Search Results (205)

Background/Objectives: Retinal optical coherence tomography (OCT) is essential for diagnosing ocular diseases, yet developing high-performing multiclass classifiers remains challenging due to limited labeled data and the computational cost of self-supervised pretraining. This study aims to address these limitations by introducing a curriculum-based self-supervised framework to improve representation learning and reduce computational burden for OCT classification. Methods: Two ensemble strategies were developed using progressive masked autoencoder (MAE) pretraining. We refer to this curriculum-based MAE framework as CurriMAE (curriculum-based masked autoencoder). CurriMAE-Soup merges multiple curriculum-aware pretrained checkpoints using weight averaging, producing a single model for fine-tuning and inference. CurriMAE-Greedy selects top-performing fine-tuned models from different pretraining stages and ensembles their predictions. Both approaches rely on one curriculum-guided MAE pretraining run, avoiding repeated training with fixed masking ratios. Experiments were conducted on two publicly available retinal OCT datasets, the Kermany dataset for self-supervised pretraining and the OCTDL dataset for downstream evaluation. The OCTDL dataset comprises seven clinically relevant retinal classes, including normal retina, age-related macular degeneration (AMD), diabetic macular edema (DME), epiretinal membrane (ERM), retinal vein occlusion (RVO), retinal artery occlusion (RAO), and vitreomacular interface disease (VID) and the proposed methods were compared against standard MAE variants and supervised baselines including ResNet-34 and ViT-S. Results: Both CurriMAE methods outperformed standard MAE models and supervised baselines. CurriMAE-Greedy achieved the highest performance with an area under the receiver operating characteristic curve (AUC) of 0.995 and accuracy of 93.32%, while CurriMAE-Soup provided competitive accuracy with substantially lower inference complexity. Compared with MAE models trained at fixed masking ratios, the proposed methods improved accuracy while requiring fewer pretraining runs and reduced model storage for inference. Conclusions: The proposed curriculum-based self-supervised ensemble framework offers an effective and resource-efficient solution for multiclass retinal OCT classification. By integrating progressive masking with snapshot-based model fusion, CurriMAE methods provide high performance with reduced computational cost, supporting their potential for real-world ophthalmic imaging applications where labeled data and computational resources are limited. Full article

Eye tracking (ET) technology is increasingly used in both research and clinical practice, but its accuracy may be compromised by the presence of ophthalmic lenses. This study systematically evaluated the influence of different optical prescriptions and lens treatments on ET performance using DIVE (Device for an Integral Visual Examination). Fourteen healthy participants underwent oculomotor control tests under thirteen optical conditions: six with varying dioptric powers and six with optical filters, compared against a no-lens control. Key parameters analysed included angle error, fixation stability (bivariate contour ellipse area, BCEA), saccadic accuracy, number of data gaps, and proportion of valid frames. High-powered spherical lenses (+6.00 D and −6.00 D) significantly increased gaze angle error, and the negative lens also increased data gaps, while cylindrical lenses had a moderate effect. Among filters, the Natural IR coating caused the greatest deterioration in ET performance, reducing valid samples and increasing the number of gaps with data loss, likely due to interference with the infrared-based detection system. The lens with basic anti-reflective treatment (SV Org 1.5 AR) also showed some deterioration in interaction with the ET. Other filters showed minimal or no significant impact. These findings demonstrate that both high-powered prescriptions and certain lens treatments can compromise ET data quality, highlighting the importance of accounting for optical conditions in experimental design and clinical applications. Full article

