training set was tripled to create a new set with 1449 datapoints. Additionally, balanced datasets with a 1:1 success-to-failure ratio were created using Python. Main Outcome Measures: Single-procedure anatomic success rate, as predicted by the ML models. F2 scores and area under the receiver operating curve (AUROC) were used as primary metrics to compare models. Results: The best performing AutoML model (F2 score: 0.85; AUROC: 0.90; MATLAB), showed comparable performance to the custom model (0.92, 0.86) when trained on the balanced datasets. However, training the AutoML model with imbalanced data yielded misleadingly high AUROC (0.81) despite low F2-score (0.2) and sensitivity (0.17). Conclusions: We demonstrated the feasibility of using AutoML as an accessible tool for medical professionals to develop models from clinical data. Such models can ultimately aid in the clinical decision-making, contributing to better patient outcomes. However, outcomes can be misleading or unreliable if used naively. Limitations exist, particularly if datasets contain missing variables or are highly imbalanced. Proper model selection and data preprocessing can improve the reliability of AutoML tools. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Mild Hypoxia Accelerates Cerebral Cavernous Malformation Disease Through CX3CR1-CX3CL1 Signaling.

BACKGROUND: Heterogeneity in the severity of cerebral cavernous malformations (CCMs) disease, including brain bleedings and thrombosis that cause neurological disabilities in patients, suggests that environmental, genetic, or biological factors act as disease modifiers. Still, the underlying mechanisms are not entirely understood. Here, we report that mild hypoxia accelerates CCM disease by promoting angiogenesis, neuroinflammation, and vascular thrombosis in the brains of CCM mouse models. METHODS: We used genetic studies, RNA sequencing, spatial transcriptome, micro-computed tomography, fluorescence-activated cell sorting, multiplex immunofluorescence, coculture studies, and imaging techniques to reveal that sustained mild hypoxia via the CX3CR1-CX3CL1 (CX3C motif chemokine receptor 1/chemokine [CX3C motif] ligand 1) signaling pathway influences cell-specific neuroinflammatory interactions, contributing to heterogeneity in CCM severity. RESULTS: Histological and expression profiles of CCM neurovascular lesions (Slco1c1-iCreERT2;Pdcd10fl/fl; Pdcd10BECKO) in male and female mice found that sustained mild hypoxia (12% O2, 7 days) accelerates CCM disease. Our findings indicate that a small reduction in oxygen levels can significantly increase angiogenesis, neuroinflammation, and thrombosis in CCM disease by enhancing the interactions between endothelium, astrocytes, and immune cells. Our study indicates that the interactions between CX3CR1 and CX3CL1 are crucial in the maturation of CCM lesions and propensity to CCM immunothrombosis. In particular, this pathway regulates the recruitment and activation of microglia and other immune cells in CCM lesions, which leads to lesion growth and thrombosis. We found that human CX3CR1 variants are linked to lower lesion burden in familial CCMs, proving it is a genetic modifier in human disease and a potential marker for aggressiveness. Moreover, monoclonal blocking antibody against CX3CL1 or reducing 1 copy of the Cx3cr1 gene significantly reduces hypoxia-induced CCM immunothrombosis. CONCLUSIONS: Our study reveals that interactions between CX3CR1 and CX3CL1 can modify CCM neuropathology when lesions are accelerated by environmental hypoxia. Moreover, a hypoxic environment or hypoxia signaling caused by CCM disease influences the balance between neuroinflammation and neuroprotection mediated by CX3CR1-CX3CL1 signaling. These results establish CX3CR1 as a genetic marker for patient stratification and a potential predictor of CCM aggressiveness.

Development of a Semi-automated Computer-based Tool for the Quantification of Vascular Tortuosity in the Murine Retina.

