Search

Aims: This study aims to develop an advanced model for the classification of Diabetic Macular Edema (DME) using deep learning techniques. Specifically, the objective is to introduce a novel architecture, SSCSAC-Net, that leverages self-supervised learning and category-selective attention mechanisms to improve the precision of DME classification. Methods: The proposed SSCSAC-Net integrates self-supervised learning to effectively utilize unlabeled data for learning robust features related to DME. Additionally, it incorporates a category-specific attention mechanism and a domain-specific layer into the ResNet-152 base architecture. The model is trained using an ensemble of unsupervised and supervised learning techniques. Benchmark datasets are utilized for testing the model's performance, ensuring its robustness and generalizability across different data distributions. Results: Evaluation of the SSCSAC-Net on multiple datasets demonstrates its superior performance compared to existing techniques. The model achieves high accuracy, precision, and recall rates, with an accuracy of 98.7%, precision of 98.6%, and recall of 98.8%. Furthermore, the incorporation of self-supervised learning reduces the dependency on extensive labeled data, making the solution more scalable and cost-effective. Conclusions: The proposed SSCSAC-Net represents a significant advancement in automated DME classification. By effectively using self-supervised learning and attention mechanisms, the model offers improved accuracy in identifying DME-related features within retinal images. Its robustness and generalizability across different datasets highlight its potential for clinical applications, providing a valuable tool for clinicians in diagnosing DME effectively. [ABSTRACT FROM AUTHOR]

Photodynamic venous occlusion is a commonly accepted method for establishing mouse models of retinal vein occlusion (RVO). However, existing model parameters do not distinguish between acute and chronic RVO subtypes. Large variations in laser energy seem to correlate with fluctuating retinopathy severity and high rates of venous recanalization during the acute phase, along with the variable levels of retinal perfusion during the chronic phase. After optimizing the modeling procedure and defining success and exclusion criteria, laser energy groups of 80mW, 100mW, and 120mW were established. Multimodal imaging confirmed that higher energy levels increased the incidence of retinal cystoid edema and intraretinal hemorrhage, exacerbated the severity of exudative retinal detachment, and reduced the venous recanalization rate. For the acute model, 100mW was considered an appropriate parameter for balancing moderate retinopathy and venous recanalization. Continuous imaging follow-up revealed that day 1 after RVO was the optimal observation point for peaking of retinal thickness and intensive occurrence of retinal cystic edema and intraretinal hemorrhage. After excluding the influence of venous recanalization on retinal thickness, acute retinal edema demonstrated a positive response to standard anti-vascular endothelial growth factor therapy, validating the clinical relevance of the acute RVO model for further study in pathogenic mechanisms and therapeutic efficacy. For the chronic model, the 120mW parameter with the lowest venous recanalization rate was applied, accompanied by an increase in both photocoagulation shots and range to ensure sustained vein occlusion. Imaging follow-up clarified non-ischemic retinopathy characterized by tortuosity and dilation of the distal end, branches, and adjacent veins of the occluded vein. These morphological changes are quantifiable and could be combined with electrophysiological functional assessment for treatment effectiveness evaluation. Moreover, the stable state of venous occlusion may facilitate investigations into response and compensation mechanisms under conditions of chronic retinal hypoperfusion. [ABSTRACT FROM AUTHOR]

This study tested if a high-resolution, multi-modal, multi-scale retinal imaging instrument can provide novel information about structural abnormalities in vivo. The study examined 11 patients with very mild to moderate non-proliferative diabetic retinopathy (NPDR) and 10 healthy subjects using fundus photography, optical coherence tomography (OCT), OCT angiography (OCTA), adaptive optics scanning laser ophthalmoscopy (AO-SLO), adaptive optics OCT and OCTA (AO-OCT(A)). Of 21 eyes of 11 patients, 11 had very mild NPDR, 8 had mild NPDR, 2 had moderate NPDR, and 1 had no retinopathy. Using AO-SLO, capillary looping, inflections and dilations were detected in 8 patients with very mild or mild NPDR, and microaneurysms containing hyperreflective granular elements were visible in 9 patients with mild or moderate NPDR. Most of the abnormalities were seen to be perfused in the corresponding OCTA scans while a few capillary loops appeared to be occluded or perfused at a non-detectable flow rate, possibly because of hypoperfusion. In one patient with moderate NPDR, non-perfused capillaries, also called ghost vessels, were identified by alignment of corresponding en face AO-OCT and AO-OCTA images. The combination of multiple non-invasive imaging methods could identify prominent microscopic abnormalities in diabetic retinopathy earlier and more detailed than conventional fundus imaging devices. [ABSTRACT FROM AUTHOR]

The ellipsoid zone (EZ) on macular optical coherence tomography (OCT) scans exhibits high intensity due to a high density of light-scattering mitochondria, making its reflectivity a potential marker for mitochondrial function. Here, we developed a reliable analysis tool for extracting relative EZ reflectivity and explore its potential as a biomarker in various diseases. We analysed OCT scans of patients with optic neuritis (ON), primary progressive optic neuropathy (PPON), chronic progressive external ophthalmoplegia (CPEO), dominant optic atrophy (DOA), and healthy controls. EZ reflectivity (normalised to the retina pigment epithelium (RPE) and outer nuclear layer (ONL)) was evaluated. Reliability was assessed using intraclass correlation coefficients (ICC), and group differences were analysed through multivariable linear regression, adjusting for relevant confounders. In total, 12 controls, 23 ON patients, 7 CPEO patients, 13 DOA patients, and 13 PPON patients were included. EZ/RPE20% and EZ/ONL ratios demonstrated good test–retest reliability with ICCs of 0.76 (p < .001) and 0.63 (p = .013), respectively. Multivariable regression analysis revealed that median EZ/RPE20% and EZ/ONL ratios were lower in CPEO (r = -0.12, p = .036, and r = -0.59, p = .011), DOA (r = -0.16, p = .049, and r = -0.55, p = .082), PPON (r = -0.17, p = .014, and r = -0.57, p = .037), and ON (r = -0.11, p = .013, and r = -0.42, p = .006) compared to controls, respectively. These data show that EZ reflectivity can be reliably determined from OCT scans and appears to be reduced in neuroinflammatory and mitochondrial disorders. Further validation in larger prospective cohorts is warranted, but our findings suggest that EZ reflectivity might serve as a non-invasive in-vivo biomarker for mitochondrial health. [ABSTRACT FROM AUTHOR]

Background: To design a novel anomaly detection and localization approach using artificial intelligence methods using optical coherence tomography (OCT) scans for retinal diseases. Methods: High-resolution OCT scans from the publicly available Kaggle dataset and a local dataset were used by four state-of-the-art self-supervised frameworks. The backbone model of all the frameworks was a pre-trained convolutional neural network (CNN), which enabled the extraction of meaningful features from OCT images. Anomalous images included choroidal neovascularization (CNV), diabetic macular edema (DME), and the presence of drusen. Anomaly detectors were evaluated by commonly accepted performance metrics, including area under the receiver operating characteristic curve, F1 score, and accuracy. Results: A total of 25,315 high-resolution retinal OCT slabs were used for training. Test and validation sets consisted of 968 and 4000 slabs, respectively. The best performing across all anomaly detectors had an area under the receiver operating characteristic of 0.99. All frameworks were shown to achieve high performance and generalize well for the different retinal diseases. Heat maps were generated to visualize the quality of the frameworks' ability to localize anomalous areas of the image. Conclusions: This study shows that with the use of pre-trained feature extractors, the frameworks tested can generalize to the domain of retinal OCT scans and achieve high image-level ROC-AUC scores. The localization results of these frameworks are promising and successfully capture areas that indicate the presence of retinal pathology. Moreover, such frameworks have the potential to uncover new biomarkers that are difficult for the human eye to detect. Frameworks for anomaly detection and localization can potentially be integrated into clinical decision support and automatic screening systems that will aid ophthalmologists in patient diagnosis, follow-up, and treatment design. This work establishes a solid basis for further development of automated anomaly detection frameworks for clinical use. [ABSTRACT FROM AUTHOR]

