Rationale and design of the BeyeOMARKER study: prospective evaluation of blood- and eye-based biomarkers for early detection of Alzheimer's disease pathology in the eye clinic.

BACKGROUND: Alzheimer's disease (AD) is a common, complex and multifactorial disease that may require screening across multiple routes of referral to enable early detection and subsequent future implementation of tailored interventions. Blood- and eye-based biomarkers show promise as low-cost, scalable and patient-friendly tools for early AD detection given their ability to provide information on AD pathophysiological changes and manifestations in the retina, respectively. Eye clinics provide an intriguing real-world proof-of-concept setting to evaluate the performance of these potential AD screening tools given the intricate connections between the eye and brain, presumed enrichment for AD pathology in the aging population with eye disorders, and the potential for an accelerated diagnostic pathway for under-recognized patient groups. METHODS: The BeyeOMARKER study is a prospective, observational, longitudinal cohort study aiming to include individuals visiting an eye-clinic. Inclusion criteria entail being ≥ 50 years old and having no prior dementia diagnosis. Excluded eye-conditions include traumatic insults, superficial inflammation, and conditions in surrounding structures of the eye that are not engaged in vision. The BeyeOMARKER cohort (n = 700) will undergo blood collection to assess plasma p-tau217 levels and a brief cognitive screening at the eye clinic. All participants will subsequently be invited for annual longitudinal follow-up including remotely administered cognitive screening and questionnaires. The BeyeOMARKER + cohort (n = 150), consisting of 100 plasma p-tau217 positive participants and 50 matched negative controls selected from the BeyeOMARKER cohort, will additionally undergo Aß-PET and tau-PET, MRI, retinal imaging including hyperspectral imaging (primary), widefield imaging, optical coherence tomography (OCT) and OCT-Angiography (secondary), and cognitive and cortical vision assessments. RESULTS: We aim to implement the current protocol between April 2024 until March 2027. Primary outcomes include the performance of plasma p-tau217 and hyperspectral retinal imaging to detect AD pathology (using Aß- and tau-PET visual read as reference standard) and to detect cognitive decline. Initial follow-up is ~ 2 years but may be extended with additional funding. CONCLUSIONS: We envision that the BeyeOMARKER study will demonstrate the feasibility of early AD detection based on blood- and eye-based biomarkers in alternative screening settings, and will improve our understanding of the eye-brain connection. TRIAL REGISTRATION: The BeyeOMARKER study (Eudamed CIV ID: CIV-NL-23-09-044086; registration date: 19th of March 2024) is approved by the ethical review board of the Amsterdam UMC.

Artificial Intelligence for Early Detection of Pediatric Eye Diseases Using Mobile Photos.

IMPORTANCE: Identifying pediatric eye diseases at an early stage is a worldwide issue. Traditional screening procedures depend on hospitals and ophthalmologists, which are expensive and time-consuming. Using artificial intelligence (AI) to assess children's eye conditions from mobile photographs could facilitate convenient and early identification of eye disorders in a home setting. OBJECTIVE: To develop an AI model to identify myopia, strabismus, and ptosis using mobile photographs. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study was conducted at the Department of Ophthalmology of Shanghai Ninth People's Hospital from October 1, 2022, to September 30, 2023, and included children who were diagnosed with myopia, strabismus, or ptosis. MAIN OUTCOMES AND MEASURES: A deep learning-based model was developed to identify myopia, strabismus, and ptosis. The performance of the model was assessed using sensitivity, specificity, accuracy, the area under the curve (AUC), positive predictive values (PPV), negative predictive values (NPV), positive likelihood ratios (P-LR), negative likelihood ratios (N-LR), and the F1-score. GradCAM++ was utilized to visually and analytically assess the impact of each region on the model. A sex subgroup analysis and an age subgroup analysis were performed to validate the model's generalizability. RESULTS: A total of 1419 images obtained from 476 patients (225 female [47.27%]; 299 [62.82%] aged between 6 and 12 years) were used to build the model. Among them, 946 monocular images were used to identify myopia and ptosis, and 473 binocular images were used to identify strabismus. The model demonstrated good sensitivity in detecting myopia (0.84 [95% CI, 0.82-0.87]), strabismus (0.73 [95% CI, 0.70-0.77]), and ptosis (0.85 [95% CI, 0.82-0.87]). The model showed comparable performance in identifying eye disorders in both female and male children during sex subgroup analysis. There were differences in identifying eye disorders among different age subgroups. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, the AI model demonstrated strong performance in accurately identifying myopia, strabismus, and ptosis using only smartphone images. These results suggest that such a model could facilitate the early detection of pediatric eye diseases in a convenient manner at home.