Purpose: The murine oxygen-induced retinopathy (OIR) model is one of the most widely used animal models of ischemic retinopathy, mimicking hallmark pathophysiology of initial vaso-obliteration (VO) resulting in ischemia that drives neovascularization (NV). In addition to NV and VO, human ischemic retinopathies, including retinopathy of prematurity (ROP), are characterized by increased vascular tortuosity. Vascular tortuosity is an indicator of disease severity, need to treat, and treatment response in ROP. Current literature investigating novel therapeutics in the OIR model often report their effects on NV and VO, and measurements of vascular tortuosity are less commonly performed. No standardized quantification of vascular tortuosity exists to date despite this metric's relevance to human disease. This proof-of-concept study aimed to apply a previously published semi-automated computer-based image analysis approach (iROP-Assist) to develop a new tool to quantify vascular tortuosity in mouse models. Design: Experimental study. Subjects: C57BL/6J mice subjected to the OIR model. Methods: In a pilot study, vasculature was manually segmented on flat-mount images of OIR and normoxic (NOX) mice retinas and segmentations were analyzed with iROP-Assist to quantify vascular tortuosity metrics. In a large cohort of age-matched (postnatal day 12 [P12], P17, P25) NOX and OIR mice retinas, NV, VO, and vascular tortuosity were quantified and compared. In a third experiment, vascular tortuosity in OIR mice retinas was quantified on P17 following intravitreal injection with anti-VEGF (aflibercept) or Immunoglobulin G isotype control on P12. Main Outcome Measures: Vascular tortuosity. Results: Cumulative tortuosity index was the best metric produced by iROP-Assist for discriminating between OIR mice and NOX controls. Increased vascular tortuosity correlated with disease activity in OIR. Treatment of OIR mice with aflibercept rescued vascular tortuosity. Conclusions: Vascular tortuosity is a quantifiable feature of the OIR model that correlates with disease severity and may be quickly and accurately quantified using the iROP-Assist algorithm. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Applications of Deep Learning: Automated Assessment of Vascular Tortuosity in Mouse Models of Oxygen-Induced Retinopathy.

Objective: To develop a generative adversarial network (GAN) to segment major blood vessels from retinal flat-mount images from oxygen-induced retinopathy (OIR) and demonstrate the utility of these GAN-generated vessel segmentations in quantifying vascular tortuosity. Design: Development and validation of GAN. Subjects: Three datasets containing 1084, 50, and 20 flat-mount mice retina images with various stains used and ages at sacrifice acquired from previously published manuscripts. Methods: Four graders manually segmented major blood vessels from flat-mount images of retinas from OIR mice. Pix2Pix, a high-resolution GAN, was trained on 984 pairs of raw flat-mount images and manual vessel segmentations and then tested on 100 and 50 image pairs from a held-out and external test set, respectively. GAN-generated and manual vessel segmentations were then used as an input into a previously published algorithm (iROP-Assist) to generate a vascular cumulative tortuosity index (CTI) for 20 image pairs containing mouse eyes treated with aflibercept versus control. Main Outcome Measures: Mean dice coefficients were used to compare segmentation accuracy between the GAN-generated and manually annotated segmentation maps. For the image pairs treated with aflibercept versus control, mean CTIs were also calculated for both GAN-generated and manual vessel maps. Statistical significance was evaluated using Wilcoxon signed-rank tests (P ≤ 0.05 threshold for significance). Results: The dice coefficient for the GAN-generated versus manual vessel segmentations was 0.75 ± 0.27 and 0.77 ± 0.17 for the held-out test set and external test set, respectively. The mean CTI generated from the GAN-generated and manual vessel segmentations was 1.12 ± 0.07 versus 1.03 ± 0.02 (P = 0.003) and 1.06 ± 0.04 versus 1.01 ± 0.01 (P < 0.001), respectively, for eyes treated with aflibercept versus control, demonstrating that vascular tortuosity was rescued by aflibercept when quantified by GAN-generated and manual vessel segmentations. Conclusions: GANs can be used to accurately generate vessel map segmentations from flat-mount images. These vessel maps may be used to evaluate novel metrics of vascular tortuosity in OIR, such as CTI, and have the potential to accelerate research in treatments for ischemic retinopathies. Financial Disclosures: The author(s) have no proprietary or commercial interest in any materials discussed in this article.

32-year-old diabetic patient with progressive vision loss and crystalline retinopathy.

