Comprehensive Association Analyses of Extraintestinal Manifestations in Inflammatory Bowel Disease.

BACKGROUND & AIMS: Patients with inflammatory bowel disease (IBD) frequently develop extraintestinal manifestations (EIMs) that contribute substantially to morbidity. We assembled the largest multicohort data set to date to investigate the clinical, serologic, and genetic factors associated with EIM complications in IBD. METHODS: Data were available in 12,083 unrelated European ancestry IBD cases with presence or absence of EIMs (eg, ankylosing spondylitis [ankylosing spondylitis and sacroiliitis], primary sclerosing cholangitis [PSC], peripheral arthritis, and skin and ocular manifestations) across 4 cohorts (Cedars-Sinai Medical Center, National Institute for Diabetes and Digestive and Kidney Diseases IBD Genetics Consortium, Sinai Helmsley Alliance for Research Excellence Consortium, and Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn's Disease cohort). Clinical and serologic parameters were analyzed by means of univariable and multivariable regression analyses using a mixed-effects model. Within-case logistic regression was performed to assess genetic associations. RESULTS: Most EIMs occurred more commonly in female subjects (overall EIM: P = 9.0E-05, odds ratio [OR], 1.2; 95% CI, 1.1-1.4), with CD (especially colonic disease location; P = 9.8E-09, OR, 1.7; 95% CI, 1.4-2.0), and in subjects who required surgery (both CD and UC; P = 3.6E-19, OR, 1.7; 95% CI, 1.5-1.9). Smoking increased risk of EIMs except for PSC, where there was a "protective" effect. Multiple serologic associations were observed, including with PSC (anti-nuclear cytoplasmic antibody; IgG and IgA, anti-Saccharomyces cerevisiae antibodies; and anti-flagellin) and any EIM (anti-nuclear cytoplasmic antibody; IgG and IgA, anti-Saccharomyces cerevisiae antibodies; and anti-Pseudomonas fluorescens-associated sequence). We identified genome-wide significant associations within major histocompatibility complex (ankylosing spondylitis and sacroiliitis, P = 1.4E-15; OR, 2.5; 95% CI, 2.0-3.1; PSC, P = 2.7E-10; OR, 2.8; 95% CI, 2.0-3.8; ocular, P = 2E-08, OR, 3.6; 95% CI, 2.3-5.6; and overall EIM, P = 8.4E-09; OR, 2.2; 95% CI, 1.7-2.9) and CPEB4 (skin, P = 2.7E-08; OR, 1.5; 95% CI, 1.3-1.8). Genetic associations implicated tumor necrosis factor, JAK-STAT, and IL6 as potential targets for EIMs. Contrary to previous reports, only 2% of our subjects had multiple EIMs and most co-occurrences were negatively correlated. CONCLUSIONS: We have identified demographic, clinical, and genetic associations with EIMs that revealed underlying mechanisms and implicated novel and existing drug targets-important steps toward a more personalized approach to IBD management.

Diagnostic genome sequencing improves diagnostic yield: a prospective single-centre study in 1000 patients with inherited eye diseases.

PURPOSE: Genome sequencing (GS) is expected to reduce the diagnostic gap in rare disease genetics. We aimed to evaluate a scalable framework for genome-based analyses 'beyond the exome' in regular care of patients with inherited retinal degeneration (IRD) or inherited optic neuropathy (ION). METHODS: PCR-free short-read GS was performed on 1000 consecutive probands with IRD/ION in routine diagnostics. Complementary whole-blood RNA-sequencing (RNA-seq) was done in a subset of 74 patients. An open-source bioinformatics analysis pipeline was optimised for structural variant (SV) calling and combined RNA/DNA variation interpretation. RESULTS: A definite genetic diagnosis was established in 57.4% of cases. For another 16.7%, variants of uncertain significance were identified in known IRD/ION genes, while the underlying genetic cause remained unresolved in 25.9%. SVs or alterations in non-coding genomic regions made up for 12.7% of the observed variants. The RNA-seq studies supported the classification of two unclear variants. CONCLUSION: GS is feasible in clinical practice and reliably identifies causal variants in a substantial proportion of individuals. GS extends the diagnostic yield to rare non-coding variants and enables precise determination of SVs. The added diagnostic value of RNA-seq is limited by low expression levels of the major IRD disease genes in blood.

