Racial Differences in Diagnostic Accuracy of Retinal Nerve Fiber Layer Thickness in Primary Open-Angle Glaucoma.

Purpose: To evaluate the diagnostic accuracy of retinal nerve fiber layer thickness (RNFLT) by spectral-domain optical coherence tomography (OCT) in primary open-angle glaucoma (POAG) in eyes of African (AD) and European descent (ED). Design: Comparative diagnostic accuracy analysis by race. Participants: 379 healthy eyes (125 AD and 254 ED) and 442 glaucomatous eyes (226 AD and 216 ED) from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. Methods: Spectralis (Heidelberg Engineering GmbH) and Cirrus (Carl Zeiss Meditec) OCT scans were taken within one year from each other. Main Outcome Measures: Diagnostic accuracy of RNFLT measurements. Results: Diagnostic accuracy for Spectralis-RNFLT was significantly lower in eyes of AD compared to those of ED (area under the receiver operating curve [AUROC]: 0.85 and 0.91, respectively, P=0.04). Results for Cirrus-RNFLT were similar but did not reach statistical significance (AUROC: 0.86 and 0.90 in AD and ED, respectively, P =0.33). Adjustments for age, central corneal thickness, axial length, disc area, visual field mean deviation, and intraocular pressure yielded similar results. Conclusions: OCT-RNFLT has lower diagnostic accuracy in eyes of AD compared to those of ED. This finding was generally robust across two OCT instruments and remained after adjustment for many potential confounders. Further studies are needed to explore the potential sources of this difference.

Bilateral optic disc collaterals secondary to high-flow dural arteriovenous fistula: a diagnostic dilemma.

A man in his 80s, with a history of diabetes, hypertension and coronary artery disease, presented with bilateral painless progressive vision loss 2 years prior. His examination showed subnormal best corrected visual acuity of 20/50 and 20/80 in the right eye and left eye (LE), respectively, grade II relative afferent pupillary defect in LE, normal anterior segment, intra-ocular pressure (IOP) and defective colour vision in both eyes (BE). Fundus examination revealed optic disc pallor, disc collaterals and grade 2 hypertensive retinopathy in BE. Automated perimetry showed advanced field loss in BE. MRI of the brain and orbits with contrast showed signs of raised intracranial pressure, and magnetic resonance angiogram of the brain showed multiple arterio-venous channels along with the right transverse and sigmoid sinuses. The patient was referred to a neuroradiologist for further evaluation, and cerebral angiogram confirmed multifocal high-flow dural arterio-venous fistulae at right jugular foramen, transverse and sigmoid sinuses. He underwent Onyx liquid embolization.

Evaluation of optical coherence tomography findings in patients with multiple sclerosis and glaucoma.

PURPOSE: Glaucoma and multiple sclerosis (MS) can cause optic disc pathology and, in this way, affect optical coherence tomography (OCT) data. In this context, the objective of this study is to investigate the changes in the mean, quadrant, and sector data measured by OCT in glaucoma and MS patients. METHODS: The sample of this prospective cohort study consisted of 42 MS patients (84 eyes), 34 Primary open-angle glaucomas patients (67 eyes), and 24 healthy control subjects (48 eyes). The MS group was divided into two groups according to the presence of a history of optic neuritis. Accordingly, those with a history of optic neuritis were included in the MS ON group, and those without a history of optic neuritis were included in the MS NON group. The differences between these groups in the mean, quadrant, and sector data related to the retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) were evaluated. RESULTS: Superior nasal (SN), superior temporal (ST), inferior nasal (IN), and superior quadrant (SUP) values were significantly lower in the glaucoma group than in the MS group (p < 0.05). The mean superior GCC (GCC SUP) value was significantly lower in the MS ON group than in the glaucoma group (p < 0.05). On the other hand, SN, ST, inferior temporal (IT), IN, average RNFL (AVE RNFL), semi-average superior RNFL (SUP AVE RNFL), semi-average inferior RNFL (INF AVE RNFL), SUP, and inferior quadrant RNFL (INF) values were significantly lower in the glaucoma group than in the MS NON group (p < 0.05). CONCLUSION: RNFL and GCC parameters get thinner in MS and glaucoma patients. While the inferior and superior RNFL quadrants are more frequently affected in glaucoma patients, the affected quadrants vary according to the presence of a history of optic neuritis in MS patients. It is noteworthy that the GCC superior quadrant was thin in MS ON patients. The findings of this study indicate that OCT data may be valuable in the differential diagnosis of glaucoma and MS.

