Search Results (1,513)

Background: Retinal and optic nerve disorders are a leading cause of irreversible visual impairment worldwide. Advances in molecular genetics—including next-generation sequencing, genome-wide association studies, and gene-based therapeutic technologies—have reshaped understanding of both inherited and complex retinal diseases. However, translating genetic discovery into sustained clinical benefit remains biologically and practically constrained. Methods: A structured literature search was conducted using PubMed and Scopus to identify relevant studies published between 2015 and 2025. The search focused on molecular genetics, epigenetic modulation, mitochondrial biology, and translational applications in inherited retinal dystrophies and selected complex retinal diseases, prioritizing high-impact original research and systematic reviews addressing diagnostic innovation and therapeutic development. Results: Inherited retinal dystrophies represent the most advanced model of precision ophthalmology, with diagnostic yields approaching 70–80% in well-characterized cohorts. Gene augmentation and genome-editing strategies have demonstrated proof-of-concept efficacy, yet clinical benefit depends on residual cellular viability, delivery efficiency, and durability of expression. Emerging platforms include AAV-mediated gene transfer, in vivo CRISPR-based editing, RNA-directed splice modulation, and mitochondrial-targeted approaches. Persistent barriers include unresolved non-coding and structural variants, variant interpretation uncertainty, and endpoint selection in clinical trials. In contrast, complex retinal diseases such as glaucoma, age-related macular degeneration, and pathological myopia reflect polygenic susceptibility interacting with environmental and aging-related factors. Although polygenic risk scores refine probabilistic prediction, their utility is limited by ancestry bias and incomplete predictive performance. Epigenetic and mitochondrial mechanisms further modulate disease expression but remain largely non-actionable in routine practice. Conclusions: Retinal genetics has progressed from gene discovery to early therapeutic implementation. Future advances will depend on improved variant detection, functional validation, biomarker-guided staging, and integration of genomics with imaging and longitudinal modeling to achieve durable and equitable precision ophthalmology. Full article

From falcons spotting prey to humans recognizing faces, the ability to rapidly process visual information depends on a foveated retinal organization that provides high-acuity central vision while preserving low-resolution peripheral vision. This organization is conserved along early visual pathways, yet remains under-explored in machine learning. Here, we examine the impact of embedding a foveated retinotopic transformation as a preprocessing layer on convolutional neural networks (CNNs) for image classification. By applying a log-polar mapping to off-the-shelf models and retraining them, we achieve comparable accuracy while improving robustness to scale and rotation. We demonstrate that this architecture is highly sensitive to shifts in the fixation point and that this sensitivity provides an effective proxy for defining saliency maps that facilitate object localization. Our results demonstrate that foveated retinotopy encodes prior geometric knowledge, providing a solution for visual searches and a meaningful classification robustness and localization trade-off. These findings provides a proof of concept in order to connect principles of biological vision with artificial networks, suggesting new, robust and efficient approaches for computer vision systems. Full article

The management of multiple sclerosis (MS) is shifting from a phenotype-based framework toward a biologically driven precision medicine model, as conventional magnetic resonance imaging (MRI) inadequately captures smoldering inflammation and progression independent of relapse activity (PIRA). This systematic review aimed to synthesize current evidence on the diagnostic and prognostic utility of fluid biomarkers in distinguishing acute inflammatory injury from chronic neurodegeneration. A comprehensive search of Web of Science, PubMed, and Scopus (January 2020–September 2025) identified 28 eligible studies including 7775 participants (6365 MS patients and 1410 controls). Biomarkers derived from serum, plasma, cerebrospinal fluid (CSF), and stool were evaluated in relation to clinical disability measured using the Expanded Disability Status Scale (EDSS) and magnetic resonance imaging (MRI) outcomes. Neurofilament light chain (NfL) consistently predicted acute inflammatory activity, gadolinium-enhancing lesions, and relapse-associated worsening, but levels were reduced by high-efficacy therapies and did not reliably predict PIRA. In contrast, glial fibrillary acidic protein (GFAP) was associated with astrogliosis, disability progression, and retinal thinning, even in patients with low inflammatory activity. Additional CSF, metabolic, and immunologic markers correlated with neurodegeneration and disease severity. Nevertheless, broader clinical use will require greater assay standardization, improved consistency across cohorts, and validation in prospective longitudinal studies. These findings compel a shift toward a multi-biomarker model to guide personalized therapeutic strategies and develop targeted neuroprotective treatments for progressive multiple sclerosis. Full article