A bird's eye view on the use of whole exome sequencing in rare congenital ophthalmic diseases.

Phenotypic and genotypic heterogeneity in congenital ocular diseases, especially in anterior segment dysgenesis (ASD), have created challenges for proper diagnosis and classification of diseases. Over the last decade, genomic research has indeed boosted our understanding in the molecular basis of ASD and genes associated with both autosomal dominant and recessive patterns of inheritance have been described with a wide range of expressivity. Here we describe the molecular characterization of a cohort of 162 patients displaying isolated or syndromic congenital ocular dysgenesis. Samples were analyzed with diverse techniques, such as direct sequencing, multiplex ligation-dependent probe amplification, and whole exome sequencing (WES), over 20 years. Our data reiterate the notion that PAX6 alterations are primarily associated with ASD, mostly aniridia, since the majority of the cohort (66.7%) has a pathogenic or likely pathogenic variant in the PAX6 locus. Unexpectedly, a high fraction of positive samples (20.3%) displayed deletions involving the 11p13 locus, either partially/totally involving PAX6 coding region or abolishing its critical regulatory region, underlying its significance. Most importantly, the use of WES has allowed us to both assess variants in known ASD genes (i.e., CYP1B1, ITPR1, MAB21L1, PXDN, and PITX2) and to identify rarer phenotypes (i.e., MIDAS, oculogastrointestinal-neurodevelopmental syndrome and Jacobsen syndrome). Our data clearly suggest that WES allows expanding the analytical portfolio of ocular dysgenesis, both isolated and syndromic, and that is pivotal for the differential diagnosis of those conditions in which there may be phenotypic overlaps and in general in ASD.

Raman spectroscopy assisted tear analysis: A label free, optical approach for noninvasive disease diagnostics.

In recent times, tear fluid analysis has garnered considerable attention in the field of biomarker-based diagnostics due to its noninvasive sample collection method. Tears encompass a reservoir of biomarkers that assist in diagnosing not only ocular disorders but also a diverse list of systemic diseases. This highlights the necessity for sensitive and dependable screening methods to employ tear fluid as a potential noninvasive diagnostic specimen in clinical environments. Considerable research has been conducted to investigate the potential of Raman spectroscopy-based investigations for tear analysis in various diagnostic applications. Raman Spectroscopy (RS) is a highly sensitive and label free spectroscopic technique which aids in investigating the molecular structure of samples by evaluating the vibrational frequencies of molecular bonds. Due to the distinct chemical compositions of different samples, it is possible to obtain a sample-specific spectral fingerprint. The distinctive spectral fingerprints obtained from Raman spectroscopy enable researchers to identify specific compounds or functional groups present in a sample, aiding in diverse biomedical applications. Its sensitivity to changes in molecular structure or environment provides invaluable insights into subtle alterations associated with various diseases. Thus, Raman Spectroscopy has the potential to assist in diagnosis and treatment as well as prognostic evaluation. Raman spectroscopy possesses several advantages, such as the non-destructive examination of samples, remarkable sensitivity to structural variations, minimal prerequisites for sample preparation, negligible interference from water, and the aptness for real-time investigation of tear samples. The purpose of this review is to highlight the potential of Raman spectroscopic technique in facilitating the clinical diagnosis of various ophthalmic and systemic disorders through non-invasive tear analysis. Additionally, the review delves into the advancements made in Raman spectroscopy with regards to paper-based sensing substrates and tear analysis methods integrated into contact lenses. Furthermore, the review also addresses the obstacles and future possibilities associated with implementing Raman spectroscopy as a routine diagnostic tool based on tear analysis in clinical settings.

Advances in the ocular complications after hematopoietic stem cell transplantation.