Fundus Tessellation and Parapapillary Atrophy, as Ocular Characteristics of Spontaneously High Myopia in Macaques: The Non-Human Primates Eye Study.

Purpose: This study aimed to evaluate the ocular characteristics associated with spontaneously high myopia in adult nonhuman primates (NHPs). Methods: A total of 537 eyes of 277 macaques with an average age of 18.53 ± 3.01 years (range = 5-26 years), raised in a controlled environment, were included. We measured ocular parameters, including spherical equivalent (SE), axial length (AXL), and intraocular pressure. The 45-degree fundus images centered on the macula and the disc assessed the fundus tessellation and parapapillary atrophy (PPA). Additionally, optical coherence tomography (OCT) was used to measure the thickness of the retinal nerve fiber layer (RNFL). Results: The mean SE was -1.58 ± 3.71 diopters (D). The mean AXL was 18.76 ± 0.86 mm. The prevalence rate of high myopia was 17.7%. As myopia aggravated, the AXL increased (r = -0.498, P < 0.001). Compared with non-high myopia, highly myopic eyes had a greater AXL (P < 0.001), less RNFL thickness (P = 0.004), a higher incidence of PPA (P < 0.001), and elevated grades of fundus tessellation (P < 0.001). The binary logistic regression was performed, which showed PPA (odds ratio [OR] = 4.924, 95% confidence interval [CI] = 2.375-10.207, P < 0.001) and higher grades of fundus tessellation (OR = 1.865, 95% CI = 1.474-2.361, P < 0.001) were independent risk characteristics for high myopia. Conclusions: In NHPs, a higher grade of fundus tessellation and PPA were significant biomarkers of high myopia. Translational Relevance: The study demonstrates adult NHPs raised in conditioned rooms have a similar prevalence and highly consistent fundus changes with human beings, which strengthens the foundation for utilizing macaques as an animal model in high myopic studies.

Assessing the efficacy of 2D and 3D CNN algorithms in OCT-based glaucoma detection.

Glaucoma is a progressive neurodegenerative disease characterized by the gradual degeneration of retinal ganglion cells, leading to irreversible blindness worldwide. Therefore, timely and accurate diagnosis of glaucoma is crucial, enabling early intervention and facilitating effective disease management to mitigate further vision deterioration. The advent of optical coherence tomography (OCT) has marked a transformative era in ophthalmology, offering detailed visualization of the macula and optic nerve head (ONH) regions. In recent years, both 2D and 3D convolutional neural network (CNN) algorithms have been applied to OCT image analysis. While 2D CNNs rely on post-prediction aggregation of all B-scans within OCT volumes, 3D CNNs allow for direct glaucoma prediction from the OCT data. However, in the absence of extensively pre-trained 3D models, the comparative efficacy of 2D and 3D-CNN algorithms in detecting glaucoma from volumetric OCT images remains unclear. Therefore, this study explores the efficacy of glaucoma detection through volumetric OCT images using select state-of-the-art (SOTA) 2D-CNN models, 3D adaptations of these 2D-CNN models with specific weight transfer techniques, and a custom 5-layer 3D-CNN-Encoder algorithm. The performance across two distinct datasets is evaluated, each focusing on the macula and the ONH, to provide a comprehensive understanding of the models' capabilities in identifying glaucoma. Our findings demonstrate that the 2D-CNN algorithm consistently provided robust results compared to their 3D counterparts tested in this study for glaucoma detection, achieving AUC values of 0.960 and 0.943 for the macular and ONH OCT test images, respectively. Given the scarcity of pre-trained 3D models trained on extensive datasets, this comparative analysis underscores the overall utility of 2D and 3D-CNN algorithms in advancing glaucoma diagnostic systems in ophthalmology and highlights the potential of 2D algorithms for volumetric OCT image-based glaucoma detection.

