Red and green defocus curves and duochrome test in different age groups / Curvas de desenfoque rojo y verde y prueba de duocromo en diferentes grupos de edad

Purpose: To compare the eye defocus curves (DCs) obtained with stimuli on red, green, and white backgrounds and to investigate the applicability of the duochrome test (DT) in different age groups. Methods: 12 elderly (ELD: 59.3 ± 3.9 years) and 8 young (YG: 22.1 ± 1.1 years) subjects were recruited. An optometric assessment with the DT was carried out to obtain the subjective refraction at distance. DCs at distance on green, white, and red backgrounds were measured and the following parameters were deduced: dioptric difference between red-green, green-white, red-white focal positions (minima of the DCs), best corrected visual acuity (BCVA), and widths of the DCs for red, green, and white. Results: The DC difference between the green-white focal positions (mean ± standard deviation) was -0.12±0.17 diopters (D) (ELD, p = 0.012) and -0.11±0.12 D (YG, p = 0.039), while the red-white difference was not statistically significant. The DC red-green difference was 0.20±0.16 D (ELD, p = 0.002) and 0.18±0.18 D (YG, p = 0.008). The ELD BCVA with green background was significantly worse than BCVA with red (p = 0.007) and white (p = 0.007). The mean value of the DC's width in ELD for green (1.01±0.36 D) was higher than for red (0.77±0.21 D) and for white (0.84±0.35 D), but with no statistical significance. Conclusion: Both age groups showed a slight focusing preference for red when using white light. Moreover, ELD showed a worse BCVA with a green compared to a red background. Despite these results deduced by DC analyses, these aspects do not compromise the possibility of using the DT in clinical practice both in the young and in the elderly. Furthermore, the difference of about 0.20 D between red-green DC in both groups confirms the clinical appropriateness of the widespread use of 0.25 D step as the standard minimum difference in power between correcting lenses.(AU)

Intereye Microvascular Differences in Patients With Same-Stage Diabetic Retinopathy Revealed by OCTA.

Purpose: To evaluate microvascular intereye differences in diabetic patients with same-stage diabetic retinopathy (DR) in both eyes as assessed using optical coherence tomography angiography (OCTA). Methods: In this cross-sectional study, fovea-centered swept-source 6 × 6 mm OCTA scans were acquired using a 200 kHz OCTA device. Vessel density (VD) and fractal dimension were calculated on binarized, vessel-segmented images in the superficial capillary plexus (SCP) and deep capillary plexus (DCP). Foveal avascular zone (FAZ) area (FAZA) and perimeter (FAZP) was measured and FAZ circularity (FAZC) calculated. Absolute difference (δabs) and asymmetry index between eyes was assessed and compared across DR stages. Differences of VD, FD, and FAZ parameters between left and right eye were evaluated using linear mixed models. Results: A total of 336 eyes of 168 diabetic patients without DR and with DR stages ranging from mild nonproliferative to proliferative DR were included for analysis. The intereye comparison revealed significantly lower VD in the SCP (estimate [95% CI] = -0.009 [-0.01; -0.006], P < 0.01), as well as a significantly lower FD in the SCP (-0.007 [-0.009; -0.005], P < 0.01) of the left compared to the right eye. FAZC of the left compared to the right eye was lower in eyes without DR, moderate DR, and PDR (P < 0.05). FAZ δabs and asymmetry index were higher in more advanced disease stages (P < 0.05). Conclusions: OCTA metrics provide important information on the retinal microvasculature in systemic diseases such as DR. Our results reveal a significant intereye difference with lower VD and FD in the SCP as well as higher FAZ impairment of the left compared to the right eye.

Follow-up report of fundus findings of tuberous sclerosis-associated retinal astrocytoma of two siblings.