Introduction: Optical coherence tomography (OCT) is the gold standard for retinal nerve fibre layer (RNFL) assessment; its high cost and limited accessibility hinder widespread use. This study aims to develop deep learning models that generate RNFL thickness maps from fundus images, providing a cost-effective alternative to OCT. Methods: A dataset of 5000 fundus-OCT image pairs from 5000 unique glaucoma patients was used to train and compare the following four U-Net-based deep learning models: ResU-Net, R2U-Net, Nested U-Net, and Dense U-Net. All models were trained for up to 1000 epochs with early stopping (patience = 50 epochs). Performance was evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Fréchet Inception Distance (FID). Results: ResU-Net demonstrated the best performance, achieving MSE = 0.00061, MAE = 0.01877, SSIM = 0.9163, PSNR = 32.19 dB, and FID = 30.08. These results represent a 108% improvement in SSIM and a 67% improvement in PSNR compared to previously published benchmark for this task. Conclusions: This study demonstrates that deep learning models, particularly ResU-Net, can generate high-fidelity RNFL thickness maps from fundus photographs, substantially outperforming prior published benchmarks. This approach represents a potential contribution toward accessible glaucoma assessment, contingent upon prospective clinical validation and regulatory evaluation. Full article

Irreversible anterior segment blindness with preserved retinal integrity (e.g., dense corneal opacity) remains a major clinical challenge because effective sight-restoring options are limited. Here, we describe an intraocular micro-light-emitting diode (Micro-LED) epiretinal microdisplay intended to deliver patterned optical stimulation to intact photoreceptors by bypassing opaque anterior optics. The prototype was based on a color-capable VGA microdisplay (640 × 480 pixels) and operated at <30 mW under typical conditions. An ultra-thin flexible cable and a copper-mesh–reinforced polydimethylsiloxane (PDMS) encapsulation provided a compact, conformable intraocular package with high pixel density. We evaluated a monochromatic (green) prototype in a single beagle eye $(n=1)$ using a transscleral implantation approach and performed 7 days of postoperative follow-up with slit-lamp examination and multimodal imaging. Patterned stimulation via the implanted display elicited flash-evoked visual evoked potentials (VEPs) with consistent within-session waveform morphology, providing preliminary neurophysiological surrogate evidence of upstream visual pathway activation under the tested conditions in this single-animal pilot. The short-term postoperative course included transient hypotony and anterior segment inflammation, and implant rotation with associated inferior retinal detachment was observed by day 7, highlighting current biomechanical limitations. Beyond anterior segment opacity, the same intraocular optical interface could be explored as a modular light-delivery platform to pair with emerging retinal therapies (e.g., optogenetics), pending chronic safety and functional validation. This pilot large-animal study therefore provides a translationally relevant testbed while delineating key engineering constraints that must be addressed next. Full article

To perform screening of the retina on a population scale, an automated procedure is required that incorporates accurate, reproducible, interpretable, and computationally costeffective models. Existing approaches using convolutional or transformer architectures typically do not adequately represent both fine-grained pathology and large-scale retinal context simultaneously, which could adversely affect their reliability if used for large-scale applications in clinical practice. In this paper, we propose a hierarchical transformer-based screening framework for retinal fundus images that incorporates patch-based tokenization, global transformer encoding, and hierarchical aggregation of contextual information. We also developed a lightweight prediction head that supports screening for both single and multiple diseases. The framework has been evaluated using standard screening metrics, robustness, and cross-dataset generalization analyses on two eye retinopathy image databases: EyePACS and RFMiD. With regard to screening for a binary outcome of diabetic retinopathy, our method provided an accuracy of 89.4% and an area under the receiver operating characteristic (AUROC) curve of 93.6% on EyePACS and attained an accuracy of 95.2% and a macro-averaged F1 score of 82.7% on RFMiD. Our hierarchical transformer achieved improved robustness to degraded images and increased generalizability across datasets compared with all current state-of-the-art models. The proposed hierarchical transformer demonstrates strong potential for large-scale retinal screening and provides a promising foundation for future clinically validated deployment. Full article

Ocular Color Doppler ultrasound (OCDUS) has been underutilized in the past as a diagnostic technique, although several OCDUS-based studies were performed in the last 30 years for diagnosis or monitoring of some ophthalmological, cerebrovascular or systemic diseases. OCDUS can provide quantitative and reproducible measurements of the blood flow of the main orbital vessels at the retrobulbar level. In this narrative review we aimed to investigate the relevance of OCDUS as an imaging modality in several ophthalmological, cerebrovascular and systemic diseases based on the current literature. Full article