Biomechanical Correlations Between the Cornea and the Optic Nerve Head.

Purpose: A thin cornea is a potent risk factor for glaucoma. The underlying mechanisms remain unexplained. It has been postulated that central corneal thickness (CCT) may be a surrogate for biomechanical parameters of the posterior eye. In this study, we aimed to explore correlations of biomechanical responses between the cornea and the optic nerve head (ONH) and the peripapillary sclera (PPS) to elevated intraocular pressure (IOP), the primary risk factor of glaucoma. Methods: Inflation tests were performed in nine pairs of human donor globes. One eye of each pair was randomly assigned for cornea or posterior eye inflation. IOP was raised from 5 to 30 millimeters of mercury (mmHg) at 0.5 mmHg steps in the whole globe and the cornea or the ONH/PPS was imaged using a 50 MHz ultrasound probe. Correlation-based ultrasound speckle tracking was used to calculate tissue displacements and strains. Associations of radial, tangential, and shear strains at 30 mmHg between the cornea and the ONH or PPS were evaluated. Results: Corneal shear strain was significantly correlated with ONH shear strain (R = 0.857, P = 0.003) and PPS shear strain (R = 0.724, P = 0.028). CCT was not correlated with any strains in the cornea, ONH, or PPS. Conclusions: Our results suggested that an eye that experiences a larger shear strain in the cornea would likely experience a larger shear strain in its ONH and PPS at IOP elevations. The strong correlation between the cornea's and the ONH's shear response to IOP provides new insights and suggests a plausible explanation of the cornea's connection to glaucoma risk.

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.

Association between eyeball asymmetry and offset of openings in optic nerve head canal assessed by posterior polar eyeball topography.

We investigated three-dimensional (3D) eyeball protrusion and its association with the offset between the lamina cribrosa (LC) and Bruch's membrane opening (BMO). 3D-MRI scans were taken from 93 subjects (186 eyes). An ellipsoid was fitted along the posterior 2/3 contour of each eyeball. Eyeball asymmetry with focal bulging was determined by the existence of an adjacent outward protrusion/reciprocal inward depression pair, and the angular deviation of the outermost protruded point (OPP) was measured from the nasal side of the fovea-BMO axis. The LC/BMO offset was evaluated by measuring the central retinal vascular trunk (CRVT) location from the BMO center: (1) the angular deviation and (2) the offset index as the ratio between the CRVT-BMO center distance and the BMO radius in the same direction. Seventy-nine eyes (42%) were classified as having eyeball asymmetry, which had a more superior LC/BMO offset (P < 0.001) and a larger offset index (P = 0.002). In those eyes, the angular deviation of the OPP showed a significant correlation with that of the LC/BMO offset (r = -0.724, P < 0.001), as did protrusion depth with the offset index (r = 0.291, P = 0.009). The presence of eyeball asymmetry was associated with superior LC/BMO offset (P = 0.004) and larger offset index (P = 0.009). Superior LC/BMO offset was associated with older age (P < 0.001), shorter axial length (P < 0.001) and inferior location of OPP (P < 0.001). The location and extent of focal bulging were closely associated with those of LC/BMO offset. This indicates that focal bulging during expansion might be associated with diverse directionality of LC/BMO offset.

Lamina Cribrosa Insertions Into the Sclera Are Sparser, Narrower, and More Slanted in the Anterior Lamina.