Segmentation is crucial in diagnosing retinal diseases by accurately identifiying retinal vessels. This paper addresses the complexity of segmenting retinal vessels, highlighting the need for precise analysis of blood vessel structures. Despite the progress made by convolutional neural networsks (CNNs) in image segmentation, their limitations in capturing the global structure of retinal vsessels and maintaining segmentation continuity present challenges. To tackle these issues, our proposed network integrates graph convolutional networks (GCNs) and attention mechansims. This allows the model to consider pixel relationships and learn vessel graphical structures, significantly improving segmentation accuracy. Additionally, the attentional feature fusion module, including pixel‐wise and channel‐wise attention mechansims within the U‐Net architecture, refines the model's focus on relevant features. This paper emphasizes the importance of continuty preservation, ensuring an accurate representation of pixel‐level information and structural details during sefmentation. Therefore, our method performs as an effective solution to overcome challenges in retinal vessel segmentation. The proposed method outperformed the state‐of‐the‐art approaches on DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (Structed Analysis of the Retina) datasets with accuracies of 0.12% and 0.14%, respecttively. Importantly, our proposed approach excelled in delineating slender and diminutive blood vessels, crucial for diagnosing vascular‐related diseases. Implementation is accessible on https://github.com/CVLab‐SHUT/VGA‐Net. [ABSTRACT FROM AUTHOR]

IOLs introduce a significant amount of peripheral defocus which affects peripheral retinal image quality in eyes implanted with IOLs. IOL peripheral defocus varies significantly with IOL power and design. Purpose: To quantify the angular dependence of monofocal intraocular lens (IOL) power. Setting: Ophthalmic Biophysics Laboratory, Kallam Anji Reddy campus, L V Prasad Eye Institute, Hyderabad, India. Design: Laboratory study. Methods: Experiments were performed on IOLs from 2 different manufacturers (APPALENS 207, Appasamy Associates and SN60WF, Alcon Laboratories, Inc.). IOL powers ranged from 17 to 25 diopters (D). The IOLs were mounted in a fluid-filled chamber, and the on-axis and off-axis powers were measured using a laser ray tracing system over the central 3 mm zone with delivery angles ranging from −30 to +30 degrees in 5-degree increments. The position of the best focus was calculated for each IOL at each angle. The angular dependence of IOL power was compared with theoretical predictions. Results: Peripheral defocus increased significantly with increasing incidence angle and power. The peripheral defocus at ±30 degrees increased from 5.8 to 8.5 D when the power increased from 17.5 to 24.5 D for APPALENS 207 and from 4.9 to 7.4 D when the power increased from 17 to 25 D for SN60WF. The mean difference between the measured and theoretical tangential power at ±30 degrees was 0.50 ± 0.16 D for the APPALENS 207 and −0.40 ± 0.10 D for the SN60WF, independent of IOL power. Conclusions: IOLs introduce a significant amount of peripheral defocus which varies significantly with IOL power and design. Given that peripheral defocus is related to lens power, replacement of the crystalline lens (approximately 24 D) with an IOL will produce a significant difference in peripheral defocus profile after surgery. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy (DR) arises from blood vessel damage and is a leading cause of blindness on a global scale. Clinical professionals rely on examining fundus images to diagnose the disease, but this process is frequently prone to errors and is tedious. The usage of computer-assisted techniques offers assistance to clinicians in detecting the severity levels of the disease. Experiments involving automated diagnosis employing convolutional neural networks (CNNs) have produced impressive outcomes in medical imaging. At the same time, retinal image grading for detecting DR severity levels has predominantly focused on spatial features. More spectral features must be explored for a more efficient performance of this task. Analysing spectral features plays a vital role in various tasks, including identifying specific objects or materials, anomaly detection, and differentiation between different classes or categories within an image. In this context, a model incorporating Wavelet CNN and Support Vector Machine has been introduced and assessed to classify clinically significant grades of DR from retinal fundus images. The experiments were conducted on the EyePACS dataset and the performance of the proposed model was evaluated on the following metrics: precision, recall, F1-score, accuracy, and AUC score. The results obtained demonstrate better performance compared to other state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Background: Early melanoma detection is the main factor affecting prognosis and survival. For that reason, non‐invasive technologies have been developed to provide a more accurate diagnosis. Recently, line‐field confocal optical coherence tomography (LC‐OCT) was developed to provide an in vivo, imaging device, with deep penetration and cellular resolution in three dimensions. Combining the advantages of conventional OCT and reflectance confocal microscopy, this tool seems to be particularly suitable for melanocytic lesions. Objectives: The objective of this study was to identify and describe the correlation between specific dermoscopic criteria and LC‐OCT features in three dimensions associated with melanocytic lesions. Methods: Dermoscopic and LC‐OCT images of 126 melanocytic lesions were acquired in three different centres. The following dermoscopic criteria have been considered: reticular pattern, dots and globules, structureless areas, blue‐whitish veil, regression structures, negative network, homogeneous pattern, streaks and blotches. Results: 69 (55%) benign and 57 (45%) malignant lesions were analysed. A regular reticular pattern was found associated in the 75% of the cases with the presence of elongated rete ridges with pigmented cells along the basal layer, while atypical reticular pattern showed an irregular organization of rete ridges with melanocytic hyperplasia, broadened and fused ridges and elongated nests. Both typical and atypical dots and globules were found associated with melanocytic nests in the dermis or at the dermoepidermal junction (DEJ), as well as with keratin cysts/pseudocysts. Grey globules corresponded to the presence of melanin‐containing dermal inflammatory cells (melanophages) within the papillae. Structureless brown/black areas correlated with alterations of the DEJ. We observed the same DEJ alterations, but with the presence of dermal melanophages, in 36% of the cases of blue/white/grey structureless areas. A description of each LC‐OCT/dermoscopy correlation was made. Conclusions: LC‐OCT permitted for the first time to perform an in vivo, 3D correlation between dermoscopic criteria and pathological‐like features of melanocytic lesions. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this work is to estimate the sensitivity, specificity, and misclassification rate of an automated retinal image analysis system (ARIAS) in diagnosing active diabetic macular edema (DME) and to identify factors associated with true and false positives. Methods: We conducted a cross-sectional study of prospectively enrolled patients with diabetes mellitus (DM) referred to a tertiary medical retina center for screening or management of DME. All patients underwent two-field fundus photography (macula- and disc-centered) with a true-color confocal camera; images were processed by EyeArt V.2.1.0 (Woodland Hills, CA, USA). Active DME was defined as the presence of intraretinal or subretinal fluid on spectral-domain optical coherence tomography (SD-OCT). Sensitivity and specificity and their 95% confidence intervals (CIs) were calculated. Variables associated with true (i.e., DME labeled as present by ARIAS + fluid on SD-OCT) and false positives (i.e., DME labeled as present by ARIAS + no fluid on SD-OCT) of active DME were explored. Results: A total of 298 eyes were included; 92 eyes (31%) had active DME. ARIAS sensitivity and specificity were 82.61% (95% CI 72.37–89.60) and 84.47% (95% CI 78.34–89.10). The misclassification rate was 16%. Factors associated with true positives included younger age (p = 0.01), shorter DM duration (p = 0.006), presence of hard exudates (p = 0.005), and microaneurysms (p = 0.002). Factors associated with false positives included longer DM duration (p = 0.01), worse diabetic retinopathy severity (p = 0.008), history of inactivated DME (p < 0.001), and presence of hard exudates (p < 0.001), microaneurysms (p < 0.001), or epiretinal membrane (p = 0.06). Conclusions: The sensitivity of ARIAS was diminished in older patients and those without DME-related fundus lesions, while the specificity was reduced in cases with a history of inactivated DME. ARIAS performed well in screening for naïve DME but is not effective in surveillance inactivated DME. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To assess self-reported awareness of diabetic retinopathy (DR) and concordance of eye examination follow-up compared with findings from concurrent retinal images. RESEARCH DESIGN AND METHODS: We conducted a prospective observational 10-year study of 26,876 consecutive patients with diabetes who underwent retinal imaging during an endocrinology visit. Awareness and concordance were evaluated using questionnaires and retinal imaging. RESULTS: Awareness information and gradable images were available in 25,360 patients (94.3%). Severity of DR by imaging was as follows: no DR (n = 14,317; 56.5%), mild DR (n = 6,805; 26.8%), or vision-threatening DR (vtDR; n = 4,238; 16.7%). In the no, mild, and vtDR groups, 96.7%, 88.5%, and 54.9% of patients, respectively, reported being unaware of any prior DR. When DR was present, reporting no prior DR was associated with shorter diabetes duration, milder DR, last eye examination >1 year before, no dilation, no scheduled appointment, and less specialized provider (all P < 0.001). Among patients with vtDR, 41.2%, 58.1%, and 64.2% did not report being aware of any DR and follow-up was concordant with current DR severity in 66.7%, 41.3%, and 25.4% (P < 0.001) of patients when prior examination was performed by a retinal specialist, nonretinal ophthalmologist, or optometrist (P < 0.001), respectively. CONCLUSIONS: Substantial discrepancies exist between DR presence, patient awareness, and concordance of follow-up across all DR severity levels. These discrepancies are present across all eye care provider types, with the magnitude influenced by provider type. Therefore, patient self-report should not be relied upon to reflect DR status. Modification of medical care and education models may be necessary to enhance retention of ophthalmic knowledge in patients with diabetes and ensure accurate communication between all health care providers. [ABSTRACT FROM AUTHOR]