Background/Objectives: Octenidine dihydrochloride (OCT-D) is a broad-spectrum antiseptic with high chemical stability, low toxicity, and no reported microbial resistance, making it a strong candidate for use on mucosal surfaces. Despite increasing interest in its potential ophthalmic applications, limited data exist regarding its cellular effects on ocular tissues. This study aimed to investigate the cytotoxic, apoptotic, inflammatory, and transcriptional responses induced by OCT-D in human conjunctival (IOBA-NHC) and retinal pigment epithelial (ARPE-19) cells. Methods: Cells were exposed to varying concentrations of OCT-D, and viability was assessed using the WST-1 assay to determine IC₅₀ and IC₅₀/2 values. These concentrations were subsequently used in molecular assays. Pro-inflammatory cytokines (IL-6, IL-1β, TNF-α, IFN-γ) were quantified by ELISA. Apoptotic activation was evaluated through caspase-3/7 activity assays. Gene expression analysis of apoptotic (Bax, Bcl-2), DNA damage-related (ATM, Rad51), and inflammatory markers was performed using RT-qPCR. Results: OCT-D induced a marked, dose-dependent reduction in cell viability in both cell lines, with ARPE-19 showing greater sensitivity. Caspase-3/7 activity increased significantly at IC₅₀ and IC₅₀/2, confirming intrinsic apoptotic activation. OCT-D markedly suppressed the release of key inflammatory cytokines and downregulated transcription of inflammatory genes. RT-qPCR revealed upregulation of pro-apoptotic and DNA damage-associated genes, demonstrating coordinated activation of apoptotic and genomic stress pathways. Conclusion: OCT-D triggers integrated cytotoxic, apoptotic, and immunomodulatory responses in conjunctival and retinal epithelial cells. While these findings provide important mechanistic insights into OCT-D’s cellular effects, further studies using primary cells, advanced 3D ocular models, and disease-relevant systems are required to support its potential translational use in ophthalmology. Full article

The development of advanced biomaterials for corneal applications requires robust translational platforms that faithfully replicate human characteristics. Porcine corneas are increasingly recognized for ophthalmic research. Their unique combination of anatomical similarity, biomechanical comparability, and accessibility make them highly suitable for preclinical evaluation of innovative therapies, bridging the gap between preclinical discovery and clinical application. This review outlines the utility of porcine corneal models in validating advanced biomaterials, particularly in ex vivo settings, focusing on current methodologies, while addressing challenges and future directions. We aim to underscore the potential of porcine corneal models to accelerate the translation of next-generation biomaterials into clinically relevant corneal therapies. Full article

Diabetic retinopathy (DR) and diabetic macular edema (DME) remain major causes of vision loss among working-age adults. Artificial intelligence (AI), particularly deep learning, has gained attention in ophthalmic imaging, offering opportunities to improve both diagnostic accuracy and efficiency. This review examined applications of AI in DR and DME published between 2010 and 2025. A narrative search of PubMed and Google Scholar identified English-language, peer-reviewed studies, with additional screening of reference lists. Eligible articles evaluated AI algorithms for detection, classification, prognosis, or treatment monitoring, with study selection guided by PRISMA 2020. Of 300 records screened, 60 met the inclusion criteria. Most reported strong diagnostic performance, with sensitivities up to 96% and specificities up to 98% for detecting referable DR on fundus photographs. Algorithms trained on optical coherence tomography (OCT) data showed high accuracy for identifying DME, with area under the receiver operating characteristic curve (AUC) values frequently exceeding 0.90. Several models also predicted anti-vascular endothelial growth factor (anti-VEGF) treatment response and recurrence of fluid with encouraging results. Autonomous AI tools have gained regulatory approval and have been implemented in clinical practice, though performance can vary depending on image quality, device differences, and patient populations. Overall, AI demonstrates strong potential to improve screening, diagnostic consistency, and personalized care, but broader validation and system-level integration remain necessary. Full article

This study investigates the compatibility of various acrylic and silane monomers and aims to develop a high-performance hydrogel ophthalmic polymer. The formulations incorporated 2-(trimethylsiloxy)ethyl methacrylate (2TSEMA), 3-(methacryloxy)propyl tris(trimethylsiloxy)silane (3TRIS), and (1,1-dimethyl-2-propyl)oxy-trimethylsilane (TRIS) as functional additives to a base composition of silanol-terminated silicone (Sil-OH), N,N–dimethyl acrylamide (DMA), methyl methacrylate (MMA), and methyl acrylate (MA). Copolymerization was carried out using ethylene glycol dimethacrylate (EGDMA) as the crosslinking agent and azobisisobutyronitrile (AIBN) as the thermal initiator. All synthesized hydrogel lenses exhibited excellent optical transparency, indicating good monomer compatibility. The optical and physicochemical properties of the hydrogels varied depending on monomer composition. Notably, the formulation combining 2TSEMA with 1 wt% TRIS showed enhanced oxygen permeability, suggesting a synergistic interaction between the two silane-based components. These results demonstrate the potential of such hybrid formulations for use in next-generation functional hydrogel ophthalmic lenses. Full article