A late adolescent with tuberous sclerosis (TS) presented with reduced vision in one eye to our tertiary care university hospital 4 years ago. Fundus examination revealed multiple retinal astrocytic hamartomas (RAHs) in both eyes. His younger sibling, who also had TS, was found to have RAH on retinal screening. The swept-source optical coherence tomography (SS-OCT) findings were typical of RAH. We further noted that some of the RAH lesions showed segmental whitening of the outer walls of the arterioles, which traversed through them. The segmental whitening may suggest the enveloping of normal retinal vessels by the tumour. En-face and B-scan SS-OCT angiography of patients with TS showed vascularity within the tumour. The vessels within the tumour appeared to be in continuity with the retinal vasculature. Both siblings were reviewed annually. At the end of 4 years, there was no change in visual acuity, tumour size, number, vascularity and behaviour.

Observation of structural and vascular features of retina and choroid in myopia using ultra-widefield SS-OCTA.

BACKGROUND: To find the relationship between the changes of retinal and choriodal structure/ vascular densities (VD) and the myopia progress. METHODS: 126 eyes of 126 age-matched young participants were divided into three groups: Emmetropia and Low Myopia (EaLM) (33 eyes), Moderate Myopia (MM) (39 eyes), and High Myopia (HM) (54 eyes). Fundus images measuring 12 × 12 mm were captured using ultra-widefield swept-source optical coherence tomography angiography (SS-OCTA). Each image was uniformly divided into nine regions: supra-temporal (ST), temporal (T), infra-temporal (IT), superior (S), central macular area (C), inferior (I), supra-nasal (SN), nasal (N), and infra-nasal (IN). Various structural parameters, including inner retina thickness (IRT), outer retina thickness (ORT), and choroid thickness (CT), were assessed, and the VD of the superficial capillary plexus (SCP), deep capillary plexus (DCP), choriocapillaries (CC), and choroid vessels (ChdV) were quantified. RESULTS: CT in upper fundus exhibited a significant reduction from EaLM to MM. Additionally, ORT (ST, S. SN, C, N, IT, I, IN), CT (ST, S, SN, T, C, N, IT, I, IN) and VDs of SCP (ST, S, C, I, IN), DCP (ST, S, T, C, I) and ChdV (T, N, I, IN) were statistically diminished in EaLM compared to HM. Furthermore, IRT (N), ORT (N, IN), CT (S, SN, T, C, IT, I) and VDs of SCP (I, IN) and DCP (I) exhibited significant decreases as MM progressed towards HM. Intriguingly, there was a notable increase in the VD of CC (ST, S, T, C, N) as myopia progressed from MM to HM. CONCLUSION: Significant changes in retinal and choroid structure and vascular density occur as moderate myopia advances to high myopia. Efforts to curb myopia progression to this stage are essential, as the failure to do so may lead to the development of corresponding retinopathy.

A case of choroidal neovascularization as a first manifestaion of systemic lupus erythematosus.

BACKGROUND: To report a rare occurrence of pigment epitheliopathy associated with choroidal neovasculization as a first manifestation of systemic lupus erythematosus. CASE PRESENTATION: A 54-year-old female, with no prior medical history, sought a second opinion due to sudden drop in vision in her right eye to 20/80. Slit lamp examination was normal. Fundus examination revealed the presence of a subretinal hemorrhage in the macular area. Fundus imaging including optical coherence tomography and fluorescein angiography showed multifocal retinal pigment epitheliopathy associated with choroidal neovascularization (CNV). The patient had received an intravitreal injection of Bevacizumab 2 weeks ago. It was decided to complete the loading dose regimen with two additional Bevacizumab injections, and the first injection was done 2 weeks after her presentation. Two weeks later, the patient reported a rash on her cheeks, painful joints, and purpura. Systemic workup revealed positive ANA, anti-cardiolipin antibodies, and decreased complement levels, with negative anti-histone antibodies. This led to the diagnosis of systemic lupus erythematosus (SLE) based on the "Systemic Lupus International Collaborating Clinics" criteria. The patient was treated with 50 mg of prednisolone which was then tapered. 1 month after the third injection, an showed a total resolution of the sub-retinal fluid with an improvement of vision to 20/20. No recurrence was observed during follow-up. CONCLUSION: Based on the findings from the fundus exam and imaging, systemic symptoms and the blood work-up, we postulate that the pigment epitheliopathy associated with choroidal neovascularization was related to the vaso-occlusive disease at the level of the choroid that can be part of SLE vasculopathy. To our knowledge, this represents the first case in which pigment epitheliopathy and CNV were the primary manifestations of SLE.