Purpose: The lamina cribrosa (LC) depends on the sclera for support. The support must be provided through the LC insertions. Although a continuous insertion over the whole LC periphery is often assumed, LC insertions are actually discrete locations where LC collagenous beams meet the sclera. We hypothesized that LC insertions vary in number, size, and shape by quadrant and depth. Methods: Coronal cryosections through the full LCs from six healthy monkey eyes were imaged using instant polarized light microscopy. The images were registered into a stack, on which we manually marked LC insertion outlines, nothing their position in-depth and quadrant (inferior, superior, nasal, or temporal). From the marks, we determined the insertion number, width, angle to the canal wall (90 degrees = perpendicular), and insertion ratio (fraction of LC periphery represented by insertions). Using linear mixed effect models, we determined if the insertion characteristics were associated with depth or quadrant. Results: Insertions in the anterior LC were sparser, narrower, and more slanted than those in deeper LC (P values < 0.001). There were more insertions spanning a larger ratio of the canal wall in the middle LC than in the anterior and posterior (P values < 0.001). In the nasal quadrant, the insertion angles were significantly smaller (P < 0.001). Conclusions: LC insertions vary substantially and significantly over the canal. The sparser, narrower, and more slanted insertions of the anterior-most LC may not provide the robust support afforded by insertions of the middle and posterior LC. These variations may contribute to the progressive deepening of the LC and regional susceptibility to glaucoma.

Imaging Assessment of Peripapillary Vessel Diameters in Postmortem Eyes.

PURPOSE: Proof of concept of ex vivo retinal vessel diameter measurements in human postmortem eyes. METHODS: En face near-infrared (IR) images and optical coherence tomography (OCT) of the optic nerve head (ONH) were captured ex vivo with a Heidelberg Engineering Spectralis (Spectralis, version 7.0.4, Image Capture Module, version 1.2.4, Heidelberg Heidelberg, Germany) device, using a custom-made eye chamber holding and positioning the eyes during the image process. Thirty-two formaldehyde-fixated eyes of 16 patients were imaged. In the IR images, two independent graders measured retinal vessel diameters at the intersection of a drawn circle centered on the ONH with diameters of 2.0 mm and 3.4 mm, respectively. The anatomically corresponding measurements between both graders were statistically analyzed using a Wilcoxon signed-rank test. RESULTS: A total of 246 matched measurements of both graders were analyzed across all 32 imaged eyes. Statistically significant differences between the graders were found for arterioles at 2 mm from the ONH. The other measurements did not show statistically significant intergrader differences. The mean values for arteriole diameters were 72.2 µm at 2.0 mm and 61.5 µm at 3.4 mm for grader 1, and 66.4 µm at 2.0 mm and 63.2 µm at 3.4 mm for grader 2. The mean diameter for venules were 75.5 µm at 2.0 mm and 79.3 µm at 3.4 mm for grader 1, and 67.4 µm at 2 mm and 79.1 µm at 3.4 mm for grader 2. CONCLUSION: To the best of our knowledge, this is the first study to present IR image-based retinal vessel diameters in ex vivo postmortem eyes. Retinal IR/OCT imaging is possible, and measurements are reproducible in formaldehyde-fixated human eyes. Fixation artefacts result in lower image quality, and this can impose challenges in correctly detecting, classifying, and measuring retinal vessels.

A method for analyzing AFM force mapping data obtained from soft tissue cryosections.

Atomic force microscopy (AFM) is a valuable tool for assessing mechanical properties of biological samples, but interpretations of measurements on whole tissues can be difficult due to the tissue's highly heterogeneous nature. To overcome such difficulties and obtain more robust estimates of tissue mechanical properties, we describe an AFM force mapping and data analysis pipeline to characterize the mechanical properties of cryosectioned soft tissues. We assessed this approach on mouse optic nerve head and rat trabecular meshwork, cornea, and sclera. Our data show that the use of repeated measurements, outlier exclusion, and log-normal data transformation increases confidence in AFM mechanical measurements, and we propose that this methodology can be broadly applied to measuring soft tissue properties from cryosections.

The Temporal Relation Between Rates of Retinal Nerve Fiber Layer and Minimum Rim Width Changes in Glaucoma.