This review critically synthesizes current evidence regarding the natural history, advanced diagnostic imaging, and therapeutic interventions for acquired retinoschisis and retinoschisis-associated retinal detachment. A systematic search of PubMed and Embase databases was conducted for literature published up to 2026, focusing on comparative outcomes of scleral buckling versus pars plana vitrectomy and novel imaging modalities. The advent of ultra-widefield optical coherence tomography has shifted the diagnostic paradigm, enabling the precise identification of outer layer breaks as the primary biomarkers for progression. While observation is mandated for asymptomatic, non-progressive cases, the choice between buckling and vitrectomy for active detachments is often driven by surgeon preference rather than anatomical necessity. We propose an updated decision-making algorithm that integrates lens status, break localization, and vitreous findings to guide the surgical approach. Moving beyond a “one-size-fits-all” strategy, this review advocates for a personalized management plan that balances anatomical success with long-term quality of life. Full article

Craniopharyngioma (CP) is a rare benign tumor of the sellar and suprasellar region that often compresses the optic pathways, causing significant visual impairment in both children and adults. The early detection and monitoring of optic nerve involvement are essential for preserving visual function. Optical coherence tomography (OCT) and OCT angiography (OCTA) are noninvasive, high-resolution imaging modalities that provide quantitative assessment of retinal nerve fiber layer (RNFL) thickness, ganglion cell complex (GCC), and retinal microvasculature. Thinning of the RNFL and GCC correlates with visual field defects and reduced visual acuity and may also serve as a predictor of postoperative visual recovery. OCTA reveals microvascular alterations that may precede structural damage and, together with other imaging parameters, can be used to estimate the likelihood of visual improvement after neurosurgery. This review summarizes current evidence on the use of OCT and OCTA in CP, highlighting their applications in assessment of optic pathway involvement, preoperative evaluation, postoperative monitoring, and risk stratification. Based on our clinical experience, we propose a table with recommended OCT parameters and follow-up intervals. Importantly, OCT should be interpreted alongside the visual acuity, visual field testing, and fundus examination for comprehensive assessment. Future directions include the standardization of imaging protocols and prospective multicenter studies, and integration of OCTA metrics into predictive models of visual outcomes. OCT and OCTA provide objective, reproducible biomarkers that support individualized patient care and may improve visual prognosis in CP. Full article

Background/Objectives: Optical coherence tomography angiography (OCTA) enables noninvasive quantitative assessment of the retinal microvasculature and is widely used in diabetic retinopathy (DR). However, OCTA-derived metrics are highly dependent on post-processing techniques, particularly vessel binarization. This study aimed to compare local and global binarization methods applied after Frangi filtering for vessel enhancement in parafoveal vessel density analysis. Methods: This cross-sectional study included 69 participants: 17 healthy controls and 52 diabetic patients, classified as the following: no DR (n = 14), non-proliferative DR (NPDR, n = 18), or proliferative DR (PDR, n = 20). All subjects underwent comprehensive ophthalmological examination and OCTA imaging of the superficial capillary plexus using a Topcon OCTA system. Images were processed using a custom MATLAB protocol. Following Frangi filtering, five binarization methods were applied: three local (Phansalkar, local Otsu, adaptive mean) and two global (global mean and global Otsu). Parafoveal vessel density was quantified within the four inner quadrants of the ETDRS grid. Results: Statistically significant differences in vessel density were consistently observed between PDR group and both the control and no DR groups across all local binarization methods. Among global methods, only global Otsu thresholding detected a significant difference between PDR and control. The most robust differences were predominantly identified in the nasal and inferior quadrants. Conclusions: Local adaptive binarization methods demonstrated superior sensitivity and structural preservation for parafoveal vessel density analysis in DR. Global methods showed limited discriminative capability. These findings support the preferential use of local adaptive techniques for reliable OCTA-based vascular assessment in diabetic retinopathy. Full article