Ixabepilone related angiographically silent macular edema.

INTRODUCTION: We present a single-eyed case with a previous diagnosis of breast cancer who had intraretinal cystoid changes associated with the systemic administration of ixabepilone in her only seeing eye. To our best knowledge, this is the first reported case describing this phenomenon related to the ixabepilone administration. CASE DESCRIPTION: A 54-year-old woman with a history of breast cancer was examined due to visual deterioration in her only good left eye. The patient had undergone cataract surgery and lens implantation in her right eye following a childhood accident, but subsequently had developed a refractory glaucoma and lost her right vision. Six cycles of 40 mg/m2 systemic ixabepilone (3-hly intravenous infusion once every 3 weeks) had been administered within the past six months. Her visual decline started two weeks following the last treatment session. She was offered intravitreal anti-vascular endothelial growth factor injection elsewhere. Fluorescein angiogram showed no dye leakage whereas spectral-domain optical coherence tomography demonstrated parafoveal intraretinal cystoid changes. En-face optical coherence tomography revealed petaloid type roundish hyporeflective areas at the level of superficial and deep vascular plexus. Ixabepilone-associated cystoid maculopathy was suspected as she received only ixabepilone for the chemotherapy in the last six months. We thus recommended her not to continue ixabepilone therapy. Ten weeks after the ixabepilone cessation, intraretinal cystoid changes had resolved completely. CONCLUSION: Angiographically silent intraretinal cystoid changes may develop in association with the use of ixabepilone. Referral to an ophthalmologist should be considered for the patients experiencing visual complaints as ixabepilone cessation may lead to visual improvement and avoid unnecessary treatment.

Diagnostic Role of Oral Fluorescein Angiography in Pediatric Ambulatory Clinics.

Oral ingestion of fluorescein can be done in ambulatory pediatric clinics. We show that oral ultra-widefield fluorescein angiography is a non-invasive approach to rapidly diagnose and manage a diverse set of pediatric retinal vascular diseases.

Imágenes multimodales y retromodo en la calcificación esclerocoroidea: reporte de un caso / Multimodal and retro-mode imaging in sclerochoroidal calcification: A case report

Presentamos un reporte de caso en una paciente de 70años sobre las calcificaciones esclerocoroideas, una rara condición que involucra depósitos de pirofosfato de calcio en el polo posterior del ojo. Proporcionamos un relato sobre la presentación clínica y su apariencia en imágenes multimodales, utilizando fotografías de color del fondo de ojo, tomografía de coherencia óptica de fuente de barrido (SS-OCT), ecografía ocular y la novedosa técnica de retromodo (RMI). Al examen la agudeza visual fue de 20/25 en el ojo derecho y de 20/20 en el ojo izquierdo. La fotografía de color del fondo de ojo reveló depósitos amarillentos localizados en la arcada temporal-superior de ambos ojos. SS-OCT demostró masas de origen escleral. Las ecografías oculares confirmaron la calcificación de estas masas. El RMI detectó imágenes hiperreflectivas con una marcada elevación superficial de las lesiones. El laboratorio sistémico no presentó alteraciones, lo que llevó al diagnóstico de calcificaciones esclerocoroideas bilaterales de origen idiopático.(AU)

We present a case report on sclerochoroidal calcification (SCC), a rare condition involving calcium pyrophosphate deposits in the posterior pole of the eye in a 70-year-old patient. We provide an account of the clinical presentation and its appearance in multimodal images, using color fundus photography, swept-source optical coherence tomography (SS-OCT), ocular ultrasound, and the novel retro-mode imaging (RMI) technique. Visual acuity was 20/25 in the right eye (OD) and 20/20 in the left eye (OS). Color fundus photography revealed yellowish deposits located in the upper temporal arcade of both eyes. SS-OCT demonstrated masses of scleral origin. Ocular ultrasounds confirmed the calcification of these masses. RMI detected hyper-reflective images with marked superficial elevation. Systemic laboratory results did not detect any abnormalities, leading to the diagnosis of bilateral idiopathic SCC.(AU)

Deep learning segmentation of non-perfusion area from color fundus images and AI-generated fluorescein angiography.