The profile of patients attending to the general emergency department with ocular complaints within the last year: is it a true ocular emergency?

PURPOSE: Ocular emergencies require immediate intervention to prevent rapid vision loss or functional impairment. The aim of this study was to determine the proportion of true ocular emergencies among patients who presented to the general emergency department with ocular complaints and were referred to the Eye Clinic. METHODS: In a retrospective cross-sectional study in a tertiary hospital in Istanbul, patients aged 0-100 years who presented to the general emergency department with ocular complaints between January and December 2022 were included. Inconclusive diagnoses and incomplete records were excluded. Patients were divided into three groups: top eye emergencies (TE), relative eye emergencies (REE), and non-emergency eyes (NEE). RESULTS: Among the 652,224 individuals seeking care, 9,982 (1.5%) were referred to the Eye Emergency Clinic. Of these, 2,788 (27.9%) were female, and 7,194 (72.1%) were male, with ages ranging from 0 to 98 years. TopEye Emergencies (TEE), Relative Eye Emergencies (REE), and Non-Eye Emergencies (NEE) accounted for 13%, 60%, and 27% of the cases, respectively. Common top-eye emergencies (TEE) include chemical injuries, orbital-preseptal cellulitis, and orbital fractures. Relative eye emergencies (REEs) commonly feature corneal foreign bodies, corneal erosion, and conjunctivitis. Nonemulsion eye (NEE) methods involve simple eye redness, trauma without eye involvement, and subconjunctival haemorrhage. CONCLUSIONS: Consistent with the literature, 1.5% of patients presenting to the general emergency department had eye complaints.However, 27% of those referred to the ophthalmological clinic did not have an urgent eye condition. This is partly due to the high proportion of patients presenting to the emergency department with ocular complaints and the lack of knowledge of ophthalmological diseases by emergency physicians, leading to unnecessary referrals to the ophthalmology clinic, resulting in a loss of the workforce and reduced time allocated to patients with true ocular emergencies.

Tutorial on Biostatistics: Sample Size and Power Calculation for Ophthalmic Studies With Correlated Binary Eye Outcomes.

Purpose: To describe and demonstrate sample size and power calculation for ophthalmic studies with a binary outcome from one or both eyes. Methods: We describe sample size and power calculation for four commonly used eye designs: (1) one-eye design or person-design: one eye per subject or outcome is at person-level; (2) paired design: two eyes per subject and two eyes are in different treatment groups; (3) two-eye design: two eyes per subject and both eyes are in the same treatment group; and (4) mixture design: mixture of one eye and two eyes per subject. For each design, we demonstrate sample size and power calculations in real ophthalmic studies. Results: Using formulas and commercial or free statistical packages including SAS, STATA, R, and PS, we calculated sample size and power. We demonstrated that different statistical packages require different parameters and provide similar, yet not identical, results. We emphasize that studies using data from two eyes of a subject need to account for the intereye correlation for appropriate sample size and power calculations. We demonstrate the gain in efficiency in designs that include two eyes of a subject compared to one-eye designs. Conclusions: Ophthalmic studies use different eye designs that include one or both eyes in the same or different treatment groups. Appropriate sample size and power calculations depend on the eye design and should account for intereye correlation when two eyes from some or all subjects are included in a study. Calculations can be executed using formulas and commercial or free statistical packages.

Evaluating the Diagnostic Accuracy of a Portable, Motorized, and Remotely Controlled Slit Lamp Imaging Adaptor Prototype for Head-Mounted Displays.