PURPOSE: To report the case of severe bilateral retinal vascular occlusion in a patient with hyperoxalosis and chronic renal failure. METHODS: Observational case report. Medical and imaging records were retrospectively reviewed. The patient was imaged with ultra-widefield (UWF) fundus photography and fluorescein angiography (UWF-FA), cross sectional and en face spectral-domain optical coherence tomography (SD-OCT), and OCT angiography. RESULTS: A 32-year-old diabetic patient receiving peritoneal dialysis was referred because of severe vision loss. UWF color fundus photography showed diffuse sclerotic retinal vessels and diffuse intraretinal crystals in both eyes. UWF-FA illustrated near-complete retinal vascular occlusion and capillary wipe out in both eyes. SD-OCT demonstrated diffuse inner and middle retina thinning in both eyes and multiple intraretinal hyperreflective foci consistent with crystalline deposits in all retina layers of both eyes. OCT angiography revealed severe capillary and large vessel non-perfusion in the superficial and deep retinal capillary plexus of each eye. The serum oxalate levels were increased at 28 µmol/L (reference range < 2 µmol/L) and genetic testing was positive for a heterozygous mutation of the AGXT (Alanine-Glyoxylate Amino Transferase) gene that causes type 1 autosomal recessive primary hyperoxaluria. CONCLUSION: A diagnosis of hyperoxalosis causing severe retinal vascular occlusion was rendered. Hyperoxalosis was the result of multiple factors including heterozygous AGXT mutation, chronic renal failure insufficiently treated with peritoneal dialysis, and a diet high in oxalate. This case highlights the importance of ruling out retinal oxalosis in patients on peritoneal dialysis in order to initiate prompt hemodialysis and prevent severe retinal vascular occlusion.

Prevalence of peripheral retinal findings in retinal patients using ultra-widefield pseudocolor fundus imaging.

Ultra-widefield retinal imaging is increasingly used in ophthalmology and optometry practices to image patients identifying peripheral abnormalities. However, the clinical relevance of these peripheral retinal abnormalities is unclear. This cross-sectional study aims to firstly validate a new grading system, secondly, assess the prevalence of peripheral retinal abnormalities in retinal patients, and finally understand how peripheral findings may associate with retinal disease. Ultra-widefield pseudocolor fundus images were taken from the eyes of clinic patients. Demographic data and clinical diagnosis for each patient was noted. The grading system was validated using masked retinal specialists. Logistic regression identified associations between retinal disease and peripheral retinal findings. Using the grading system, inter-observer agreement was 76.1% with Cohen's Kappa coefficient 0.542 (p < 0.0001) and the test-retest agreement was 95.1% with Kappa 0.677(p < 0.0001). 971 images were included, with 625 eyes (64.4%) having peripheral abnormalities. Peripheral drusen was the most common abnormality (n = 221, 22.76%) and correlated with age-related macular degeneration (p < 0.001). Novel correlations were also identified between diabetic retinopathy and retinal pigmentation as well as pigmentary degeneration. This study provides a validated system for identifying peripheral abnormalities and adds to literature highlighting peripheral retinal associations with retinal disease which would benefit from further study.

Telemedicine retinopathy of prematurity severity score (TeleROP-SS) versus modified activity score (mROP-ActS) retrospective comparison in SUNDROP cohort.

Identifying and planning treatment for retinopathy of prematurity (ROP) using telemedicine is becoming increasingly ubiquitous, necessitating a grading system to help caretakers of at-risk infants gauge disease severity. The modified ROP Activity Scale (mROP-ActS) factors zone, stage, and plus disease into its scoring system, addressing the need for assessing ROP's totality of binocular burden via indirect ophthalmoscopy. However, there is an unmet need for an alternative score which could facilitate ROP identification and gauge disease improvement or deterioration specifically on photographic telemedicine exams. Here, we propose such a system (Telemedicine ROP Severity Score [TeleROP-SS]), which we have compared against the mROP-ActS. In our statistical analysis of 1568 exams, we saw that TeleROP-SS was able to return a score in all instances based on the gradings available from the retrospective SUNDROP cohort, while mROP-ActS obtained a score of 80.8% in right eyes and 81.1% in left eyes. For treatment-warranted ROP (TW-ROP), TeleROP-SS obtained a score of 100% and 95% in the right and left eyes respectively, while mROP-ActS obtained a score of 70% and 63% respectively. The TeleROP-SS score can identify disease improvement or deterioration on telemedicine exams, distinguish timepoints at which treatments can be given, and it has the adaptability to be modified as needed.

The Sensitivity of Ultra-Widefield Fundus Photography Versus Scleral Depressed Examination for Detection of Retinal Horseshoe Tears.