The non-perfusion area (NPA) of the retina is an important indicator in the visual prognosis of patients with branch retinal vein occlusion (BRVO). However, the current evaluation method of NPA, fluorescein angiography (FA), is invasive and burdensome. In this study, we examined the use of deep learning models for detecting NPA in color fundus images, bypassing the need for FA, and we also investigated the utility of synthetic FA generated from color fundus images. The models were evaluated using the Dice score and Monte Carlo dropout uncertainty. We retrospectively collected 403 sets of color fundus and FA images from 319 BRVO patients. We trained three deep learning models on FA, color fundus images, and synthetic FA. As a result, though the FA model achieved the highest score, the other two models also performed comparably. We found no statistical significance in median Dice scores between the models. However, the color fundus model showed significantly higher uncertainty than the other models (p < 0.05). In conclusion, deep learning models can detect NPAs from color fundus images with reasonable accuracy, though with somewhat less prediction stability. Synthetic FA stabilizes the prediction and reduces misleading uncertainty estimates by enhancing image quality.

Comparison of 21 artificial intelligence algorithms in automated diabetic retinopathy screening using handheld fundus camera.

BACKGROUND: Diabetic retinopathy (DR) is a common complication of diabetes and may lead to irreversible visual loss. Efficient screening and improved treatment of both diabetes and DR have amended visual prognosis for DR. The number of patients with diabetes is increasing and telemedicine, mobile handheld devices and automated solutions may alleviate the burden for healthcare. We compared the performance of 21 artificial intelligence (AI) algorithms for referable DR screening in datasets taken by handheld Optomed Aurora fundus camera in a real-world setting. PATIENTS AND METHODS: Prospective study of 156 patients (312 eyes) attending DR screening and follow-up. Both papilla- and macula-centred 50° fundus images were taken from each eye. DR was graded by experienced ophthalmologists and 21 AI algorithms. RESULTS: Most eyes, 183 out of 312 (58.7%), had no DR and mild NPDR was noted in 21 (6.7%) of the eyes. Moderate NPDR was detected in 66 (21.2%) of the eyes, severe NPDR in 1 (0.3%), and PDR in 41 (13.1%) composing a group of 34.6% of eyes with referable DR. The AI algorithms achieved a mean agreement of 79.4% for referable DR, but the results varied from 49.4% to 92.3%. The mean sensitivity for referable DR was 77.5% (95% CI 69.1-85.8) and specificity 80.6% (95% CI 72.1-89.2). The rate for images ungradable by AI varied from 0% to 28.2% (mean 1.9%). Nineteen out of 21 (90.5%) AI algorithms resulted in grading for DR at least in 98% of the images. CONCLUSIONS: Fundus images captured with Optomed Aurora were suitable for DR screening. The performance of the AI algorithms varied considerably emphasizing the need for external validation of screening algorithms in real-world settings before their clinical application.

What is already known on this topic? Diabetic retinopathy (DR) is a common complication of diabetes. Efficient screening and timely treatment are important to avoid the development of sight-threatening DR. The increasing number of patients with diabetes and DR poses a challenge for healthcare.What this study adds? Telemedicine, mobile handheld devices and artificial intelligence (AI)-based automated algorithms are likely to alleviate the burden by improving efficacy of DR screening programs. Reliable algorithms of high quality exist despite the variability between the solutions.How this study might affect research, practice or policy? AI algorithms improve the efficacy of screening and might be implemented to clinical use after thorough validation in a real-life setting.

Lipid profile alterations in non-infectious uveitis: correlation with quantitative optical coherence tomography angiography parameters.