Introduction: Inherited retinal dystrophies (IRDs) are genetically determined conditions leading to progressive vision loss. Developments in gene therapy are creating new treatment options for IRD, but require precise imaging diagnosis and monitoring. According to recent studies, artificial intelligence, especially deep neural networks, could become an important tool for analyzing imaging data. Material and Methods: A systematic literature review was conducted in accordance with PRISMA guidelines, using PubMed, Scopus, and Web of Science databases to identify publications from 2015 to 2025 on the application of artificial intelligence in diagnosing inherited retinal dystrophies and monitoring the effects of gene therapy. The included articles passed a two-stage selection process and met the methodological quality criteria. Results: Among all the included studies it can be noticed that the use of artificial intelligence in diagnostics and therapy of IRDs is rather effective. The most common method was deep learning with its subtype convolutional neural networks (CNNs). However, there is still a place for improvement due to various limitations occurring in the studies. Conclusions: The review points to the growing potential of AI models in optimizing the diagnostic and therapeutic pathway in IRDs, while noting current limitations such as low data availability, the need for clinical validation, and the interpretability of the models. AI may play a key role in personalized ophthalmic medicine in the near future, supporting both clinical decisions and interventional study design. Full article

Ophthalmic surgery requires micrometer-level precision due to the eye’s delicate anatomy, yet manual limitations and restricted 3D visualization make absolute accuracy challenging, driving interest in robotic and Artificial Intelligence technologies to enhance safety and precision. This is a narrative review of experimental and published studies on PubMed and Open Evidence to review the current advances, challenges, and translational potential of robotic-assisted needle insertion in corneal surgery. Topics include robotic corneal surgery platforms such as the da Vinci and custom microsurgical robots, telemanipulation, intraoperative optical coherence tomography (iOCT), and reinforcement learning applications. Recent advancements in the field have demonstrated enhanced needle insertion precision, tremor elimination, and improved visualization of needle trajectory in corneal procedures, including corneal lacerations, pterygium repairs and penetrating keratoplasties (PKs). Nonetheless, significant limitations in the state of the art persist, particularly concerning the integration of robotic systems into clinical practice in in vivo settings. Our results indicate that current studies are mostly conducted in an ex vivo setting, which introduces inherent biases and reduces the generalizability of findings to clinical practice. Additionally, the majority of these studies involve small sample sizes, limiting statistical power and the ability to draw robust conclusions. Together, these limitations highlight the need for larger, well-designed in vivo studies to validate and expand upon existing findings. This review bridges experimental innovation and clinical application, highlighting strategies to overcome current barriers in robotic corneal surgery. Full article

Background: Hypochlorous acid (HOCl) is an integral component of the human innate immune system. It possesses antimicrobial properties and is available in solution, dermal spray, and scar gel forms. Objectives/Methods: This review presents data from studies on the clinical use of HOCl in various specialties, including dermatology, surgery, dentistry, ophthalmology, and rhinology. Results: Due to its anti-inflammatory/antimicrobial/immunomodulatory and healing properties, HOCl is advantageous in treating various skin disorders: ulcus cruris (and wound care), diabetic ulcers, atopic dermatitis, seborrheic dermatitis, pruritus, acne vulgaris, etc. Also, the application of a HOCl spray/gel after surgical procedures may prevent infection, reduce inflammation, and accelerate healing. HOCl is also effective and safe for the prevention and treatment of hypertrophic and keloid scars. Growing evidence shows a broader role for HOCl in limiting cancer cell survival and slowing tumor growth. It is also important in treating various viral infections like SARS-CoV-2 (coronavirus), influenza, and herpes, thereby helping to prevent the spread of aerosols. In addition, since HOCl is an endogenous compound naturally present in mammals with a high safety profile, it may be an effective bacterial disinfectant in dental waterlines. In ophthalmology, adjuvant treatment with HOCl ophthalmic spray can reduce the duration of antibiotic/corticosteroid use, even in severe blepharitis. To fully harness the protective/therapeutic properties of HOCl, future advancements will rely on the development of new chemical compounds and sophisticated pharmaceutical formulations. Conclusions: The majority of clinical studies have confirmed that HOC1 is useful in therapy, although the results are not entirely consistent. Further research is essential to optimize HOCl dosing and to develop controlled-release systems aimed at maximizing its anti-inflammatory and photoprotective effects while minimizing tissue irritation and damage. Full article