Purpose: The purpose of this study was to validate the performance of a portable and remotely controlled slit lamp imaging adaptor. Methods: Twenty patients with anterior eye segment conditions participated in a randomized masked clinical trial. Imaging was performed using a Haag-Streit AG, BX 900 slit lamp biomicroscope and a new slit lamp prototype. Three ophthalmologists independently reviewed masked and randomized 2D images from both instruments and conducted physical eye examinations based on these images. Inter- and intra-grader reliability were assessed using kappa statistics, and sensitivity and specificity were determined with reference to the clinical eye examinations performed during the patients' visits. Results: The sensitivity and specificity of the evaluations with the prototype were 47.8% and 64.1%. Similarly, the evaluations from the conventional system obtained a sensitivity and specificity of 49.5% and 66.2%. The differences in the sensitivity and specificity between imaging modalities were not statistically significant (P > 0.05). The intra-grader reliability showed moderate to substantial agreement between the systems (κ = 0.522-0.708). The inter-grader reliability also indicated moderate agreement for the evaluations with the conventional system (κ = 0.552) and the prototype (κ = 0.474). Conclusions: This study presents a new prototype that exhibits diagnostic accuracy on par with conventional slit lamps and moderate reliability. Further studies with larger sample sizes are required to characterize the prototype's performance. However, its remote functionality and accessibility suggest the potential to extend eye care. Translational Relevance: The development of portable and remotely controlled eye imaging systems will enhance teleophthalmology services and broaden access to eye care at the primary care level.

AI in Neuro-Ophthalmology: Current Practice and Future Opportunities.

BACKGROUND: Neuro-ophthalmology frequently requires a complex and multi-faceted clinical assessment supported by sophisticated imaging techniques in order to assess disease status. The current approach to diagnosis requires substantial expertise and time. The emergence of AI has brought forth innovative solutions to streamline and enhance this diagnostic process, which is especially valuable given the shortage of neuro-ophthalmologists. Machine learning algorithms, in particular, have demonstrated significant potential in interpreting imaging data, identifying subtle patterns, and aiding clinicians in making more accurate and timely diagnosis while also supplementing nonspecialist evaluations of neuro-ophthalmic disease. EVIDENCE ACQUISITION: Electronic searches of published literature were conducted using PubMed and Google Scholar. A comprehensive search of the following terms was conducted within the Journal of Neuro-Ophthalmology: AI, artificial intelligence, machine learning, deep learning, natural language processing, computer vision, large language models, and generative AI. RESULTS: This review aims to provide a comprehensive overview of the evolving landscape of AI applications in neuro-ophthalmology. It will delve into the diverse applications of AI, optical coherence tomography (OCT), and fundus photography to the development of predictive models for disease progression. Additionally, the review will explore the integration of generative AI into neuro-ophthalmic education and clinical practice. CONCLUSIONS: We review the current state of AI in neuro-ophthalmology and its potentially transformative impact. The inclusion of AI in neuro-ophthalmic practice and research not only holds promise for improving diagnostic accuracy but also opens avenues for novel therapeutic interventions. We emphasize its potential to improve access to scarce subspecialty resources while examining the current challenges associated with the integration of AI into clinical practice and research.

Miscellaneous ophthalmic conditions related to low CD4 cell count in HIV-positive patients.