BACKGROUND/AIMS: Lipid profiles have been changed in numerous chronic conditions. The impact of uveitis on lipid metabolism remains unclear. METHODS: This is a cross-sectional study included 416 patients with non-infectious uveitis (NIU) and 416 healthy subjects. Standard techniques were used to measure total cholesterol (TC), triglycerides (TG), high-density lipoprotein-cholesterol (HDLc), low-density lipoprotein-cholesterol (LDLc) levels. Quantitative optical coherence tomography angiography (OCTA) parameters were obtained from 500 eyes in each group. Correlation analysis examined the relationship between lipid profile and OCTA parameters. RESULTS: Patients with NIU exhibited significantly elevated TC, TG and LDLc levels compared with controls (p=0.003; p<0.001; p<0.001, respectively). Subgroup analysis revealed that HDLc was significantly lower in Behçet's disease (p=0.024) compared with controls. Vascular density (VD) in the superficial capillary plexus (SCP), deep capillary plexus (DCP), choriocapillaris and optic disk were significantly decreased in NIU eyes (p<0.05, respectively) compared with controls. HDLc exhibited a significant negative correlation with VDs in the whole and parafovea SCP (r=-0.489, p=0.008; r=-0.480, p=0.0026, respectively), while LDLc showed a significant positive correlation with VDs in the whole and parafovea DCP in NIU patients (r=0.576, p=0.032; r=0.267, p=0.034, respectively). CONCLUSIONS: The lipid profile is altered in NIU, and there are correlations between HDLc and LDLc levels and VD as measured by OCTA. Lipid profile analysis may offer valuable insights into evaluating vascular and metabolic aspects of NIU.

Multimodal Structural and Functional Characterization of Retinal Vasculopathy with Cerebral Leukoencephalopathy.

OBJECTIVE: To describe and quantify the structural and functional consequences of retinal vasculopathy with cerebral leukoencephalopathy (RVCL) on the neurosensory retina. DESIGN: Cross sectional descriptive study from December 2021 to December 2022. PARTICIPANTS: Retinal vasculopathy with cerebral leukoencephalopathy patients (n = 9, 18 eyes) recruited from the RVCL Research Center at Washington University in St. Louis. METHODS: Retinal vasculopathy with cerebral leukoencephalopathy patients underwent comprehensive ophthalmological evaluation including OCT, OCT angiography (OCTA), ultrawidefield fundus imaging, retinal autofluorescence, dark adaptation, electroretinography (ERG), Goldmann kinetic perimetry, and fluorescein angiography (FA). MAIN OUTCOME MEASURES: Comprehensive characterization from various modalities including best-corrected visual acuity, central subfield thickness (µm) from OCT, foveal avascular zone (mm2) from OCTA, dark adaptation rod intercept (seconds), cone response in ERG, and presence or absence of vascular abnormalities, leakage, neovascularization, and nonperfusion on FA. RESULTS: A total of 18 eyes from 9 individuals were included in this study. The best-corrected visual acuity ranged from 20/15 to 20/70. The mean central subfield thickness from OCT was 275.8 µm (range, 217-488 µm). The mean foveal avascular zone (FAZ) from OCTA was 0.65 (range, 0.18-1.76) mm2. On dark adaptometry, the mean time was 5.02 (range, 2.9-6.5) minutes, and 1 individual had impaired dark adaptation. Electroretinography demonstrated mild cone response impairment in 4 eyes. On FA, there was evidence of macular and peripheral capillary nonperfusion in 16 of 18 eyes and notable areas of vascular leakage and retinal edema in 5 of the 18 eyes. CONCLUSIONS: This study illustrates the phenotypic spectrum of disease and may be clinically valuable for aiding diagnosis, monitoring disease progression, and further elucidating the pathophysiology of RVCL to aid in the development of therapies. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Fundus Autofluorescence in Posterior and Panuveitis-An Under-Estimated Imaging Technique: A Review and Case Series.