Background: Diabetic retinopathy (DR) is a leading cause of vision loss worldwide. Microvascular changes precede clinically detectable DR, creating an opportunity for early diagnosis and intervention. Optical coherence tomography angiography (OCTA) enables noninvasive, quantitative assessments of retinal and choroidal microcirculation and has emerged as a promising tool for identifying early biomarkers of DR. The goal of this study was to review the literature on OCTA-derived biomarkers associated with preclinical diabetic retinopathy in patients with type 1 and type 2 diabetes mellitus. Methods: This descriptive literature review summarizes current evidence regarding OCTA-derived biomarkers associated with preclinical diabetic retinopathy in patients with type 1 and type 2 diabetes mellitus. A search of the PubMed/MEDLINE database was performed to identify original studies published between 2015 and 2025 evaluating OCTA parameters in diabetic patients without clinically detectable diabetic retinopathy. The findings were synthesized qualitatively due to methodological heterogeneity among studies in terms of OCTA devices, imaging protocols, and analyzed parameters. Results: The reviewed studies consistently reported early microvascular abnormalities detectable by OCTA prior to the development of clinically visible diabetic retinopathy. The most frequently described changes included reduced vessel density (VD) and perfusion parameters, enlargement and increased irregularity of the foveal avascular zone (FAZ), areas of capillary non-perfusion, and alterations in vascular network geometry and complexity. These changes were most consistently observed in the deep capillary plexus (DCP), suggesting that this vascular layer may be particularly susceptible to early diabetic microvascular damage. Conclusions: This review provides a comprehensive synthesis of OCTA-derived biomarkers associated with early retinal microvascular alterations in diabetic patients without clinically detectable diabetic retinopathy. By integrating findings from recent studies, the review highlights the potential role of OCTA in identifying preclinical microvascular changes and discusses current methodological challenges and future research directions. Full article

Background/Objectives: Hyperreflective foci (HRF) are supportive optical coherence tomography (OCT) imaging biomarkers that have been examined for their association with disease progression and severity in various retinal disorders. The accurate identification and segmentation of these tiny structures of lipid extravasation remain complicated because of their small size, class imbalance, similarity in the reflectivity patterns with the surrounding structures and imaging artifacts. While U-Net-based models have promised exceptional results for medical image segmentation, optimal architectural settings and suitable preprocessing methods for HRF detection remain unclear. Methods: This research assessed optimal settings for U-Net-based models for HRF segmentation by evaluating standard U-Net and attention U-Net under different preprocessing regimes. Attention U-Net employed Z-score normalization and contrast-limited adaptive histogram equalization (CLAHE) enhancement with soft dice loss. The standard U-Net was trained on OCT images with CLAHE using focal Tversky loss. A total of 435 fovea-centered OCT B scans with the corresponding, consensus-annotated HRF masks were utilized for this research. Results: The standard U-Net outperformed attention U-Net with a dice score of 0.5207, an AUC of 0.8411, and a recall of 0.6439 on raw OCT images. The attention U-Net with preprocessing (dice: 0.5033, AUC: 0.6987, recall: 0.5391) demonstrated satisfactory performance. The results showed that the U-Net model with CLAHE and focal Tversky loss improved recall by 19.4% relative to the attention U-Net, and this corresponds roughly to a 23% relative decline in false negatives. This indicates increased sensitivity in identifying HRF regions. Conclusions: The best-performing configuration using U-Net-based architectures for segmentation of HRFs combines the standard U-Net model with CLAHE and focal Tversky loss for handling class imbalance. This approach yields relatively higher sensitivity, indicating that the standard U-Net model delivers a simple and robust framework for automated HRF segmentation on the evaluated dataset, promising further validation in broader clinical datasets. Full article