Introduction: Management of patients living with Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (AIDS) (PLWHA) still represents a challenge for doctors in various medical fields. The presence of co-infections, with different degrees of immune system impairment, raises the need for a multi-disciplinary approach to the PLWHA. Methods: In this paper, we present three cases of PLWHA with various ophthalmological conditions, who were admitted to "Prof. Dr. Matei Balș" National Institute for Infectious Diseases (INBIMB). Three of them were late presenters, recently diagnosed with AIDS. All three were in immuno-virological failure. The ophthalmic conditions were either related to the HIV infection, or the result of other complications. Discussion: The diversity and complexity of ocular involvement in PLWHA were deeply linked to the patient's immunological status at the ophthalmological evaluation moment. Thus, antiretroviral therapy (ART) played an important immune status recovery role. Encountered ocular conditions vary, some being directly caused by the presence of the virus, and the others were the result of opportunistic infections (cytomegalovirus, Varicella virus) or other co-infections (Treponema pallidum). Neurological conditions disturbing the natural defense mechanism, prolonged hospital stay, and exposure to multiple antibiotic regimens are risk factors for difficult-to-treat eye infections with multidrug-resistant bacteria. Some ocular conditions can be the reason that leads to HIV infection diagnosis, while others can appear during the time, especially in patients with low ART adherence. The prognostic is conditioned by the early recognition and correct management of the disease and the immunological status recovery under ART. Conclusions: Correct and early diagnosis of HIV-related eye conditions is mandatory to establish the most appropriate medical management to obtain an increase in the quality of life of the patient. Abbreviations: HIV = Human Immunodeficiency Virus, AIDS = Acquired Immunodeficiency Syndrome, ART = Antiretroviral Therapy.

Fairer AI in ophthalmology via implicit fairness learning for mitigating sexism and ageism.

The transformative role of artificial intelligence (AI) in various fields highlights the need for it to be both accurate and fair. Biased medical AI systems pose significant potential risks to achieving fair and equitable healthcare. Here, we show an implicit fairness learning approach to build a fairer ophthalmology AI (called FairerOPTH) that mitigates sex (biological attribute) and age biases in AI diagnosis of eye diseases. Specifically, FairerOPTH incorporates the causal relationship between fundus features and eye diseases, which is relatively independent of sensitive attributes such as race, sex, and age. We demonstrate on a large and diverse collected dataset that FairerOPTH significantly outperforms several state-of-the-art approaches in terms of diagnostic accuracy and fairness for 38 eye diseases in ultra-widefield imaging and 16 eye diseases in narrow-angle imaging. This work demonstrates the significant potential of implicit fairness learning in promoting equitable treatment for patients regardless of their sex or age.

Ocular Manifestations of Fabry Disease: Report from a Tertiary Eye Care Center in Türkiye.

Objectives: To report ocular manifestations in patients with Fabry disease (FD) from a tertiary eye care center in Türkiye. Materials and Methods: This prospective, cross-sectional study included 30 eyes of 15 patients with FD. The diagnosis of FD was made based on a combination of clinical findings, genetic analysis, and biochemical evaluation. All participants underwent a detailed ophthalmic examination with special focus on the typical ocular features of FD (cornea verticillata, conjunctival aneurysms, cataract, retinal vessel tortuosity). Results: The mean age was 45±17 years (range: 22-75 years), with a female/male ratio of 2:3. All patients had tortuous conjunctival vessels and 12 patients (80%) had conjunctival aneurysms. Cornea verticillata was present in 10 patients (66.6%), lens opacification in 4 patients (26.6%), and retinal vascular tortuosity in 8 patients (53.3%). All patients had at least two different ocular findings; most (3 heterozygotes/7 hemizygotes) had a combination of corneal verticillata and conjunctival vessel abnormality. The conjunctiva, cornea, and retina were affected together in 5 hemizygous patients (33.3%). One hemizygous patient had all FDrelated ocular manifestations in both eyes. Conclusion: To our knowledge, this study is the first to describe the ocular manifestations of FD in the Turkish population. Although cornea verticillata is considered a hallmark of FD, it was absent in approximately one-third of patients. Moreover, cataract, another well-known feature of FD, was present in only 26.6% of the patients. Conjunctival vascular abnormality alone seems to be quite rare in FD, although it often accompanies other ocular manifestations. Therefore, recognition of other mild findings and special consideration of their associations may increase the diagnostic value of ocular findings in FD.

[Association between emotional disorders and ophthalmopathology in residents of the Arkhangelsk region at the age of 60-74 years.]