Fundus autofluorescence (FAF) is a prompt and non-invasive imaging modality helpful in detecting pathological abnormalities within the retina and the choroid. This narrative review and case series provides an overview on the current application of FAF in posterior and panuveitis. The literature was reviewed for articles on lesion characteristics on FAF of specific posterior and panuveitis entities as well as benefits and limitations of FAF for diagnosing and monitoring disease. FAF characteristics are described for non-infectious and infectious uveitis forms as well as masquerade syndromes. Dependent on the uveitis entity, FAF is of diagnostic value in detecting disease and following the clinical course. Currently available FAF modalities which differ in excitation wavelengths can provide different pathological insights depending on disease entity and activity. Further studies on the comparison of FAF modalities and their individual value for uveitis diagnosis and monitoring are warranted.

iGWAS: Image-based genome-wide association of self-supervised deep phenotyping of retina fundus images.

Existing imaging genetics studies have been mostly limited in scope by using imaging-derived phenotypes defined by human experts. Here, leveraging new breakthroughs in self-supervised deep representation learning, we propose a new approach, image-based genome-wide association study (iGWAS), for identifying genetic factors associated with phenotypes discovered from medical images using contrastive learning. Using retinal fundus photos, our model extracts a 128-dimensional vector representing features of the retina as phenotypes. After training the model on 40,000 images from the EyePACS dataset, we generated phenotypes from 130,329 images of 65,629 British White participants in the UK Biobank. We conducted GWAS on these phenotypes and identified 14 loci with genome-wide significance (p<5×10-8 and intersection of hits from left and right eyes). We also did GWAS on the retina color, the average color of the center region of the retinal fundus photos. The GWAS of retina colors identified 34 loci, 7 are overlapping with GWAS of raw image phenotype. Our results establish the feasibility of this new framework of genomic study based on self-supervised phenotyping of medical images.

Automated machine learning model for fundus image classification by health-care professionals with no coding experience.

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary outcomes from fundus images in ophthalmology, evaluating two distinct online-based platforms (Google Vertex and Amazon Rekognition), and two distinct datasets. Two publicly available datasets, Messidor-2 and BRSET, were utilized for model development. The Messidor-2 consists of fundus photographs from diabetic patients and the BRSET is a multi-label dataset. The CFDL platforms were used to create deep learning models, with no preprocessing of the images, by a single ophthalmologist without coding expertise. The performance metrics employed to evaluate the models were F1 score, area under curve (AUC), precision and recall. The performance metrics for referable diabetic retinopathy and macular edema were above 0.9 for both tasks and CDFL. The Google Vertex models demonstrated superior performance compared to the Amazon models, with the BRSET dataset achieving the highest accuracy (AUC of 0.994). Multi-classification tasks using only BRSET achieved similar overall performance between platforms, achieving AUC of 0.994 for laterality, 0.942 for age grouping, 0.779 for genetic sex identification, 0.857 for optic, and 0.837 for normality with Google Vertex. The study demonstrates the feasibility of using automated machine learning platforms for predicting binary outcomes from fundus images in ophthalmology. It highlights the high accuracy achieved by the models in some tasks and the potential of CFDL as an entry-friendly platform for ophthalmologists to familiarize themselves with machine learning concepts.

CauDR: A causality-inspired domain generalization framework for fundus-based diabetic retinopathy grading.