Background/Objectives: Rosacea is a chronic inflammatory dermatosis that may involve the eye, causing surface and adnexal damage that can precede cutaneous signs. Detecting subclinical ocular changes is clinically important because early ocular surface dysfunction may be missed on routine examination yet progress to corneal complications, allowing earlier preventive management when identified. We prospectively evaluated subclinical ocular alterations in cutaneous rosacea using a combined, fully non-invasive high-tech imaging workflow—tear film interferometry, infrared meibography, and exploratory retinal optical coherence tomography angiography (OCT-A)—including patients without clinically evident ocular involvement. Methods: Sixteen patients with cutaneous rosacea (mean age 44.3 ± 11.2 years; 4 males, 12 females) were enrolled and divided into: Group 1—rosacea with clinically evident ocular involvement (n = 11); Group 2—rosacea without clinical ocular involvement (n = 5). Six age-matched healthy subjects served as controls (Group 3). All underwent LipiView II^® interferometry and meibography to quantify lipid-layer thickness (LLT, nm) and meibomian gland (MG) loss score (1 = normal–4 = severe), plus retinal OCT-A (Optovue Inc., Fremont, CA, USA). ANOVA with post hoc Tukey test assessed inter-group differences. Results: OCT-A showed no significant alterations in superficial or deep retinal plexuses across groups (p > 0.05). Conversely, LLT was significantly reduced in both rosacea groups vs. controls (OD: 45.5 ± 21.4 nm and 67.4 ± 10.1 nm vs. 92.7 ± 8.2 nm; OS: 40.4 ± 15.3 nm and 66.4 ± 10.1 nm vs. 96.0 ± 6.7 nm; p < 0.001). MG score was markedly higher (worse) in rosacea (OD: 3.63 ± 0.50 and 3.20 ± 0.83 vs. 1.83 ± 0.75; OS: 3.45 ± 0.68 and 3.40 ± 0.54 vs. 1.66 ± 0.81; p < 0.001). Ocular symptoms were reported by 85% of patients yet slit-lamp examination revealed surface alterations in 58% of asymptomatic cases. Conclusions: Tear film interferometry and meibography detect early ocular surface impairment in rosacea—even in the absence of clinical signs—while retinal microvasculature appears unaffected. Routine ophthalmologic screening of all rosacea patients could enable prompt treatment of subclinical dysfunction, potentially preventing corneal complications. Retinal OCTA metrics were not significantly different in this small pilot cohort, and these negative findings should be interpreted cautiously pending larger studies. Full article

Background: The eye has shown potential as a reliable, readily accessible and clinically relevant site for investigating patients with multiple sclerosis (pwMS). Optical coherence tomography angiography (OCTA) shows promise in revealing new metabolic and vascular elements driving multiple sclerosis (MS) disease pathology. This study aimed to explore correlations between OCTA parameters and clinical characteristics in newly diagnosed relapsing–remitting MS (RRMS) patients. Methods: In this cross-sectional study, forty-one newly diagnosed RRMS patients underwent comprehensive evaluations, including neurological examinations, functional and cognitive tests (9-Hole Peg Test, Montreal Cognitive Assessment), and OCT/OCTA scans. Multiple regression analyses assessed correlations between OCT/OCTA parameters and baseline clinical characteristics. Results: Lower superficial capillary plexus (SCP) vessel density was associated with longer disease duration, higher EDSS scores (visual, pyramidal, cerebellar, ambulation), and impaired 9-Hole Peg Test performance, especially in the non-dominant hand. Higher values of choriocapillaris (CC) flow voids correlated with worse cognitive performance (MoCA). Structural OCT parameters showed limited clinical correlations. Conclusions: OCTA-derived parameters are associated with disability, fine motor function, and cognitive performance in newly diagnosed RRMS patients without prior ON. These findings suggest that retinal vascular alterations may reflect early neurodegenerative processes and provide complementary information beyond structural OCT metrics. OCTA may represent a sensitive, non-invasive imaging biomarker for patient assessment in early MS. Full article

Background: Mixed connective tissue disease (MCTD) is a rare systemic autoimmune disease which presents with clinical features that overlap with at least two connective tissue disorders, including systemic lupus erythematosus (SLE), systemic sclerosis (SSc), polymyositis (PM), dermatomyositis (DM), and rheumatoid arthritis (RA). It is characterized by the presence of anti-ribonucleoprotein (anti-U1RNP) antibodies. The mechanism of the vasculopathy associated with MCTD remains largely unknown. Optical coherence tomography angiography (OCTA) is a non-invasive imaging method of the microvasculature of the retina and choroid, providing the assessment of retinal perfusion. Objectives: The aim of the study was to evaluate the optical coherence tomography angiography (OCTA) parameters in patients with mixed connective tissue disease compared to healthy individuals. Methods: In this study, we compared the following parameters between patients with MCTD and healthy subjects: foveal avascular zone (FAZ), FAZ perimeter (PERIM), flow density (FD), choriocapillaris flow area (CCFA), outer retina flow area (ORFA), and foveal and parafoveal mean superficial and deep vessel density. Results: Parafoveal mean superficial vessel density and parafoveal mean deep vessel density were significantly lower in the MCTD group than in controls. The FAZ, FAZ PERIM, and FD values in the patients with MCTD were lower than in the control group and statistically significant for all parameters. Conclusions: The present study’s findings suggest the presence of ocular vascular abnormalities in patients suffering from MCTD. These abnormalities are characterized by decreased retinal vessel density and lower choriocapillaris flow. The results of the study demonstrate the significant role of OCTA in the diagnosis and monitoring of microvascular changes in patients with MCTD. Full article