Optical coherence tomography (OCT) is a non-invasive imaging tool that is currently used in the evaluation and management of neuro-ophthalmic disorders. The detailed ability to visualize the optic nerve head, peripapillary retinal nerve fiber layer, and the macula, including the ganglion cell layer, allows for both qualitative and quantitative analysis of optic nerve diseases. This review covers the technical aspects of OCT and related imaging techniques in neuro-ophthalmology and discusses its use in common optic nerve head diseases such as optic disc drusen, optic disc coloboma, and elevated intracranial pressure. It also explores emerging OCT angiography applications in these disorders. Full article

Ophthalmic lens coatings are increasingly designed to combine optical, mechanical, and biological functions. This systematic review, registered in PROSPERO and conducted according to PRISMA 2020 guidelines, synthesized 54 experimental, preclinical, and clinical studies on coatings for spectacle lenses, contact lenses, and intraocular lenses. Spectacle lens studies consistently showed that anti-reflective and blue-light filtering coatings reduce glare perception, improve contrast sensitivity, and provide UV protection, while laboratory tests demonstrated significant reductions in impact resistance, with fracture energy of CR-39 lenses decreasing by up to 63% when coated. Contact lens research revealed that plasma and polymeric coatings reduce water contact angles from >100° to <20°, enhancing wettability, while antimicrobial strategies such as melamine binding or nanoparticle-based films achieved >80% reductions in bacterial adhesion. Drug-eluting approaches sustained antibiotic or antioxidant release for periods ranging from 24 h to 6 days, with improved ocular bioavailability compared with drops. Intraocular lens studies demonstrated that heparin surface modifications reduced postoperative flare and anterior chamber cells, and phosphorylcholine or alkylphosphocholine coatings suppressed lens epithelial cell proliferation. Drug-loaded coatings with methotrexate, gefitinib, or amikacin significantly inhibited posterior capsule opacification and infection in ex vivo and animal models. Collectively, coatings improve visual comfort, photoprotection, wettability, and biocompatibility, but clinical translation requires solutions to mechanical trade-offs, long-term stability, and regulatory challenges. Full article

Ocular surface disorders such as dry eye disease are an increasingly encountered ophthalmic disorder, in which signs and symptoms can vary significantly from one patient to the next. Severe dry eye can be a challenge for the ophthalmic practitioner to manage. Contemporary management options are wide-ranging and include topical treatments, contact lenses, and surgical options. More recently, newer stem cell-based therapies have emerged, and early reports have shown promising outcomes. Meanwhile, other novel approaches, such as the eggshell membrane, are currently in development, and while no studies have yet reported on its use in ophthalmic applications, further developments in this area are expected. However, longer-term studies are needed in order to fully assess the safety and efficacy of these newer treatments. There are an increasing number of treatment options available for ocular surface disorders. This article provides an overview of some of the current treatment options that are available for severe ocular surface disorders, including dry eye disease, as well as insight into applications that are currently in development, which may show potential in the future. Full article

Background: Papilledema, an ophthalmic finding associated with increased intracranial pressure, is often induced by dermatological medications, including corticosteroids, isotretinoin, and tetracyclines. Early detection is crucial for preventing irreversible optic nerve damage, but access to ophthalmologic expertise is often limited in rural settings. Artificial intelligence (AI) may enable the automated and accurate detection of papilledema from fundus images, thereby supporting timely diagnosis and management. Objective: The primary objective of this study was to explore the diagnostic capability of ChatGPT-4o, a general large language model with multimodal input, in identifying papilledema from fundus photographs. For context, its performance was compared with a ResNet-based convolutional neural network (CNN) specifically fine-tuned for ophthalmic imaging, as well as with the assessments of two human ophthalmologists. The focus was on applications relevant to dermatological care in resource-limited environments. Methods: A dataset of 1094 fundus images (295 papilledema, 799 normal) was preprocessed and partitioned into a training set and a test set. The ResNet model was fine-tuned using discriminative learning rates and a one-cycle learning rate policy. GPT-4o and two human evaluators (a senior ophthalmologist and an ophthalmology resident) independently assessed the test images. Diagnostic metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and Cohen’s Kappa, were calculated for each evaluator. Results: GPT-4o, when applied to papilledema detection, achieved an overall accuracy of 85.9% with substantial agreement beyond chance (Cohen’s Kappa = 0.72), but lower specificity (78.9%) and positive predictive value (73.7%) compared to benchmark models. For context, the ResNet model, fine-tuned for ophthalmic imaging, reached near-perfect accuracy (99.5%, Kappa = 0.99), while two human ophthalmologists achieved accuracies of 96.0% (Kappa ≈ 0.92). Conclusions: This study explored the capability of GPT-4o, a large language model with multimodal input, for detecting papilledema from fundus photographs. GPT-4o achieved moderate diagnostic accuracy and substantial agreement with the ground truth, but it underperformed compared to both a domain-specific ResNet model and human ophthalmologists. These findings underscore the distinction between generalist large language models and specialized diagnostic AI: while GPT-4o is not optimized for ophthalmic imaging, its accessibility, adaptability, and rapid evolution highlight its potential as a future adjunct in clinical screening, particularly in underserved settings. These findings also underscore the need for validation on external datasets and real-world clinical environments before such tools can be broadly implemented. Full article