A study was conducted to investigate the associations of the diseases of the organ of vision and its accessory apparatus with anxiety and depression in the elderly people. The study included 678 participants of the ESSE-RF3 population study in the Arkhangelsk region in the age of 60-74 years. We used a questionnaire, including the hospital scale of anxiety and depression score (HADS), and the assessment of the ophthalmological status. It was found that all the study participants had diseases of the visual organ. Elevated depression scores were associated with sex, age, marital status (being single), and disability, elevated anxiety scores - with sex. The scores on the anxiety scale were on average 25% higher in participants whose visual acuity decreased to 0,5 units, and showed no independent associations with diagnosed ophthalmological diseases. The scores on the depression scale were on average 33% higher in participants with visual acuity 0,5 units, and 22% higher in the presence of retinopathy. In conclusion, anxiety and depression in the elderly people were more associated with visual deficits rather than with the presence of ophthalmological diseases underlying a decrease in functional status.

Comparing the intraocular pressure values obtained with a rebound tonometer (TONOVET Plus) and an indentation tonometer (IOPvet) in dogs with and without ocular disease.

BACKGROUND: This study aimed to compare the intraocular pressure (IOP) values obtained from two groups of dogs using the IOPvet indentation tonometer to those obtained from the same dogs using an established rebound tonometer (TONOVET Plus). METHODS: Tonometry was performed on 36 dogs with ocular diseases (70 eyes; group A) and 25 healthy dogs (49 eyes; group B). First, the TONOVET Plus rebound tonometer was used. Then, one drop of oxybuprocaine hydrochloride was applied to each eye, and 1 minute later, the IOP was estimated using the IOPvet. RESULTS: The IOPvet was safe, well tolerated and easy to use. The instrument had a high specificity (98.5%) for identifying IOPs of 20 mmHg or less. A lack of sensitivity (67.9%) was noted when evaluating eyes with an IOP between 20 and 30 mmHg. The sensitivity (33.3%) for identifying canine eyes with an IOP of greater than 30 mmHg (n = 24) was low. LIMITATIONS: This study lacks manometric work, which would be hard to justify with client-owned dogs. Quantitative numerical data were compared with qualitative values and the same investigator obtained readings using both tonometers without being masked. CONCLUSIONS: The IOPvet is highly sensitive for assessing normal IOPs, but underestimation of higher IOPs can lead to poor diagnostics. Digital tonometers remain the best way to assess IOP in veterinary clinics.

PREVALENCE OF OCULAR ABNORMALITIES AND NORMAL DIAGNOSTIC PARAMETERS IN TWO GROUPS OF PANAMANIAN GOLDEN FROGS (ATELOPUS ZETEKI).

Panamanian golden frog (PGF) (Atelopus zeteki) is a critically endangered species. The Maryland Zoo in Baltimore houses two groups of PGF originating from distinct geographic locations as an assurance colony, with the goal of upholding genetics for future release of individuals back to their native environment. The purpose of this cross-sectional study was to characterize the prevalence of ocular abnormalities in these two zoo-housed populations of PGF as well as to establish normal parameters for selected diagnostic tests in these groups. Twenty-five females and 25 males were randomly selected from each group (100 PGF; 200 eyes in total) to undergo ocular examination using slit lamp biomicroscopy and direct ophthalmoscopy. Endodontic absorbent paper point test (EAPPT) and intraocular pressure (IOP) and Rose Bengal stain diagnostic tests were also performed. Reference ranges for tear production (EAPPT, 0.5-3 mm/min) and IOP (14-26 mmHg) were calculated in the nondiseased PGF eyes (n = 160 eyes). Rose Bengal stain uptake was negative on all eyes. In total, 40 eyes of 30 PGF were found to have some form of ocular abnormality (28% of PGF, 20% of eyes). The most frequently observed ocular abnormalities were cataract (9% of PGF, 6% of eyes) and keratitis (nonlipid keratopathy; 10% of PGF, 5.5% of eyes). There was no significant difference in overall ocular abnormality prevalence between the two groups studied (P = 0.37) or between the sexes (P = 0.76). The median age of an eye with cataract and keratitis (nonlipid keratopathy) was 10.35 and 7.7 yr, respectively. Ocular abnormalities are common in these two populations of PGF. Documentation of these ocular abnormalities and establishment of diagnostic reference ranges have not previously been published and may be important for maintaining the health of this endangered species.