Purpose: This study aims to determine whether OCT-derived rates of change in minimum rim width (MRW) are associated with and can potentially predict corresponding alterations in retinal nerve fiber layer thickness (RNFLT) in people with glaucoma. Methods: The rates of change between six-monthly visits were taken from 568 eyes of 278 participants in the P3 Study. Structural equation models (SEM) assessed whether one parameter was predicted by the concurrent or previous rate of the other parameter, after adjusting for its own rate in the previous time interval. Root mean square error of approximation (RMSEA, with 90% confidence intervals [CI]), Tucker Lewis index (TLI) and the comparative fit index (CFI) assessed goodness of fit. Results: Models without a time lag provided a better fit for the data (RMSEA = 0.101 [CI, 0.089, 0.113]), compared to a model featuring a time lag in RNFLT (RMSEA = 0.114 [CI, 0.102, 0.126]) or MRW (RMSEA = 0.114 [CI, 0.102, 0.127]). The SEMs indicated that rates for both MRW and RNFLT were predicted by their own rate in the previous time interval and by the other measure's change in the concurrent time interval (P > 0.001 for all). No evidence of a clinically significant time lag for either parameter was determined. Conclusions: MRW and RNFLT exhibit concurrent changes over time in patients with glaucoma, with no clinically significant time lag determined. Translational Relevance: RNFLT may be more useful than MRW in early glaucoma assessment because of its previously reported lower variability and reduced sensitivity to intraocular pressure changes.

Self-supervised pre-training for joint optic disc and cup segmentation via attention-aware network.

Image segmentation is a fundamental task in deep learning, which is able to analyse the essence of the images for further development. However, for the supervised learning segmentation method, collecting pixel-level labels is very time-consuming and labour-intensive. In the medical image processing area for optic disc and cup segmentation, we consider there are two challenging problems that remain unsolved. One is how to design an efficient network to capture the global field of the medical image and execute fast in real applications. The other is how to train the deep segmentation network using a few training data due to some medical privacy issues. In this paper, to conquer such issues, we first design a novel attention-aware segmentation model equipped with the multi-scale attention module in the pyramid structure-like encoder-decoder network, which can efficiently learn the global semantics and the long-range dependencies of the input images. Furthermore, we also inject the prior knowledge that the optic cup lies inside the optic disc by a novel loss function. Then, we propose a self-supervised contrastive learning method for optic disc and cup segmentation. The unsupervised feature representation is learned by matching an encoded query to a dictionary of encoded keys using a contrastive technique. Finetuning the pre-trained model using the proposed loss function can help achieve good performance for the task. To validate the effectiveness of the proposed method, extensive systemic evaluations on different public challenging optic disc and cup benchmarks, including DRISHTI-GS and REFUGE datasets demonstrate the superiority of the proposed method, which can achieve new state-of-the-art performance approaching 0.9801 and 0.9087 F1 score respectively while gaining 0.9657 D C disc and 0.8976 D C cup . The code will be made publicly available.

Morphological differences of the neuroretinal rim between temporally tilted and non-tilted optic discs in healthy eyes.

This study aimed to compare morphological differences of the neuroretinal rim between the temporally tilted and non-tilted optic discs in healthy eyes. We prospectively enrolled participants aged 20-40 years with temporally tilted or non-tilted optic discs. The optic nerve head parameters were analyzed using spectral domain-optical coherence tomography. The angle between the Bruch's membrane opening (BMO) plane and BMO-minimum rim width (BMO-MRW) was termed "BMO-MRW angle". Peripapillary retinal nerve fiber layer thickness (pRNFLT) and BMO-based parameters were compared between the temporally tilted and non-tilted disc groups. As a result, 55 temporally tilted disc eyes and 38 non-tilted disc eyes were analyzed. Global pRNFLT, global BMO-MRW, and total BMO-minimum rim area (BMO-MRA) were similar between the two groups (p = 0.138, 0.161, and p = 0.410, respectively). In the sectoral analysis, temporally tilted disc group exhibited thicker BMO-MRW in the temporal sector (p = 0.032) and thinner in the nasal superior and nasal sectors (p = 0.025 and p = 0.002, respectively). Temporally tilted disc group showed larger BMO-MRA in the temporal, temporal superior, and temporal inferior sectors (p < 0.001, p < 0.001, and p < 0.016, respectively), alongside a higher BMO-MRW angle in the temporal sector and lower in the nasal superior and nasal sectors. In conclusion, the neuroretinal rim, represented by BMO-MRW and BMO-MRA, showed morphological differences between temporally tilted and non-tilted optic discs in healthy eyes. BMO-MRW and BMO-MRA showed temporalization in the same manner as pRNFLT in the temporally tilted disc eyes. The BMO-MRW angle showed that in temporally tilted disc eyes, optic nerve fibers met the BMO plane steeply in the nasal sector and gently in the temporal sector than in non-tilted disc eyes, suggesting potential stress region of optic nerve fibers in temporally tilted disc eyes.