PURPOSE: Ultra-widefield (UWF) imaging is commonly used in ophthalmology in tandem with scleral depressed examinations (SDE) to evaluate peripheral retinal disease. Because of the increased reliance on this technology in tele-ophthalmology, it is critical to evaluate its efficacy for detecting the peripheral retina when performed in isolation. Therefore, we sought to evaluate UWF imaging sensitivity in detecting retinal horseshoe tears (HSTs). STUDY DESIGN: Retrospective clinical validity and reliability study. METHODS: A single-institutional retrospective analysis was performed on patients at the Shiley Eye Institute, University of California, San Diego. Patients with HSTs seen on SDE who underwent treatment with laser were included in the study. A total of 140 patients with HSTs in the right and/or left eyes met the inclusion criteria. Those with concomitant ruptured globes, retinal detachments, and vitreous hemorrhages were excluded. A total of 123 patients with 135 HSTs were included in the final analysis. The primary outcome was the number of HSTs detected by UWF imaging. A secondary outcome was HST location. Sensitivity was measured with respect to HST location, and statistical significance was calculated by Fisher exact testing. RESULTS: A total of 69 (51.1%) HSTs were visualized on UWF images and 66 (48.9%) were not visualized. The sensitivity of UWF imaging in capturing HSTs was 7 of 41 (17.1%), 8 of 25 (32.0%), 7 of 14 (50.0%), and 47 of 55 (85.5%) for the superior, inferior, nasal, and temporal quadrants, respectively. Sensitivities between HST visibility and location were statistically significant (P < .001). CONCLUSIONS: Nearly half of HSTs were missed by UWF imaging. This study demonstrates that UWF imaging alone is not sufficiently sensitive to exclude the presence of HSTs.

Barriers to Implementation of Teleretinal Diabetic Retinopathy Screening Programs Across the University of California.

Aim: To describe barriers to implementation of diabetic retinopathy (DR) teleretinal screening programs and artificial intelligence (AI) integration at the University of California (UC). Methods: Institutional representatives from UC Los Angeles, San Diego, San Francisco, Irvine, and Davis were surveyed for the year of their program's initiation, active status at the time of survey (December 2021), number of primary care clinics involved, screening image quality, types of eye providers, image interpretation turnaround time, and billing codes used. Representatives were asked to rate perceptions toward barriers to teleretinal DR screening and AI implementation using a 5-point Likert scale. Results: Four UC campuses had active DR teleretinal screening programs at the time of survey and screened between 246 and 2,123 patients at 1-6 clinics per campus. Sites reported variation between poor-quality photos (<5% to 15%) and average image interpretation time (1-5 days). Patient education, resource availability, and infrastructural support were identified as barriers to DR teleretinal screening. Cost and integration into existing technology infrastructures were identified as barriers to AI integration in DR screening. Conclusions: Despite the potential to increase access to care, there remain several barriers to widespread implementation of DR teleretinal screening. More research is needed to develop best practices to overcome these barriers.

PENTOSAN POLYSULFATE SODIUM (ELMIRON) MACULOPATHY: A Genetic Perspective.

PURPOSE: To assess genetic associations for pentosan polysufate sodium maculopathy. METHODS: Genetic testing for inherited retinal dystrophy genes using exome testing and for 14 age-related macular degeneration-associated single nucleotide polymorphisms (SNPs) using panel testing were performed. In addition, full-field electroretinograms (ffERG) were obtained to identify any cone-rod dystrophy. RESULTS: Eleven of 15 patients were women, with a mean age of 69 (range 46-85). Inherited retinal dystrophy exome testing in five patients revealed six pathogenic variants, but failed to confirm inherited retinal dystrophy in any patient genetically. FfERG performed in 12 patients demonstrated only nonspecific a- and b-wave abnormalities in 11 cases and was normal in one case. For age-related macular degeneration single nucleotide polymorphisms, CFH rs3766405 ( P = 0.003) and CETP ( P = 0.027) were found to be statistically significantly associated with pentosan polysulfate maculopathy phenotype compared with the control population. CONCLUSION: Pentosan polysulfate maculopathy is not associated with Mendelian inherited retinal dystrophy genes. However, several age-related macular degeneration risk alleles were identified to be associated with maculopathy compared with their frequency in the normal population. This suggests a role for genes in disease pathology, particularly the alternative complement pathway. These findings would benefit from further investigation to understand the risk of developing maculopathy in taking pentosan polysulfate.

Typical and atypical clinical presentations of X-Linked retinoschisis: A case series and literature review.