Dual-Mode Imaging System for Early Detection and Monitoring of Ocular Surface Diseases.

The global prevalence of ocular surface diseases (OSDs), such as dry eyes, conjunctivitis, and subconjunctival hemorrhage (SCH), is steadily increasing due to factors such as aging populations, environmental influences, and lifestyle changes. These diseases affect millions of individuals worldwide, emphasizing the importance of early diagnosis and continuous monitoring for effective treatment. Therefore, we present a deep learning-enhanced imaging system for the automated, objective, and reliable assessment of these three representative OSDs. Our comprehensive pipeline incorporates processing techniques derived from dual-mode infrared (IR) and visible (RGB) images. It employs a multi-stage deep learning model to enable accurate and consistent measurement of OSDs. This proposed method has achieved a 98.7% accuracy with an F1 score of 0.980 in class classification and a 96.2% accuracy with an F1 score of 0.956 in SCH region identification. Furthermore, our system aims to facilitate early diagnosis of meibomian gland dysfunction (MGD), a primary factor causing dry eyes, by quantitatively analyzing the meibomian gland (MG) area ratio and detecting gland morphological irregularities with an accuracy of 88.1% and an F1 score of 0.781. To enhance convenience and timely OSD management, we are integrating a portable IR camera for obtaining meibography during home inspections. Our system demonstrates notable improvements in expanding dual-mode image-based diagnosis for broader applicability, effectively enhancing patient care efficiency. With its automation, accuracy, and compact design, this system is well-suited for early detection and ongoing assessment of OSDs, contributing to improved eye healthcare in an accessible and comprehensible manner.

[Challenges and prospects in the application of artificial intelligence for ocular disease screening and diagnosis].

In recent years, artificial intelligence (AI) technologies have experienced substantial growth across various sectors, with significant strides made particularly in medical AI through advancements such as large models. The application of AI within the field of ophthalmology can enhance the accuracy of eye disease screening and diagnosis. However, the deployment of AI and its large models in ophthalmology still encounters numerous limitations and challenges. This article builds upon the transformative achievements in the medical AI sector and discusses the ongoing challenges faced by AI applications in ophthalmology. It provides forward-looking insights from an ophthalmic perspective regarding the era of large models and anticipates research trends in AI applications in ophthalmology, so as to foster the continuous advancement of AI technologies, thereby significantly promoting eye health.

The UK clinical eye research strategy: refreshing research priorities for clinical eye research in the UK.

OBJECTIVES: To validate and update the 2013 James Lind Alliance (JLA) Sight Loss and Vision Priority Setting Partnership (PSP)'s research priorities for Ophthalmology, as part of the UK Clinical Eye Research Strategy. METHODS: Twelve ophthalmology research themes were identified from the JLA report. They were allocated to five Clinical Study Groups of diverse stakeholders who reviewed the top 10 research priorities for each theme. Using an online survey (April 2021-February 2023), respondents were invited to complete one or more of nine subspecialty surveys. Respondents indicated which of the research questions they considered important and subsequently ranked them. RESULTS: In total, 2240 people responded to the survey (mean age, 59.3 years), from across the UK. 68.1% were female. 68.2% were patients, 22.3% healthcare professionals or vision researchers, 7.1% carers, and 2.1% were charity support workers. Highest ranked questions by subspecialty: Cataract (prevention), Cornea (improving microbial keratitis treatment), Optometric (impact of integration of ophthalmic primary and secondary care via community optometric care pathways), Refractive (factors influencing development and/or progression of refractive error), Childhood onset (improving early detection of visual disorders), Glaucoma (effective and improved treatments), Neuro-ophthalmology (improvements in prevention, diagnosis and treatment of neurodegeneration affecting vision), Retina (improving prevention, diagnosis and treatment of dry age-related macular degeneration), Uveitis (effective treatments for ocular and orbital inflammatory diseases). CONCLUSIONS: A decade after the initial PSP, the results refocus the most important research questions for each subspecialty, and prime targeted research proposals within Ophthalmology, a chronically underfunded specialty given the substantial burden of disability caused by eye disease.