Development of a deep learning model to distinguish the cause of optic disc atrophy using retinal fundus photography.

The differential diagnosis for optic atrophy can be challenging and requires expensive, time-consuming ancillary testing to determine the cause. While Leber's hereditary optic neuropathy (LHON) and optic neuritis (ON) are both clinically significant causes for optic atrophy, both relatively rare in the general population, contributing to limitations in obtaining large imaging datasets. This study therefore aims to develop a deep learning (DL) model based on small datasets that could distinguish the cause of optic disc atrophy using only fundus photography. We retrospectively reviewed fundus photographs of 120 normal eyes, 30 eyes (15 patients) with genetically-confirmed LHON, and 30 eyes (26 patients) with ON. Images were split into a training dataset and a test dataset and used for model training with ResNet-18. To visualize the critical regions in retinal photographs that are highly associated with disease prediction, Gradient-Weighted Class Activation Map (Grad-CAM) was used to generate image-level attention heat maps and to enhance the interpretability of the DL system. In the 3-class classification of normal, LHON, and ON, the area under the receiver operating characteristic curve (AUROC) was 1.0 for normal, 0.988 for LHON, and 0.990 for ON, clearly differentiating each class from the others with an overall total accuracy of 0.93. Specifically, when distinguishing between normal and disease cases, the precision, recall, and F1 scores were perfect at 1.0. Furthermore, in the differentiation of LHON from other conditions, ON from others, and between LHON and ON, we consistently observed precision, recall, and F1 scores of 0.8. The model performance was maintained until only 10% of the pixel values of the image, identified as important by Grad-CAM, were preserved and the rest were masked, followed by retraining and evaluation.

Myelin Oligodendrocyte Glycoprotein Antibody Disease Optic Neuritis: A Structure-Function Paradox?

BACKGROUND: Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) is a demyelinating disorder that most commonly presents with optic neuritis (ON) and affects children more often than adults. We report 8 pediatric patients with MOG-associated ON and characterize focal optical coherence tomography (OCT) abnormalities over time that help distinguish this condition from the trajectories of other demyelinating disorders. These OCT findings are examined in the context of longitudinal visual function testing. METHODS: This is a retrospective case series of 8 pediatric patients with MOG-associated ON who were referred for neuro-ophthalmic evaluation. Longitudinal data for demographics, clinical history, physical examination, and OCT obtained in the course of clinical evaluations were collected through retrospective medical record review. RESULTS: Patients demonstrated acute peripapillary retinal nerve fiber layer (RNFL) thickening in one or both eyes, consistent with optic disc swelling. This was followed by steady patterns of average RNFL thinning, with 9 of 16 eyes reaching significantly low RNFL thickness using OCT platform reference databases ( P < 0.01), accompanied by paradoxical recovery of high-contrast visual acuity (HCVA) in every patient. There was no correlation between HCVA and any OCT measures, although contrast sensitivity (CS) was associated with global thickness, PMB thickness, and nasal/temporal (N/T) ratio, and color vision was associated with PMB thickness. There was a lower global and papillomacular bundle (PMB) thickness ( P < 0.01) in clinically affected eyes compared with unaffected eyes. There was also a significantly higher N:T ratio in clinically affected eyes compared with unaffected eyes in the acute MOG-ON setting ( P = 0.03), but not in the long-term setting. CONCLUSIONS: MOG shows a pattern of prominent retinal atrophy, as demonstrated by global RNFL thinning, with remarkable preservation of HCVA but remaining deficits in CS and color vision. These tests may be better clinical markers of vision changes secondary to MOG-ON. Of the OCT parameters measured, PMB thickness demonstrated the most consistent correlation between structural and functional measures. Thus, it may be a more sensitive marker of clinically significant retinal atrophy in MOG-ON. The N:T ratio in acute clinically affected MOG-ON eyes in our study was higher than the N:T ratio of neuromyelitis optica (NMO)-ON eyes and similar to the N:T ratio in multiple sclerosis (MS)-ON eyes as presented in the prior literature. Therefore, MOG may share a more similar pathophysiology to MS compared with NMO.