X-linked retinoschisis (XLRS) is an X-linked inherited retinal dystrophy characterized by mild-to-severe visual impairment, splitting of the retinal layers, and a reduction in the dark-adapted b-wave amplitude on the electroretinogram. Typical clinical features include macular and peripheral schisis. Relatively common features reported include rhegmatogenous or tractional retinal detachment, vitreous hemorrhage, retinal pigment epithelial changes, vitreous veils, and various retinal vascular abnormalities with or without exudation. Macular hole and macular folds are atypical presentations of XLRS, along with several other rare findings. Here, we report 4 cases of XLRS with atypical clinical presentations and review the literature on XLRS, with a focus on the variable clinical features of this condition.

Automated Detection of Posterior Vitreous Detachment on OCT Using Computer Vision and Deep Learning Algorithms.

Objective: To develop automated algorithms for the detection of posterior vitreous detachment (PVD) using OCT imaging. Design: Evaluation of a diagnostic test or technology. Subjects: Overall, 42 385 consecutive OCT images (865 volumetric OCT scans) obtained with Heidelberg Spectralis from 865 eyes from 464 patients at an academic retina clinic between October 2020 and December 2021 were retrospectively reviewed. Methods: We developed a customized computer vision algorithm based on image filtering and edge detection to detect the posterior vitreous cortex for the determination of PVD status. A second deep learning (DL) image classification model based on convolutional neural networks and ResNet-50 architecture was also trained to identify PVD status from OCT images. The training dataset consisted of 674 OCT volume scans (33 026 OCT images), while the validation testing set consisted of 73 OCT volume scans (3577 OCT images). Overall, 118 OCT volume scans (5782 OCT images) were used as a separate external testing dataset. Main Outcome Measures: Accuracy, sensitivity, specificity, F1-scores, and area under the receiver operator characteristic curves (AUROCs) were measured to assess the performance of the automated algorithms. Results: Both the customized computer vision algorithm and DL model results were largely in agreement with the PVD status labeled by trained graders. The DL approach achieved an accuracy of 90.7% and an F1-score of 0.932 with a sensitivity of 100% and a specificity of 74.5% for PVD detection from an OCT volume scan. The AUROC was 89% at the image level and 96% at the volume level for the DL model. The customized computer vision algorithm attained an accuracy of 89.5% and an F1-score of 0.912 with a sensitivity of 91.9% and a specificity of 86.1% on the same task. Conclusions: Both the computer vision algorithm and the DL model applied on OCT imaging enabled reliable detection of PVD status, demonstrating the potential for OCT-based automated PVD status classification to assist with vitreoretinal surgical planning. Financial Disclosures: Proprietary or commercial disclosure may be found after the references.

Non-neovascular fluid in age-related macular degeneration: observe-and-extend regimen in a case-series study.

OBJECTIVE: To describe the course of non-neovascular fluid in age-related macular degeneration (AMD) after anti-vascular endothelial growth factor (anti-VEGF) therapy or after observation without injections. DESIGN: Retrospective case series. METHODS: AMD eyes with macular drusen and (or) drusenoid pigment epithelial detachment associated with non-neovascular fluid were included. Optical coherence tomography (OCT) angiography was performed in all eyes to exclude the presence of macular neovascularization. Subretinal fluid (SRF) was measured to determine the response after anti-VEGF therapy and after observation without injections. RESULTS: Ten eyes of 9 patients with intermediate AMD and SRF were studied over a median period of 59.5 months (range, 7-128 months). Six patients (6 eyes) had a history of anti-VEGF therapy. Median follow-up off injections was 13.5 months (range, 4-44 months). SRF thickness remained stable and unchanged during the follow-up off injections in all eyes (n = 6) with prior injection and in all eyes (n = 4) that had never been injected. Six eyes developed complete retinal pigment epithelial (RPE) and outer retinal atrophy, and 1 eye developed incomplete RPE and outer retinal atrophy. All eyes exhibited at least 2 OCT biomarkers associated with a high risk for progression to atrophy. CONCLUSION: This study provides preliminary data regarding the progression of non-neovascular fluid in AMD with or without anti-VEGF injections. A possible mechanism for fluid development may be related to RPE pump impairment. Distinguishing neovascular versus non-neovascular fluid using multimodal imaging, including OCT angiography, is essential to avoid unnecessary anti-VEGF therapy. An observe-and-extend regimen may be considered in AMD eyes with non-neovascular fluid.