Purpose: The recent development of a portable investigational handheld OCT-angiography (OCTA) device has allowed for expansion of imaging into the operating room (OR) in addition to standard in-clinic imaging. The aim of this study was to assess intravisit repeatability and intervisit reproducibility of retinal microvasculature measures and central retinal thickness for in-clinic table-top and portable OR compatible OCTA devices. Methods: Repeated 10 × 10 OCTA images were acquired in 20 healthy adult participants on two separate visit days using Spectralis spectral-domain OCTA table-top and investigational armature suspended Flex systems. Intravisit and intervisit intraclass correlation coefficients and average absolute percent difference were calculated for quantitative microvasculature measures and CRT. Results: 120 OCTA images were acquired from 20 subjects (n = 20, mean age 26.7 ± 1.61 years, range 24–30 years) with both devices across two separate imaging days. FAZ and CRT measurements had near complete intravisit and intervisit agreement with ICCs between.97 and 1 for both table-top (FAZ ICC.97,.97; CRT ICC.98–1,.98–.99) and Flex (FAZ ICC.97,.95; CRT ICC.99–1,.98–.99) devices. Vessel density measures demonstrated greater variance with only fair to strong agreement (ICC.32–.75) and average absolute percent differences ranging from 2.96 to 6.63%. Conclusion: FAZ and CRT measures for both devices demonstrated high repeatability and reproducibility; retinal vessel density measures demonstrated less. Differences of less than 7% for retinal microvasculature measurements across time and devices are most likely attributable to expectable variance between repeat scans. [ABSTRACT FROM AUTHOR]

Background: Kabuki Syndrome is a rare and genetically heterogenous condition with both ophthalmic and systemic complications and typical facial features. We detail the macular phenotype in two unrelated patients with Kabuki syndrome due to de novo nonsense variants in KMT2D, one novel. A follow-up of 10 years is reported. Pathogenicity of both de novo nonsense variants is analyzed. Methods: Four eyes of two young patients were studied by full clinical examination, kinetic perimetry, short wavelength autofluorescence, full field (ff) ERGs, and spectral-domain optical coherence tomography (SD-OCT). One patient had adaptive optic (AO) imaging. Whole exome sequencing was performed in both patients. Results: Both patients had de novo nonsense variants in KMTD2. One patient had c.14843C>G; p. (Ser4948ter) novel variant and the second c.11119C>T; p. (Arg3707ter). Both had a stable Snellen visual acuity of 0.2–0.3. The retinal multimodal imaging demonstrated abnormalities at the fovea in both eyes: hyperreflectivity to blue light and a well-delimited gap—disruption of ellipsoid and interdigitation layer on OCT. The dark area on AO imaging is presumed to be absent for, or with structural change to photoreceptors. The ff ERGs and kinetic visual fields were normal. The foveal findings remained stable over several years. Conclusion: Kabuki syndrome–related maculopathy is a distinct loss of photoreceptors at the fovea as shown by multimodal imaging including, for the first time, AO imaging. This report adds to the literature of only one case with maculopathy with two additional macular dystrophies in patients with Kabuki syndrome. Although underestimated, these cases further raise awareness of the potential impact of retinal manifestations of Kabuki syndrome not only among ophthalmologists but also other healthcare professionals involved in the care of patients with this multisystem disorder. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate if retinal vascular calibers and systemic risk factors in patients with no or minimal diabetic retinopathy (DR) can predict risk of long‐term progression to proliferative diabetic retinopathy (PDR). Methods: This was a matched case–control study of patients with diabetes having no or minimal DR at baseline with (cases) or without (controls) subsequent development of PDR. We collected six‐field, 45‐degree retinal images, demographic and clinical data from the Funen Diabetes Database. Results: We included 52 eyes from 39 cases and 107 eyes from 89 controls matched on sex, age, type of diabetes, time from first to last screening episode and baseline DR level. Cases had higher HbA1c (73 vs. 55 mmoL/moL; p < 0.001), triglycerides (1.32 vs. 1.16 mmoL/L; p = 0.02) and longer duration of diabetes (19 vs. 14 years; p = 0.01), but the groups did not differ in calibers of retinal arterioles (229 vs. 227 μm; p = 0.49), venules (289 vs. 290 μm; p = 0.83) or the arterio‐to‐venule ratio (0.78 vs. 0.77; p = 0.86).In a multivariable logistic regression model with cluster robust standard error, HbA1c (OR 1.54 per 10 mmoL/moL; 95%‐CI: 1.15–2.07; p = 0.004), triglyceride (OR 1.39 per 1 mmoL/L; 95%‐CI: 1.03–1.86; p = 0.03) and duration of diabetes (OR 1.09 per year; 95%‐CI: 1.03–1.16; p = 0.003) were independent risk factors for PDR. Conclusion: Retinal vascular calibers did not predict long‐term development of PDR in contrast to well‐established risk factors like HbA1c, triglyceride and duration of diabetes. [ABSTRACT FROM AUTHOR]

PurposeMethodsResultsConclusionTo report the clinical course and the retinal imaging features of a case of cytology-proven primary vitreoretinal lymphoma (PVRL) presenting with a transient bacillary layer detachment (BALAD) during the disease course.Observational case report.A 50 year-old woman was referred to us with a 2-month history of vitritis in both eyes, poorly responding to oral prednisolone. After discontinuation of oral prednisolone, worsening of vitritis and the appearance of multiple creamy-like subretinal infiltrates in the mid-peripheral retina of both eyes, along with the exclusion of common causes of intermediate/posterior uveitis, made us consider PVRL. Aqueous humor sampling detected MYD88 L265P mutation, and subsequent diagnostic pars plana vitrectomy in the left eye yielded a positive cytology for large B cell lymphoma consistent with PVRL. During the disease course, optical coherence tomography of the macula showed a BALAD in the right eye, which resolved during follow-up.Our case indicates that BALAD is a possible rare manifestation of PVRL, and this should be considered in the differential diagnosis process in order to avoid diagnostic delays. [ABSTRACT FROM AUTHOR]

Classifying retinal diseases is a complex problem because the early problematic areas of retinal disorders are quite small and conservative. In recent years, Transformer architectures have been successfully applied to solve various retinal related health problems. Age-related macular degeneration (AMD) and diabetic macular edema (DME), two prevalent retinal diseases, can cause partial or total blindness. Diseases therefore require an early and accurate detection. In this study, we proposed Vision Transformer (ViT), Tokens-To-Token Vision Transformer (T2T-ViT) and Mobile Vision Transformer (Mobile-ViT) algorithms to detect choroidal neovascularization (CNV), drusen, and diabetic macular edema (DME), and normal using optical coherence tomography (OCT) images. The predictive accuracies of ViT, T2T-ViT and Mobile-ViT achieved on the dataset for the classification of OCT images are 95.14%, 96.07% and 99.17% respectively. Experimental results obtained from ViT approaches showed that Mobile-ViT have superior performance with regard to classification accuracy in comparison with the others. Overall, it has been observed that ViT architectures have the capacity to classify with high accuracy in the diagnosis of retinal diseases. [ABSTRACT FROM AUTHOR]

Saccadic eye movements enable us to search for the target of interest in a crowded scene or, in the case of goal-directed saccades, to simply bring the image of the peripheral target to the very centre of the fovea. This mechanism extends the use of the superior image processing performance of the fovea over a large visual field. We know that visual information is processed quickly at the end of each saccade but estimates of the times involved remain controversial. This study aims to investigate the processing of visual information during post fixation oscillations of the eyeball. A new psychophysical test measures the combined eye movement response latencies, including fixation duration and visual processing times. When the test is used in conjunction with an eye tracker, each component that makes up the 'integrated saccade latency' time, from the onset of the peripheral stimulus to the correct interpretation of the information carried by the stimulus, can be measured and the discrete components delineated. The results show that the time required to process and encode the stimulus attribute of interest at the end of a saccade is longer than the time needed to carry out the same task in the absence of an eye movement. We propose two principal hypotheses, each of which can account for this finding. 1. The known inhibition of afferent retinal signals during fast eye movements extends beyond the end point of the saccade. 2. The extended visual processing times measured when saccades are involved are caused by the transient loss of spatial resolution due to eyeball instability during post-saccadic oscillations. The latter can best be described as retinal image smear with greater loss of spatial resolution expected for stimuli of low luminance contrast. [ABSTRACT FROM AUTHOR]