A new segmentation algorithm for peripapillary atrophy and optic disk from ultra-widefield Photographs1.

BACKGROUND AND OBJECTIVE: The prevalence of myopia and high myopia is increasing globally, underscoring the growing importance of diagnosing high myopia-related pathologies. While existing image segmentation models, such as U-Net, UNet++, ResU-Net, and TransUNet, have achieved significant success in medical image segmentation, they still face challenges when dealing with ultra-widefield (UWF) fundus images. This study introduces a novel automatic segmentation algorithm for the optic disc and peripapillary atrophy (PPA) based on UWF fundus images, aimed at assisting ophthalmologists in more accurately diagnosing high myopia-related diseases. METHODS: In this study, we developed a segmentation model leveraging a Transformer-based network structure, complemented by atrous convolution and selective boundary aggregation modules, to elevate the accuracy of segmenting the optic disc and PPA in UWF photography. The atrous convolution module adeptly manages multi-scale features, catering to the variances in target sizes and expanding the deep network's receptive field. Concurrently, the incorporation of the selective boundary aggregation module in the skip connections of the model significantly improves the differentiation of boundary information between segmentation targets. Moreover, the comparison of our proposed algorithm with classical segmentation models like U-Net, UNet++, ResU-Net, and TransUNet highlights its considerable advantages in processing UWF photographs. RESULTS: The experimental results show that, compared to the other four models, our algorithm demonstrates substantial improvements in segmenting the optic disc and PPA in UWF photographs. In PPA segmentation, our algorithm improves by 0.8% in Dice, 1.8% in sensitivity, and 1.3% in intersection over union (IOU). In optic disc segmentation, our algorithm improves by 0.3% in Dice, 0.6% in precision, and 0.4% in IOU. CONCLUSION: Our proposed method improves the segmentation accuracy of PPA and optic disks based on UWF photographs, which is valuable for diagnosing high myopia-related diseases in ophthalmology clinics.

Clinical Perspectives on the Use of Computer Vision in Glaucoma Screening.

Glaucoma is one of the leading causes of irreversible blindness in the world. Early diagnosis and treatment increase the chances of preserving vision. However, despite advances in techniques for the functional and structural assessment of the retina, specialists still encounter many challenges, in part due to the different presentations of the standard optic nerve head (ONH) in the population, the lack of explicit references that define the limits of glaucomatous optic neuropathy (GON), specialist experience, and the quality of patients' responses to some ancillary exams. Computer vision uses deep learning (DL) methodologies, successfully applied to assist in the diagnosis and progression of GON, with the potential to provide objective references for classification, avoiding possible biases in experts' decisions. To this end, studies have used color fundus photographs (CFPs), functional exams such as visual field (VF), and structural exams such as optical coherence tomography (OCT). However, it is still necessary to know the minimum limits of detection of GON characteristics performed through these methodologies. This study analyzes the use of deep learning (DL) methodologies in the various stages of glaucoma screening compared to the clinic to reduce the costs of GON assessment and the work carried out by specialists, to improve the speed of diagnosis, and to homogenize opinions. It concludes that the DL methodologies used in automated glaucoma screening can bring more robust results closer to reality.