Advances in retinopathy of prematurity imaging.

Retinopathy of prematurity (ROP) remains the leading cause of childhood blindness worldwide. Recent advances in ROP imaging have significantly improved our understanding of the pathogenesis and pathophysiological course of ROP including the acute phase, regression, reactivation, and late complications, known as adult ROP. Recent progress includes various contact and noncontact wide-field imaging devices for fundus imaging, smartphone-based fundus photography, wide-field fluorescein angiography, handheld optical coherence tomography (OCT) devices for wide-field en face OCT images, and OCT angiography. Images taken by those devices were incorporated in the recently updated guidelines of ROP, the International Classification of Retinopathy of Prematurity, Third Edition (ICROP3). ROP imaging has also allowed the real-world adoption of telemedicine- and artificial intelligence (AI)-based screening. Recent study demonstrated proof of concept that AI has a high diagnostic performance for the detection of ROP in a real-world screening. Here, we summarize the recent advances in ROP imaging and their application for screening, diagnosis, and management of ROP.

The Prevalence of Retinal Disease and Associated CNS Disease in Young Patients with Incontinentia Pigmenti.

PURPOSE: To evaluate the prevalence of retinal disease on fluorescein angiography (FA) in patients with incontinentia pigmenti (IP) and to compare the severity of retinal disease in those with and without known central nervous system (CNS) disease. DESIGN: Multi-institutional consecutive retrospective case series. SUBJECTS: New patients with a diagnosis of IP were seen at the Casey Eye Institute at the Oregon Health and Science University (OHSU), Moran Eye Center, University of Utah, or Bascom Palmer Eye Institute, University of Miami from December 2011 to September 2018. METHODS: Detailed ophthalmoscopic examination and FA were recommended for all new patients and performed on every patient who had parental consent. Ophthalmoscopic findings and FA images were graded for severity by 2 masked graders on a 3-point scale: 0 = no disease, 1 = vascular abnormalities without leakage, 2 = leakage or neovascularization, and 3 = retinal detachment. The presence of known CNS disease was documented. Additional cases were obtained from a pediatric retina listserv for examples of phenotypic variation. MAIN OUTCOME MEASURES: The proportion of eyes noted to have disease on ophthalmoscopy compared with FA and the severity of retinal disease in those with and without known CNS disease. RESULTS: Retinal pathology was detected in 18 of 35 patients (51%) by indirect ophthalmoscopy and 26 of 35 patients (74%) by FA (P = 0.048) in a predominantly pediatric population (median age, 9 months). Ten patients (29%) had known CNS disease at the time of the eye examination. A Wilcoxon rank-sum test indicated that the retinal severity scores for patients with CNS disease (median, 2) were significantly higher than the retinal severity scores for patients without CNS disease (median, 1), z = -2.12, P = 0.034. CONCLUSIONS: Retinal disease is present in the majority of patients with IP, and ophthalmoscopic examination is less sensitive than FA for detection of disease. There may be a correlation between the severity of retinal and CNS disease.

Novel Association between Opioid Use and Increased Risk of Retinal Vein Occlusion Using the National Institutes of Health All of Us Research Program.

Purpose: To assess for risk factors for retinal vein occlusion (RVO) among participants in the National Institutes of Health All of Us database, particularly social risk factors that have not been well studied, including substance use. Design: Retrospective, case-control study. Participants: Data were extracted for 380 adult participants with branch retinal vein occlusion (BRVO), 311 adult participants with central retinal vein occlusion (CRVO), and 1520 controls sampled among 311 640 adult participants in the All of Us database. Methods: Data were extracted regarding demographics, comorbidities, income, housing, insurance, and substance use. Opioid use was defined by relevant diagnosis and prescription codes, with prescription use > 30 days. Controls were sampled at a 4:1 control to case ratio from a pool of individuals aged > 18 years without a diagnosis of RVO and proportionally matched to the demographic distribution of the 2019 U.S. census. Multivariable logistic regression identified medical and social determinants significantly associated with BRVO or CRVO. Statistical significance was defined as P < 0.05. Main Outcome Measure: Development of BRVO or CRVO based on diagnosis codes. Results: Among patients with BRVO, the mean (standard deviation) age was 70.1 (10.5) years. The majority (53.7%) were female. Cases were diverse; 23.7% identified as Black, and 18.4% identified as Hispanic or Latino. Medical risk factors including glaucoma (odds ratio [OR], 3.29; 95% confidence interval [CI], 2.22-4.90; P < 0.001), hypertension (OR, 2.15; 95% CI, 1.49-3.11; P < 0.001), and diabetes mellitus (OR, 1.68; 95% CI, 1.18-2.38; P = 0.004) were re-demonstrated to be associated with BRVO. Black race (OR, 2.64; 95% CI, 1.22-6.05; P = 0.017) was found to be associated with increased risk of BRVO. Past marijuana use (OR, 0.68; 95% CI, 0.50-0.92; P = 0.013) was associated with decreased risk of BRVO; however, opioid use (OR, 1.98; 95% CI, 1.41-2.78; P < 0.001) was associated with a significantly increased risk of BRVO. Similar associations were found for CRVO. Conclusions: Understanding RVO risk factors is important for primary prevention and improvement in visual outcomes. This study capitalizes on the diversity and scale of a novel nationwide database to elucidate a previously uncharacterized association between RVO and opioid use.