Featured Application: The Deep Neural Network model employed in this work will help build a system for the pre-diagnosis of retinopathies that can lead to blindness. The main intention of this type of system is to support the work performed by ophthalmology specialists. Computer-based pre-diagnosis of diseases through medical imaging is a task worked on for many years. The so-called fundus images stand out since they do not have uniform illumination and are highly sensitive to noise. One of the diseases that can be pre-diagnosed through fundus images is age-related macular degeneration, which initially manifests as the appearance of lesions called drusen. Several ways of pre-diagnosing macular degeneration have been proposed, methods based entirely on the segmentation of drusen with prior image processing have been designed and applied, and methods based on image pre-processing and subsequent conversion to feature vectors, or patterns, to be classified by a Machine-Learning model have also been developed. Finally, in recent years, the use of Deep-Learning models, particularly Convolutional Networks, has been proposed and used in classification problems where the data are only images. The latter has allowed the so-called transfer learning, which consists of using the learning achieved in the solution of one problem to solve another. In this paper, we propose the use of transfer learning through the Xception Deep Convolutional Neural Network to detect age-related macular degeneration in fundus images. The performance of the Xception model was compared against six other state-of-the-art models with a dataset created from images available in public and private datasets, which were divided into training/validation and test; with the training/validation set, the training was made using 10-fold cross-validation. The results show that the Xception neural network obtained a validation accuracy that surpasses other models, such as the VGG-16 or VGG-19 networks, and had an accuracy higher than 80% in the test set. We consider that the contributions of this work include the use of a Convolutional Neural Network model for the detection of age-related macular degeneration through the classification of fundus images in those affected by AMD (drusen) and the images of healthy patients. The performance of this model is compared against other methods featured in the state-of-the-art approaches, and the best model is tested on a test set outside the training and validation set. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate the imaging capabilities of Butterfly iQ with conventional ophthalmic (piezoelectric) ultrasound (COU) for ophthalmic imaging. Methods: Custom phantom molds were designed and imaged with Butterfly iQ and COU to compare spatial resolution capabilities. To evaluate the clinical imaging performance of Butterfly iQ and COU, a survey containing pathological conditions from human subjects, imaged with both Butterfly iQ and COU probes, was given to three retina specialists and graded on image detail, resolution, quality, and diagnostic confidence on a ten-point Likert scale. Kruskal-Wallis analysis was performed for survey responses. Results: Butterfly iQ and COU had comparable capabilities for imaging small axial and lateral phantom features (down to 0.1 mm) of high and low acoustic reflectivity. One of three retina specialists demonstrated a statistically significant preference for COU related to resolution, detail, and diagnostic confidence, but the remaining graders showed no significant preference for Butterfly iQ or COU across all sample images presented. Conclusion: The emergence of portable ultrasound probes offers an affordable alternative to COU technologies with comparable qualitative imaging resolution down to 0.1 mm. These findings suggest the value to further study the use of portable ultrasound systems and their utility in routine eye care. [ABSTRACT FROM AUTHOR]

The definition of complete resection in neurosurgery depends on tumor type, surgical aims, and postoperative investigations, directly guiding the choice of intraoperative tools. Most common tumor types present challenges in achieving complete resection due to their infiltrative nature and anatomical constraints. The development of adjuvant treatments has altered the balance between oncological aims and surgical risks. We review local recurrence associated with incomplete resection based on different definitions and emphasize the importance of achieving maximal safe resection in all tumor types. Intraoperative techniques that aid surgeons in identifying tumor boundaries are used in practice and in preclinical or clinical research settings. They encompass both conservative and invasive techniques. Among them, morphological tools include imaging modalities such as intraoperative magnetic resonance imaging, ultrasound, and optical coherence tomography. Fluorescence-guided surgery, mainly using 5-aminolevulinic acid, enhances gross total resection in glioblastomas. Nuclear methods, including positron emission tomography probes, provide tumor detection based on beta or gamma emission after a radiotracer injection. Mass spectrometry– and spectroscopy-based methods offer molecular insights. The adoption of these techniques depends on their relevance, effectiveness, and feasibility. With the emergence of positron emission tomography imaging for use in recurrence benchmarking, positron emission tomography probes raise particular interest among those tools. While all such tools provide valuable insights, their clinical benefits need further evaluation. [ABSTRACT FROM AUTHOR]

MEK inhibitors (MEKi) represent innovative and promising treatments for managing manifestations of neurofibromatosis type 1 (NF1). To mitigate potential ophthalmic side effects, such as MEKi-associated retinopathy (MEKAR), patients undergoing MEKi therapy routinely receive ophthalmology evaluations. Our study aims to assess the necessity of this regular screening within a predominantly pediatric NF1 population by examining the occurrence of ocular adverse events (OAE). A retrospective study evaluated 45 NF1 patients receiving MEKi. Inclusion criteria included baseline and follow-up examinations following the initiation of MEKi therapy. At each assessment, a comprehensive eye evaluation was performed, comprising a dilated fundus examination, ocular coherence tomography of the macula and nerve fiber layer, and Humphrey visual field testing. Twenty-six patients, with an average age of 13 years (range 2–23 years) and an average follow-up duration of 413 days were included in the analysis. Three different MEKi were used: selumetinib (77%), trametinib (23%), and mirdametinib (4%). None of the patients experienced retinopathy at any point during the study. Some patients had pre-existing optic neuropathies (27%), but no instances of nerve changes occurred after commencing MEKi therapy. Four patients (15%) exhibited symptoms of dry eye, all of which were effectively managed with topical lubrication. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the sensitivity and specificity of swept-source optical coherence tomography (SS-OCT) biometer compared with the gold standard spectral-domain optical coherence tomography (SD-OCT) for detecting macular pathology in patients with cataract. Setting: Eye Centers of Tennessee, Crossville, TN. Design: Prospective, cross-sectional, observational, examiner- masked. Methods: The study included 132 participants aged 50 years and older, who underwent precataract surgery work-up. All participants underwent fixation check retinal scans using SS-OCT biometer (IOLMaster 700) as well as full macular scans using Cirrus SD-OCT. 3 independent masked examiners evaluated the scans if they were normal or had a suspected pathology. Different measures of diagnostic accuracy were calculated for 3 examiners. Results: True positive rate (sensitivity) ranged from 71.1% (32/45) to 79.2% (42/53), and false negative rate was between 20.8% (11/53) and 28.9% (13/45) for the 3 examiners. True negative rate (specificity) ranged from 86.8% (59/68) to 94.1% (64/68), and false positive rate was between 5.9 (4/68) and 13.2% (9/68). The fitted receiver operating characteristic area ranged from 0.83 to 0.95. Conclusions: Using retinal SS-OCT biometer scans as a re-placement of the dedicated macular SD-OCT for screening or diagnosing macular health would not be appropriate because of its low sensitivity. SS-OCT biometer may potentially fail to identify approximately one-fourth of patients who actually have the disease. Therefore, the final decision on macular health should be based on the gold standard SD-OCT scans. When full macular SD-OCT scans are not accessible, the limited retinal scan information from SS-OCT biometer may still provide useful insights into the macular health. [ABSTRACT FROM AUTHOR]