Diabetic retinopathy (DR) is the most common diabetic complication, which usually leads to retinal damage, vision loss, and even blindness. A computer-aided DR grading system has a significant impact on helping ophthalmologists with rapid screening and diagnosis. Recent advances in fundus photography have precipitated the development of novel retinal imaging cameras and their subsequent implementation in clinical practice. However, most deep learning-based algorithms for DR grading demonstrate limited generalization across domains. This inferior performance stems from variance in imaging protocols and devices inducing domain shifts. We posit that declining model performance between domains arises from learning spurious correlations in the data. Incorporating do-operations from causality analysis into model architectures may mitigate this issue and improve generalizability. Specifically, a novel universal structural causal model (SCM) was proposed to analyze spurious correlations in fundus imaging. Building on this, a causality-inspired diabetic retinopathy grading framework named CauDR was developed to eliminate spurious correlations and achieve more generalizable DR diagnostics. Furthermore, existing datasets were reorganized into 4DR benchmark for DG scenario. Results demonstrate the effectiveness and the state-of-the-art (SOTA) performance of CauDR. Diabetic retinopathy (DR) is the most common diabetic complication, which usually leads to retinal damage, vision loss, and even blindness. A computer-aided DR grading system has a significant impact on helping ophthalmologists with rapid screening and diagnosis. Recent advances in fundus photography have precipitated the development of novel retinal imaging cameras and their subsequent implementation in clinical practice. However, most deep learning-based algorithms for DR grading demonstrate limited generalization across domains. This inferior performance stems from variance in imaging protocols and devices inducing domain shifts. We posit that declining model performance between domains arises from learning spurious correlations in the data. Incorporating do-operations from causality analysis into model architectures may mitigate this issue and improve generalizability. Specifically, a novel universal structural causal model (SCM) was proposed to analyze spurious correlations in fundus imaging. Building on this, a causality-inspired diabetic retinopathy grading framework named CauDR was developed to eliminate spurious correlations and achieve more generalizable DR diagnostics. Furthermore, existing datasets were reorganized into 4DR benchmark for DG scenario. Results demonstrate the effectiveness and the state-of-the-art (SOTA) performance of CauDR.

PallorMetrics: Software for Automatically Quantifying Optic Disc Pallor in Fundus Photographs, and Associations With Peripapillary RNFL Thickness.

Purpose: We sough to develop an automatic method of quantifying optic disc pallor in fundus photographs and determine associations with peripapillary retinal nerve fiber layer (pRNFL) thickness. Methods: We used deep learning to segment the optic disc, fovea, and vessels in fundus photographs, and measured pallor. We assessed the relationship between pallor and pRNFL thickness derived from optical coherence tomography scans in 118 participants. Separately, we used images diagnosed by clinical inspection as pale (n = 45) and assessed how measurements compared with healthy controls (n = 46). We also developed automatic rejection thresholds and tested the software for robustness to camera type, image format, and resolution. Results: We developed software that automatically quantified disc pallor across several zones in fundus photographs. Pallor was associated with pRNFL thickness globally (ß = -9.81; standard error [SE] = 3.16; P < 0.05), in the temporal inferior zone (ß = -29.78; SE = 8.32; P < 0.01), with the nasal/temporal ratio (ß = 0.88; SE = 0.34; P < 0.05), and in the whole disc (ß = -8.22; SE = 2.92; P < 0.05). Furthermore, pallor was significantly higher in the patient group. Last, we demonstrate the analysis to be robust to camera type, image format, and resolution. Conclusions: We developed software that automatically locates and quantifies disc pallor in fundus photographs and found associations between pallor measurements and pRNFL thickness. Translational Relevance: We think our method will be useful for the identification, monitoring, and progression of diseases characterized by disc pallor and optic atrophy, including glaucoma, compression, and potentially in neurodegenerative disorders.

A fundus image dataset for intelligent retinopathy of prematurity system.

Image-based artificial intelligence (AI) systems stand as the major modality for evaluating ophthalmic conditions. However, most of the currently available AI systems are designed for experimental research using single-central datasets. Most of them fell short of application in real-world clinical settings. In this study, we collected a dataset of 1,099 fundus images in both normal and pathologic eyes from 483 premature infants for intelligent retinopathy of prematurity (ROP) system development and validation. Dataset diversity was visualized with a spatial scatter plot. Image classification was conducted by three annotators. To the best of our knowledge, this is one of the largest fundus datasets on ROP, and we believe it is conducive to the real-world application of AI systems.

Atypical acquired toxoplasmosis.

A 33-year-old male presented with unilateral painless vision loss with a history of sub-tenon steroid for the same. The fundus showed an elevated focus of retinochoroiditis with vitritis. On investigating for the cause, polymerase chain reaction test on the anterior chamber tap was found to be positive for Toxoplasma. Such confusing and atypical cases usually produce a clinical dilemma and should be managed in a stepwise manner. Ancillary investigations usually provide a clue to the clinician and should be performed without any hesitation.