Multimodal imaging of retinal findings in syndactyly, telecanthus, anogenital, and renal malformations (STAR) syndrome.

PURPOSE: To report multimodal imaging of novel retinal findings in a case of syndactyly, telecanthus, anogenital, and renal malformations (STAR) syndrome. OBSERVATIONS: A 5-year old patient with STAR syndrome, an ultra-rare developmental disorder composed of syndactyly, telecanthus, anogenital, and renal malformations, was found to have bilateral macular yellow pigmentary changes and peripheral retinal pigment epithelial changes in a radial pattern highlighted by fundus autofluorescence (FAF) imaging. Optical coherence tomography (OCT) of the macula revealed foveal hypoplasia, ellipsoid zone disruption, and outer retinal atrophy suggestive of a retinal degeneration. OCT angiography found no significant abnormalities, and oral fluorescein angiography revealed staining in areas of atrophy in both eyes. CONCLUSIONS AND IMPORTANCE: This case displays the first report of multimodal imaging of retinal manifestations in STAR syndrome, revealing bilateral foveal hypoplasia, outer retinal macular atrophy, and peripheral retinal pigment epithelial changes. Further studies and long-term follow-up are warranted to determine if patients with STAR syndrome have an underlying progressive retinal degeneration.

Artificial Intelligence for Retinopathy of Prematurity: Validation of a Vascular Severity Scale against International Expert Diagnosis.

PURPOSE: To validate a vascular severity score as an appropriate output for artificial intelligence (AI) Software as a Medical Device (SaMD) for retinopathy of prematurity (ROP) through comparison with ordinal disease severity labels for stage and plus disease assigned by the International Classification of Retinopathy of Prematurity, Third Edition (ICROP3), committee. DESIGN: Validation study of an AI-based ROP vascular severity score. PARTICIPANTS: A total of 34 ROP experts from the ICROP3 committee. METHODS: Two separate datasets of 30 fundus photographs each for stage (0-5) and plus disease (plus, preplus, neither) were labeled by members of the ICROP3 committee using an open-source platform. Averaging these results produced a continuous label for plus (1-9) and stage (1-3) for each image. Experts were also asked to compare each image to each other in terms of relative severity for plus disease. Each image was also labeled with a vascular severity score from the Imaging and Informatics in ROP deep learning system, which was compared with each grader's diagnostic labels for correlation, as well as the ophthalmoscopic diagnosis of stage. MAIN OUTCOME MEASURES: Weighted kappa and Pearson correlation coefficients (CCs) were calculated between each pair of grader classification labels for stage and plus disease. The Elo algorithm was also used to convert pairwise comparisons for each expert into an ordered set of images from least to most severe. RESULTS: The mean weighted kappa and CC for all interobserver pairs for plus disease image comparison were 0.67 and 0.88, respectively. The vascular severity score was found to be highly correlated with both the average plus disease classification (CC = 0.90, P < 0.001) and the ophthalmoscopic diagnosis of stage (P < 0.001 by analysis of variance) among all experts. CONCLUSIONS: The ROP vascular severity score correlates well with the International Classification of Retinopathy of Prematurity committee member's labels for plus disease and stage, which had significant intergrader variability. Generation of a consensus for a validated scoring system for ROP SaMD can facilitate global innovation and regulatory authorization of these technologies.