Patients with incurable corneal diseases experience visual impairment (VI) despite having a healthy retina and optic pathway. Low-vision aids (LVAs) can optimize the use of remaining vision through magnification and contrast enhancement, but do not harness the full visual capacity because they rely on the optic media. Therefore, we investigated a novel laser eyewear (LEW) technology that bypasses the anterior segment of the eye. Images captured by an integrated camera are projected directly onto the retina using a low-energy laser. The patient is able to view a full-color video, realized as augmented reality. We aimed to evaluate the efficacy of the LEW to enhance the vision of individuals with corneal diseases. Prospective, randomized, crossover clinical trial. We examined the retinal projection glasses in 21 patients (25–69 years) with VI (0.7 logarithm of the minimum angle of resolution [logMAR] or worse) resulting from corneal diseases. Patients with comorbidities that impact vision, such as retinal disorders, were excluded. Standardized measurements of visual acuity (VA) for near vision (NV) and distance vision (DV) were conducted using ETDRS charts with the respective best correction (BC) and then with LEW. In addition reading speed, vision-related quality of life (QoL) and capacity to carry out daily tasks were assessed at an initial visit and at 2 subsequent visits after a home phase with and without the device. Six weeks after last use of the LEW, an ophthalmologic examination including spectral-domain-OCT or full-field-electroretinography was conducted and compared with baseline findings to evaluate the safety of the device. Four patients participated and completed a subsequent 12-month follow-up phase. Improvement of VA using the LEW. Secondary objectives included safety, reading speed, QoL, and usability in daily activities. The mean VA in patients with VI was improved by 0.43 logMAR in DV using the LEW compared with BC (P < 0.0001). Using the ×2 magnification mode of the LEW resulted in an average improvement of 0.66 logMAR compared with BC (P < 0.0001). In NV, an increase of 0.47 logMAR was achieved compared with BC (P < 0.0001). Although only 4 of 21 participants were able to read with BC, 17 of 21 participants were able to read with the LEW. Quality of life significantly improved in the 17 participants who completed all visits. We demonstrated that the retinal projection glasses resulted in enhanced VA for all participants by directly projecting images onto the intact retina. In future, the LEW could represent a new option as an LVA for patients with corneal diseases. No pathological alterations were observed in the safety assessments. The author(s) have no proprietary or commercial interest in any materials discussed in this article. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide. Early detection and effective risk assessment are crucial for implementing preventive measures and improving patient outcomes for CVDs. This work presents a novel approach to CVD risk assessment using fundus images, leveraging the inherent connection between retinal microvascular changes and systemic vascular health. This study aims to develop a predictive model for the early detection of CVDs by evaluating retinal vascular parameters. This methodology integrates both handcrafted features derived through mathematical computation and retinal vascular patterns extracted by artificial intelligence (AI) models. By combining these approaches, we seek to enhance the accuracy and reliability of CVD risk prediction in individuals. The methodology integrates state-of-the-art computer vision algorithms and AI techniques in a multi-stage architecture to extract relevant features from retinal fundus images. These features encompass a range of vascular parameters, including vessel caliber, tortuosity, and branching patterns. Additionally, a deep learning (DL)-based binary classification model is incorporated to enhance predictive accuracy. A dataset comprising fundus images and comprehensive metadata from the clinical trials conducted is utilized for training and validation. The proposed approach demonstrates promising results in the early prediction of CVD risk factors. The interpretability of the approach is enhanced through visualization techniques that highlight the regions of interest within the fundus images that are contributing to the risk predictions. Furthermore, the validation conducted in the clinical trials and the performance analysis of the proposed approach shows the potential to provide early and accurate predictions. The proposed system not only aids in risk stratification but also serves as a valuable tool for identifying vascular abnormalities that may precede overt cardiovascular events. The approach has achieved an accuracy of 85% and the findings of this study underscore the feasibility and efficacy of leveraging fundus images for cardiovascular risk assessment. As a non-invasive and cost-effective modality, fundus image analysis presents a scalable solution for population-wide screening programs. This research contributes to the evolving landscape of precision medicine by providing an innovative tool for proactive cardiovascular health management. Future work will focus on refining the solution's robustness, exploring additional risk factors, and validating its performance in additional and diverse clinical settings. [ABSTRACT FROM AUTHOR]

Optical coherence tomography (OCT) is widely used to probe retinal structure and function. This study investigated the outer retina band (ORB) pattern and reflective intensity for the region between bands 2 and 3 (Dip) in three mouse models of inherited retinal degeneration (Rs1KO, TTLL5KO, RPE65KO) and in human AMD patients from the A2A database. OCT images were manually graded, and reflectivity signals were used to calculate the Dip ratio. Qualitative analyses demonstrated the progressive merging band 2 and band 3 in all three mouse models, leading to a reduction in the Dip ratio compared to wildtype (WT) controls. Gene replacement therapy in Rs1KO mice reverted the ORB pattern to one resembling WT and increased the Dip ratio. The degree of anatomical rescue in these mice was highly correlated with level of transgenic RS1 expression and with the restoration of ERG b-wave amplitudes. While the inner retinal cavity was significantly enlarged in dark-adapted Rs1KO mice, the Dip ratio was not altered. A reduction of the Dip ratio was also detected in AMD patients compared with healthy controls and was also positively correlated with AMD severity on the AMD score. We propose that the ORB and Dip ratio can be used as non-invasive early biomarkers for retina health, which can be used to probe therapeutic gene expression and to evaluate the effectiveness of therapy. [ABSTRACT FROM AUTHOR]

3-D assessing of intracanal anatomy in the clinical endodontic practice is always challenging. Although computed tomography could visualize intracanal anatomy but, they all use harmful ionized radiation and presented low sensitivity in detection of fine canal anatomy images. Optical coherence tomography (OCT) is a high-resolution imaging technique that allows micrometer scale imaging of biologic tissues over small distances, uses infrared light waves that reflect off the internal microstructure within the biologic tissues and gives high resolution images. In studies OCT has previously been shown to be a valuable tool in assessing intracanal anatomy, cleanliness of the canal after preparation, and even perforations. Aim: To evaluate the ability of optical coherence tomography (OCT) to image root canal walls, and to identify confounding factors in root canal treatment. Histological validation of data acquisition for root canal lumen dimensions (area and diameter) obtained from OCT scan. Methodology: Maxillary incisors with poor prognosis for endodontic treatment outcome were scanned for canal lumen dimension using Intra coronary OCT probe modality. The same tooth were extracted, was sectioned to get a total number of 20 slices (n=20). Root canal lumen dimension of each slice was validated and compared histologically, double blindedly using Nikon digital microscope software (NIKON DS -Ri2) with dimensions obtained by OCT scan. The mean data acquired by OCT were correlation with histological slices using co-relation regression test. Results: A strong correlation was found between the data acquired by using OCT and histology for area of canal lumen r (area) = 0.97, max and min diameter r= 0.95, 0.93 respectively. Conclusion: Optical coherence tomography is a non-invasive and non-destructive technique for endodontic imaging. It proved to be suitable for analysing the anatomy and cleanliness of root canal walls, and has a high sensitivity and specificity for detection of internal anatomy of canals. OCT generates high-resolution, real-time, intra-canal microscopic images, and holds great potential for in-vivo application. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the changes in retinal arterial architecture after treatment with voretigene neparvovec in patients with retinal dystrophy caused by bi‐allelic mutations in the RPE65 gene. Methods: Sixteen eyes treated with voretigene neparvovec at the University Eye Clinic in Tuebingen, Germany, underwent adaptive optics ophthalmoscopy (AO) imaging at baseline and 2 weeks, 1, 3, 6 and 12 months after treatment. Follow‐up was performed in six eyes of four patients. For each eye, five different positions at arterial vessels were selected and the wall‐to‐lumen ratio (WLR), the lumen diameter (LD) and the wall cross‐sectional area (WCSA) were measured by the manufacturer's software over the observational period. Results: Vast retinal atrophy dominated all gained AO images. WLR fluctuated in the observation period without statistically significant change. LD and WCSA changed significantly after 2 weeks from the baseline examination and returned to values similar to baseline thereafter. There were no signs of inflammation such as macrophages or perivascular accumulated fluid visible. Conclusion: AO imaging of the retinal vessels in RPE65‐associated retinal dystrophies (IRD) is challenging. There was no change in the retinal arterial vasculature over the observation period of 12 months that would indicate inflammatory changes. Decrease of the LD and WCSA shortly after treatment might be caused by the perioperative prednisolone intake. AO of retinal vessels can be used as a diagnostic module to complement monitoring the disease and effects of genetic treatments if the acquisition is possible in selected cases. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate a new automated retinal oximetry image quality indicator with cataract as a clinical model. Methods: Sixty‐one eyes in 61 patients were imaged by the Oxymap T1 Retinal Oximeter at baseline and 25 eyes were also examined 3 weeks after cataract surgery. Image quality (0–10 on a continuous scale) was compared with standardized AREDS cataract grading and Pentacam lens densitometry. Associations with retinal oximetry measurements and visual acuity were examined. Results: Image quality correlated with total, nuclear and posterior subcapsular cataract grades (ANOVA, p < 0.05), tended to be associated with lens densitometry and it improved from 4.3 ± 1.4 to 5.7 ± 1.0 (p < 0.05) after cataract surgery. Very low image quality, below 3, led to vessel detection failure in retinal oximetry images. Higher image qualities were linearly associated with higher measured retinal oxygen saturations (r = 0.52 in arteries and r = 0.46 in veins; p < 0.001). Conclusion: Retinal oximetry image quality deteriorated with increasing cataract density and improved after cataract surgery, supporting its use as a measure of optical clarity. The numerical quality indicator demonstrated a threshold below which images of poor optical quality should be discarded. Image quality affects the estimates of retinal oximetry parameters and should therefore be included in future analyses. [ABSTRACT FROM AUTHOR]