Hyaluronan (HA), a high-molecular-weight polysaccharide naturally found in vertebrate tissues such as skin, joints, and the vitreous body, plays a critical role in various biological processes. Its functionality is highly dependent on molecular weight, with high-molecular-weight HA exhibiting anti-inflammatory and immunosuppressive effects, while low-molecular-weight HA promotes inflammation, immunostimulation, and angiogenesis. Due to its biocompatibility, biodegradability, and tunable properties, HA has gained increasing attention in biomedical applications. This review summarizes recent advances in the encapsulation of HA with other polymers and therapeutic agents in nanosystems, particularly hydrogels and nanoparticles. HA-based formulations demonstrate improved therapeutic outcomes, including drug release sustained up to 7 days, wound closure rates exceeding 90% in animal models, particle size in the range of 50–300 nm, and enhanced bioavailability of encapsulated drugs by 2–3 fold compared with free drugs. Such properties have shown promise in enhancing therapeutic efficacy and targeted drug delivery in the treatment of skin wound healing, diabetes, osteoarthritis, rheumatoid arthritis, and ophthalmic diseases. The review emphasizes how HA’s modifications and composite systems optimize drug release profiles and biological interactions, thereby contributing to the development of next-generation biomedical therapies. Full article

The influence of minor components on leaching molecular iodine (I₂) through polypropylene (PP)-based packaging from a povidone iodine-based (PVP-I) formulation, simulating an ophthalmic application, was evaluated. I₂ is a cheap, broad-spectrum, and multi-target antiseptic. Nevertheless, it is volatile, and the prolonged storage of I₂-based formulations is demanding in plastic packaging because of transmission through the material. Therefore, we explored the possibility of moderating the loss of I₂ from an iodophor formulation by introducing small amounts of molecular iodine into the polymer material commonly used in eyedropper caps, i.e., PP. Thus, PP was blended via an extrusion process with a polymeric complex containing iodine (such as PVP-I) or with a second polymeric component able to complex the I₂ released from an iodophor solution. The aim of this work was to introduce I₂ into PP-based polymer matrices without using organic solvents and indirectly, i.e., through the addition of components that could generate molecular iodine or complex it in the solid phase, as I₂ is heat-sensitive. To increase the miscibility between PP and PVP-I, poly(N-vinylpyrrolidone) (PVP) or a vinyl pyrrolidone vinyl acetate copolymer 55/45 (Sokalan) were added as compatibilizers. The PP-based binary and ternary blends, in granular or sheet form, were characterized thermally (Differential Scanning Calorimetry, DSC, and Thermogravimetric analysis, TGA), mechanically (tensile tests), morphologically (scanning electron microscopy (SEM)), and chemically (attenuated total reflectance Fourier transform infrared (ATR-FTIR)). Additionally, the variation in wettability induced by the introduction of the hydrophilic minority components was determined by static contact angle measurements (static contact angle (SCA)), and tests were carried out to determine the barrier properties against oxygen (oxygen transmission rate (OTR)) and molecular iodine. The I₂ leaching of the different blends was compared with that of PP by monitoring the I₂ retention in a buffered PVP-I solution via UV-vis spectroscopy. Overall, the experimental data showed the capability of the minority components in the blends to increase thermal stability as well as act as a barrier to oxygen. Additionally, the PP blend with PVP-I induced a reduction in molecular iodine leaching in comparison with PP. Full article