In recent years, several studies have undergone automatic blood vessel segmentation based on unsupervised and supervised algorithms to reduce user interruption. Deep learning networks have been used to get highly accurate segmentation results. However, the incorrect segmentation of pathological information and low micro-vascular segmentation is considered the challenges present in the existing methods for segmenting the retinal blood vessel. It also affects different degrees of vessel thickness, contextual feature fusion in technique, and perception of details. A deep learning-aided method has been presented to address these challenges in this paper. In the first phase, the preprocessing is performed using the retinal fundus images employed by the black ring removal, LAB conversion, CLAHE-based contrast enhancement, and grayscale image. Thus, the blood vessel segmentation is performed by a new deep learning model termed optimized ResUNet + +. As an improvement to this deep learning architecture, the activation function is optimized by the J-AGSO algorithm. The objective function for the optimized ResUNet + + -based blood vessel segmentation is to minimize the binary cross-entropy loss function. Further, the post-processing of the images is carried out by median filtering and binary thresholding. By verifying the standard benchmark datasets, the proposed model outperforms and attains enhanced performance. [ABSTRACT FROM AUTHOR]

Diabetic Retinopathy (DR) and Glaucoma are two of the most common causes of vision loss world-wide. However, it can be averted if therapy is begun early enough. In biomedical applications, the use of digital image processing has assisted in the automated identification of some ailments at an earlier stage. To make this prediction generally neural network classifier models were previously used, but these models have the drawback of being unable to detect multiple illnesses that occur in the eye at the same time and require a big database for successful classifier training. As a result, a model is needed to reliably distinguish DR and Glaucoma in diabetic individuals more accurately and with minimum dataset images. In this view, this study introduced Mayfly Optimized Deep Convolutional Network (MODCN) model for automated disease detection in the fundus retina images. In the MODCN model, the images are initially preprocessed, segmented at generator in the GAN model then a discriminator readily gives synthesis of real images of the fundus retina, thus a wide database has been created and considered as training images for the MODCN classifier. MODCN classifier has a modified high-density layer as a transition layer to avoid overfitting and the errors are minimized by tuning the hyperparameters using Mayfly Optimization Algorithm. After feature mapping, the classes normal, DR and Glaucoma are labeled and stored. At the testing stage, images are preprocessed, feature mapped and classified in the MODCN model. Thus, the proposed MODCN model detects multiple illness such as Diabetic Retinopathy and Glaucoma at the same time even with a small amount of database that performs a successful classifier training. This model is then evaluated and gives an accuracy of 99% that was higher compared to previous models. [ABSTRACT FROM AUTHOR]

Background: Stroke is a leading cause of morbidity and mortality. Retinal imaging allows non-invasive assessment of the microvasculature. Consequently, retinal imaging is a technology which is garnering increasing attention as a means of assessing cardiovascular health and stroke risk. Methods: A biomedical literature search was performed to identify prospective studies that assess the role of retinal imaging derived biomarkers as indicators of stroke risk. Results: Twenty-four studies were included in this systematic review. The available evidence suggests that wider retinal venules, lower fractal dimension, increased arteriolar tortuosity, presence of retinopathy, and presence of retinal emboli are associated with increased likelihood of stroke. There is weaker evidence to suggest that narrower arterioles and the presence of individual retinopathy traits such as microaneurysms and arteriovenous nicking indicate increased stroke risk. Our review identified three models utilizing artificial intelligence algorithms for the analysis of retinal images to predict stroke. Two of these focused on fundus photographs, whilst one also utilized optical coherence tomography (OCT) technology images. The constructed models performed similarly to conventional risk scores but did not significantly exceed their performance. Only two studies identified in this review used OCT imaging, despite the higher dimensionality of this data. Conclusion: Whilst there is strong evidence that retinal imaging features can be used to indicate stroke risk, there is currently no predictive model which significantly outperforms conventional risk scores. To develop clinically useful tools, future research should focus on utilization of deep learning algorithms, validation in external cohorts, and analysis of OCT images. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is the most frequent cause of death worldwide. The alterations in the microcirculation may predict the cardiovascular mortality. The retinal vasculature can be used as a model to study vascular alterations associated with cardiovascular disease. In order to quantify microvascular changes in a non-invasive way, fundus images can be taken and analysed. The central retinal arteriolar (CRAE), the venular (CRVE) diameter and the arteriolar-to-venular diameter ratio (AVR) can be used as biomarkers to predict the cardiovascular mortality. A narrower CRAE, wider CRVE and a lower AVR have been associated with increased cardiovascular events. Dynamic retinal vessel analysis (DRVA) allows the quantification of retinal changes using digital image sequences in response to visual stimulation with flicker light. This article is not just a review of the current literature, it also aims to discuss the methodological benefits and to identify research gaps. It highlights the potential use of microvascular biomarkers for screening and treatment monitoring of cardiovascular disease. Artificial intelligence (AI), such as Quantitative Analysis of Retinal vessel Topology and size (QUARTZ), and SIVA–deep learning system (SIVA-DLS), seems efficient in extracting information from fundus photographs and has the advantage of increasing diagnosis accuracy and improving patient care by complementing the role of physicians. Retinal vascular imaging using AI may help identify the cardiovascular risk, and is an important tool in primary cardiovascular disease prevention. Further research should explore the potential clinical application of retinal microvascular biomarkers, in order to assess systemic vascular health status, and to predict cardiovascular events. [ABSTRACT FROM AUTHOR]

Aim: The retina and brain share similar anatomical and physiological features. Thus, retinal imaging by optical coherence tomography angiography (OCTA) might be a potential tool for the early diagnosis of diabetic cerebral small vessel disease (CSVD). In this study, we aimed to evaluate retinal vascular density (VD) in diabetic CSVD by OCTA imaging and explore the associations between retinal VD and cerebral magnetic resonance imaging (MRI) markers and cognitive function. Methods: In total, 131 patients were enrolled, including CSVD (n = 43) and non‐CSVD groups (n = 88). The VD and foveal avascular zone of the retinal capillary plexus were measured with OCTA. A brain MRI was performed. Results: MRI imaging showed that in the diabetic CSVD group, white matter hyperintensities (WMHs), particularly deep WMHs (58.82%), are the most common MRI marker, followed by cerebral microbleeds in the subtentorial and cortical areas (34.78%). The CSVD group showed increases in the prevalence of cognitive dysfunction (p =.034) and depression (p =.033) and decreases in visuospatial/executive ability and delayed recall ability. In the CSVD group, VDs of the macular superficial vascular plexus (32.93 ± 7.15% vs. 36.97 ± 6.59%, p =.002), intermediate capillary plexus (20.87 ± 4.30% vs. 23.08 ± 4.30%, p =.005) and deep capillary plexus (23.54 ± 5.00% vs. 26.05 ± 4.20%, p =.003) were lower than those of the non‐CSVD group. Multiple linear regression analysis showed that VD of the macular superficial vascular plexus was independently associated with cerebral microbleeds. Meanwhile, VD of the macular intermediate capillary plexus was associated with white matter lacunar infarcts after adjustment. Conclusions: Diabetic CSVDs are characterized by MRI markers, including deep WMHs and cerebral microbleeds, and showed impaired cognition with decreased visuospatial/executive ability and delayed recall ability. OCTA imaging revealed a significant decrease in retinal microvascular perfusion in diabetic CSVD, which was related to MRI markers and cognitive function. OCTA might be a valuable potential measurement for the early diagnosis of CSVD. [ABSTRACT FROM AUTHOR]

Optical coherence tomography angiography (OCTA) is widely used for non-invasive retinal vascular imaging, but the OCTA methods used to assess retinal perfusion vary. We evaluated the different methods used to assess retinal perfusion between OCTA studies. MEDLINE and Embase were searched from 2014 to August 2021. We included prospective studies including ≥ 50 participants using OCTA to assess retinal perfusion in either global retinal or systemic disorders. Risk of bias was assessed using the National Institute of Health quality assessment tool for observational cohort and cross-sectional studies. Heterogeneity of data was assessed by Q statistics, Chi-square test, and I2 index. Of the 5974 studies identified, 191 studies were included in this evaluation. The selected studies employed seven OCTA devices, six macula volume dimensions, four macula subregions, nine perfusion analyses, and five vessel layer definitions, totalling 197 distinct methods of assessing macula perfusion and over 7000 possible combinations. Meta-analysis was performed on 88 studies reporting vessel density and foveal avascular zone area, showing lower retinal perfusion in patients with diabetes mellitus than in healthy controls, but with high heterogeneity. Heterogeneity was lowest and reported vascular effects strongest in superficial capillary plexus assessments. Systematic review of OCTA studies revealed massive heterogeneity in the methods employed to assess retinal perfusion, supporting calls for standardisation of methodology. [ABSTRACT FROM AUTHOR]

Vision can provide useful cues about the geometric properties of an object, like its size, distance, pose, and shape. But how the brain merges these properties into a complete sensory representation of a three-dimensional object is poorly understood. To address this gap, we investigated a visual illusion in which humans misperceive the shape of an object due to a small change in one eye's retinal image. We first show that this illusion affects percepts of a highly familiar object under completely natural viewing conditions. Specifically, people perceived their own rectangular mobile phone to have a trapezoidal shape. We then investigate the perceptual underpinnings of this illusion by asking people to report both the perceived shape and pose of controlled stimuli. Our results suggest that the shape illusion results from distorted cues to object pose. In addition to yielding insights into object perception, this work informs our understanding of how the brain combines information from multiple visual cues in natural settings. The shape illusion can occur when people wear everyday prescription spectacles; thus, these findings also provide insight into the cue combination challenges that some spectacle wearers experience on a regular basis. [ABSTRACT FROM AUTHOR]

Objective To explore the application value of artificial intelligence (AI) based retinal microvascular analysis in the diagnosis of diabetes retinopathy (DR), diabetes nephropathy (DN) and other diabetes complications. Methods From January to December 2022, 305 subjects from the Health Medicine Department and Endocrine Department of the Eastern Theater Command General Hospital of PLA were divided into healthy control group (n = 119), diabetes without DR group (n = 100), and diabetes with DR group (n = 86) according to the condition of diabetes and its complications. The group of diabetes with DR was further divided into the group without DN (n = 50) and the group with DN (n = 36). Clinical data, laboratory test indicators, and fundus photography results of all the subjects were collected. Independent sample t-test, Kruskal Wallis H-test, and logistic regression analysis were used for data analysis. Results There were statistically significant differences in FBG, 2hPBG, HbA1c, central retinal artery equivalent (CRAE), and retinal arteriovenous ratio (AVR) among the three groups (all P < 0.05). In patients with diabetes complicated with DR, there were statistically significant differences in the history of diabetes, total number of bleeding, total area of exudation, maximum area of exudation and total number of exudation between non-DN group and DN group (all P < 0.05). There was correlation between retinal microvascular indicators and diabetic retinopathy. When the total area of retinal hemorrhage, total area of exudation, and maximum area of exudation increased, the risk of diabetic retinopathy increased. Conclusion AI-based retinal microvascular analysis has value in providing prompt indication and assisting with the diagnosis of complications in diabetic patients. [ABSTRACT FROM AUTHOR]

Background: Endotamponade of the vitreous body with silicone oil is a common procedure, being the basis of many vitreoretinal surgeries. However, emulsification may happen, which is a clinically relevant adverse event of silicone oil use. Methods: This review provides a thorough analysis of the emulsification process. It focuses on describing factors affecting this event as well as its possible subsequent complications. Results: The viscosity of silicone oil, the duration of emulsification, the status of the lens and many other factors have an influence on the onset and intensity of emulsification. This phenomenon carries several risks for operated eyes such as increased intraocular pressure, keratopathy or structural changes to the retina. Conclusions: The use of modern imaging techniques, especially optical coherence tomography, enables faster detection of the emulsification process. This allows for an adequate clinical response and more accurate follow-up of the patient. [ABSTRACT FROM AUTHOR]

Background: Philadelphia-negative chronic myeloproliferative neoplasms are a group of clonal hematopoietic disorders including polycythemia vera, essential thrombocythemia, and primary myelofi-brosis. These neoplasms are characterized by an increased risk of thrombotic complications. Several studies have highlighted that the study of vessels of the retina offers the opportunity to visualize, in vivo, the damage to microcirculation that is common in various systemic pathologies. Methods: in our study, forty patients underwent an ophthalmological examination, using non-invasive imaging tech-niques, for analyses of their retinal vascularization. The objective was to correlate the findings ob-tained from this study of the retina with different markers of thrombotic risk, to demonstrate the usefulness of studying retinal vessels as a possible new prognostic biomarker of thrombotic risk in patients affected by Philadelphia-negative chronic myeloproliferative neoplasms. Results: retinal imaging demonstrated changes in the microcirculation, with a reduced vascular density of the deep and superficial capillary plexuses with respect to a normal group, and a correlation between retinal changes and blood parameters. Conclusions: additional research will allow us to determine whether retinal changes in individuals with chronic myeloproliferative neoplasms could be predictive of the development of thrombotic events in these subjects. [ABSTRACT FROM AUTHOR]

Background: Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME. Methods: A retrospective analysis of 113 eyes from 82 patients with DME was conducted. Comprehensive feature engineering was applied to clinical and optical coherence tomography (OCT) data. Logistic regression, support vector machine (SVM), and backpropagation neural network (BPNN) classifiers were trained using a training set of 79 eyes, and evaluated on a test set of 34 eyes. Clinical implications of the OCT-omics prediction model were assessed by decision curve analysis. Performance metrics (sensitivity, specificity, F1 score, and AUC) were calculated. Results: The logistic, SVM, and BPNN classifiers demonstrated robust discriminative abilities in both the training and test sets. In the training set, the logistic classifier achieved a sensitivity of 0.904, specificity of 0.741, F1 score of 0.887, and AUC of 0.910. The SVM classifier showed a sensitivity of 0.923, specificity of 0.667, F1 score of 0.881, and AUC of 0.897. The BPNN classifier exhibited a sensitivity of 0.962, specificity of 0.926, F1 score of 0.962, and AUC of 0.982. Similar discriminative capabilities were maintained in the test set. The OCT-omics scores were significantly higher in the non-persistent DME group than in the persistent DME group (p < 0.001). OCT-omics scores were also positively correlated with the rate of decline in central subfield thickness after treatment (Pearson's R = 0.44, p < 0.001). Conclusion: The developed OCT-omics model accurately assesses anti-VEGF treatment response in DME patients. The model's robust performance and clinical implications highlight its utility as a non-invasive tool for personalized treatment prediction and retinal pathology assessment. [ABSTRACT FROM AUTHOR]

Inherited retinal diseases (IRDs) represent one of the major causes of progressive and irreversible vision loss in the working-age population. Over the last few decades, advances in retinal imaging have allowed for an improvement in the phenotypic characterization of this group of diseases and have facilitated phenotype-to-genotype correlation studies. As a result, the number of clinical trials targeting IRDs has steadily increased, and commensurate to this, the need for novel reproducible outcome measures and endpoints has grown. This review aims to summarize and describe the clinical presentation, characteristic imaging findings, and imaging endpoint measures that are being used in clinical research on IRDs. For the purpose of this review, IRDs have been divided into four categories: (1) panretinal pigmentary retinopathies affecting rods or cones; (2) macular dystrophies; (3) stationary conditions; (4) hereditary vitreoretinopathies. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the present study was to evaluate the outcomes of subretinal tissue plasminogen activator (r-tPA) injection with pars plana vitrectomy (PPV) in patients with submacular hemorrhage (SMH) extending towards the fovea. Materials and Methods: The study included 10 eyes of 10 patients who underwent subretinal r-tPA injection with 23 G PPV due to SMH extending towards the fovea. Following standard 23 G PPV, r-tPA (Actilyse, 10 mg/mL, Boehringer-Ingelheim, Germany) at a concentration of 25 µg/0.1 ml was injected into the subretinal space with a 41 G needle at a concentration of 0.2-0.3 ml. Subsequently, fluid-air-12% C3F8 exchange was performed and intravitreal 1.25 mg bevacizumab was administered. After surgery, the patient was given appropriate head position according to the bleeding site. Results: The mean age of the patients was 73.9 ± 4.7 years, 4 (40%) were male and 6 (60%) were female. Two patients (20%) developed SMH due to retinal macroaneurysm rupture, while choroidal neovascular membrane was the cause of hemorrhage in 8 patients (80%). Best corrected visual acuity was 2.53 ± 0.49 logMAR preoperatively, 1.28 ± 0.66 at one month, 1.08 ± 0.64 at three months and 1.04 ± 0.62 at six months postoperatively and the difference was significant (p<0.001 for each parameter). Conclusions: In patients with submacular hemorrhage, r-tPA administered subretinally provides significant visual acuity improvement without serious complications. [ABSTRACT FROM AUTHOR]

Retinal degenerative diseases, including age-related macular degeneration and retinitis pigmentosa, significantly contribute to adult blindness. The Royal College of Surgeons (RCS) rat is a well-established disease model for studying these dystrophies; however, molecular investigations remain limited. We conducted a comprehensive analysis of retinal degeneration in RCS rats, including an immunodeficient RCS (iRCS) sub-strain, using ocular coherence tomography, electroretinography, histology, and molecular dissection using transcriptomics and immunofluorescence. No significant differences in retinal degeneration progression were observed between the iRCS and immunocompetent RCS rats, suggesting a minimal role of adaptive immune responses in disease. Transcriptomic alterations were primarily in inflammatory signaling pathways, characterized by the strong upregulation of Tnfa, an inflammatory signaling molecule, and Nox1, a contributor to reactive oxygen species (ROS) generation. Additionally, a notable decrease in Alox15 expression was observed, pointing to a possible reduction in anti-inflammatory and pro-resolving lipid mediators. These findings were corroborated by immunostaining, which demonstrated increased photoreceptor lipid peroxidation (4HNE) and photoreceptor citrullination (CitH3) during retinal degeneration. Our work enhances the understanding of molecular changes associated with retinal degeneration in RCS rats and offers potential therapeutic targets within inflammatory and oxidative stress pathways for confirmatory research and development. [ABSTRACT FROM AUTHOR]

Recent advances have led to therapeutic options becoming available for people with inherited retinal disease. In particular, gene therapy has been shown to hold great promise for slowing vision loss from inherited retinal disease. Recent studies suggest that gene therapy is likely to be most effective when implemented early in the disease process, making consideration of paediatric populations important. It is therefore necessary to have a comprehensive understanding of retinal imaging in children with inherited retinal diseases, in order to monitor disease progression and to determine which early retinal biomarkers may be used as outcome measures in future clinical trials. In addition, as many optometrists will review children with an inherited retinal disease, an understanding of the expected imaging outcomes can improve clinical care. This review focuses on the most common imaging modality used in research assessment of paediatric inherited retinal diseases: optical coherence tomography. Optical coherence tomography findings can be used in both the clinical and research setting. In particular, the review discusses current knowledge of optical coherence tomography findings in eight paediatric inherited retinal diseases – Stargardt disease, Bests disease, Leber's congenital amaurosis, choroideremia, RPGR related retinitis pigmentosa, Usher syndrome, X-linked retinoschisis and, Batten disease. [ABSTRACT FROM AUTHOR]

Retinitis pigmentosa (RP) associated with biallelic variants in CDHR1 has rarely been reported, and detailed phenotyping data are not available. RP implies relative preservation of foveal cones, when compared to cone-rod dystrophy associated with biallelic null variants in CDHR1. We hypothesize that RP may occur in association with one or more hypomorphic CDHR1 alleles. Retrospective report of a 48-year-old patient with CDHR1-associated RP with a hypomorphic missense variant c.562 G>A, p. (Gly188Ser) and a novel, unreported variant affecting a canonical splice acceptor site (c.784–1 G>C). Clinical examination, multimodal retinal imaging, electroretinography, visual field testing, and mesopic microperimetry were undertaken 8 years apart. Scotopic microperimetry was also performed. The DNA sequence context of the variants was examined to identify theoretical CRISPR-Cas9 base-editing strategies. The patient presented at 35 years with a 12-year history of nyctalopia. His best corrected visual acuity was 20/20. Clinical presentation, multimodal retinal imaging studies, electroretinography, and mesopic microperimetry were typical of a progressive rod-cone dystrophy (i.e. classic RP). There were no scotomas within the central field as would be expected at this age in CDHR1-associated cone-rod dystrophy. Scotopic microperimetry suggested some preservation of macular cone over rod function, although both were severely impaired. A suitable CRISPR adenine base editor was identified that could theoretically correct the missense variant c.562 G>A, p. (Gly188Ser). CDHR1-associated RP shows a relative preservation of cone function in the presence of a presumed hypomorphic allele and may be considered a hypomorphic disease phenotype. Further work is required to identify modifying factors that determine disease phenotype since macular dystrophy, with relative sparing of rods, may also occur with hypomorphic CDHR1 alleles [ABSTRACT FROM AUTHOR]

Generally, the number of lenslets in Shack–Hartman wavefront sensor (SHWFS) determines its spatial sampling frequency. However, increasing the number of lenslets is limited by the data processing delay time and low sensitivity in the adaptive optics system. In this paper, a wavefront reconstruction method based on ASH-Net for SHWFS is presented to recover the distorted wavefront from the light spots array with high accuracy with a spatial sampling frequency than traditionally required. The results show that the maximum number of Zernike modes recovered by the method is 36, 54, and 70 for 4 × 4, 6 × 6, and 8 × 8 lenslets arrays, respectively. Residual wavefront root mean square values are as low as about 0.02 μ m, corresponding to a Strehl Ratio of 0.99. This method breaks the limitation that the number of reconstructed Zernike modes in the traditional wavefront reconstruction algorithm must be less than the number of effective lenslets. Experiments in lab are used to validate the method. Additionally, fewer lenslets is valuable to improve the detection capability of SHWFS for faint targets. This is important for applications of adaptive optics in areas such as astronomy and retinal imaging. [ABSTRACT FROM AUTHOR]

The Retinal Pigment Epithelium (RPE) plays a prominent role in diseases such as age-related macular degeneration, but imaging individual RPE cells is challenging due to their high absorption and low autofluorescence emission. The RPE lies beneath the highly reflective photoreceptor layer (PR) and contains absorptive pigments, preventing direct backscattered light detection when the PR layer is intact. Here, we used near-infrared autofluorescence adaptive optics scanning laser ophthalmoscopy (NIRAF AOSLO) and transscleral flood imaging (TFI) in the same healthy eyes to cross-validate these approaches. Both methods revealed a consistent RPE mosaic pattern and appeared to reflect a distribution of fluorophores consistent with findings from histological studies. Interestingly, even in apparently healthy RPE, we observed dynamic changes over months, suggesting ongoing cellular activity or alterations in fluorophore distribution. These findings emphasize the value of NIRAF AOSLO and TFI in understanding RPE morphology and dynamics. [ABSTRACT FROM AUTHOR]

The early diagnosis of diabetic retinopathy (DR) can effectively prevent irreversible vision loss and assist ophthalmologists in providing timely and accurate treatment plans. However, the existing methods based on deep learning have a weak perception ability of different scale information in retinal fundus images, and the segmentation capability of subtle lesions is also insufficient. This paper aims to address these issues and proposes MLNet for DR lesion segmentation, which mainly consists of the Multi-Scale Attention Block (MSAB) and the Lesion Perception Block (LPB). The MSAB is designed to capture multi-scale lesion features in fundus images, while the LPB perceives subtle lesions in depth. In addition, a novel loss function with tailored lesion weight is designed to reduce the influence of imbalanced datasets on the algorithm. The performance comparison between MLNet and other state-of-the-art methods is carried out in the DDR dataset and DIARETDB1 dataset, and MLNet achieves the best results of 51.81% mAUPR, 49.85% mDice, and 37.19% mIoU in the DDR dataset, and 67.16% mAUPR and 61.82% mDice in the DIARETDB1 dataset. The generalization experiment of MLNet in the IDRiD dataset achieves 59.54% mAUPR, which is the best among other methods. The results show that MLNet has outstanding DR lesion segmentation ability. [ABSTRACT FROM AUTHOR]