Hematopoietic stem cell transplantation (HSCT) has benefited an increasing number of patients with hematological disease in the clinic. It is a curative therapy for malignant and nonmalignant hematological diseases. With the advancement and further clinical application of HSCT in recent years, the life expectancy of patients has increased, but complications have become more common. The occurrence of ocular complications is receiving increasing attention because they can seriously affect the quality of life of patients. Ocular complications require increased attention from clinicians because of their negative impact on patients and increasing incidence. Most of recent reports on posttransplant ocular complications involve ocular manifestations of graft-versus-host disease (GVHD), and a few ocular complications that do not originate from GVHD have also been reported. This review summarizes the diagnosis, scoring criteria, pathophysiology, and clinical manifestations of and common therapies for ocular graft-versus-host disease(oGVHD) after HSCT, and includes a description of some rare cases and novel therapies.

Highlights of ophthalmological manifestations in newly diagnosed acute leukemia: a correlation with hematological parameters.

Acute leukemia is a hematological malignancy affecting different organ systems including the eye and orbit through direct infiltration of tissues or secondary to hematological abnormalities. Ophthalmological manifestations in acute leukemia are variable ranging from asymptomatic presentation to serious manifestations that can alter the disease course and treatment. The purpose of this study is to detect the incidence of different ophthalmological manifestations in newly diagnosed acute leukemia patients and to assess the relationship between ocular findings and hematological characteristics and the sequel of these neoplasms. A cross-sectional study with analytical components was conducted on 222 newly diagnosed acute myeloid and acute lymphoblastic leukemia patients who presented at Oncology Center Mansoura University (OCMU) between January 2022 and February 2023. All patients underwent a complete ophthalmic evaluation at Mansoura Ophthalmology Center (MOC). The mean age was 43.45 ± 17.35 years (range, 17-85), and M/F was 137 (61.7%)/85 (38.3%). One-hundred and forty-four (64.9%) had acute myeloid leukemia (AML), and 78 (35.1%) had acute lymphoblastic leukemia (ALL). Ophthalmic manifestations were detected in 96 patients (43.2%). Among them, 4 (1.8%) had poor visual acuity. Retinal hemorrhage (19.8%) and Roth spots (17.1%) were the most common ocular manifestations. Other ophthalmological manifestations observed were orbital involvement (3.2%), ocular motility issues (1.4%), subconjunctival hemorrhage (5.9%), conjunctival chemosis (0.9%),lid swelling (4.1%), lid ecchymosis (3.2%), lagophthalmos (0.5%), lid ptosis (1.8%), retinal venous congestion & tortuosity (4.1%), preretinal hemorrhage (3.2%), vitreous hemorrhage (3.2%), macular affection (2.3%), retinal infiltration (1.8%), exudative retinal detachment (ERD) (1.8%), cotton-wool spots (0.9%), retinal vein occlusion (0.5%), papilledema (2.8%), optic disc infiltration (1.8%), disc pallor (1.8%).AML patients were significantly associated with a higher frequency of ocular affection, retinal hemorrhages, and Roth spots (P 0.028, 0.003, and 0.046, respectively) compared to ALL patients. Retinal hemorrhage was statistically significantly associated with anemia (P 0.021). Ophthalmological manifestations of acute leukemia are heterogeneous; they can be detected at initial presentations or relapse. Some manifestations are asymptomatic, others can affect visual acuity or even alter the disease course. Cooperation between ophthalmologists and haemato-oncologists is crucial for recognizing ocular involvement and disease management.

Implementation of anterior segment ophthalmic telemedicine.

PURPOSE OF REVIEW: The growing push to integrate telemedicine into ophthalmic practices requires physicians to have a thorough understanding of ophthalmic telemedicine's applications, limitations, and recent advances in order to provide well tolerated and appropriate clinical care. This review aims to provide an overview of recent advancements in the use of ophthalmic telemedicine for anterior segment eye examinations. RECENT FINDINGS: Virtual care for anterior segment evaluation relies on appropriate technology, novel workflows, and appropriate clinical case selection. Recent advances, particularly in the wake of the COVID-19 pandemic, have highlighted the utility of home-based assessments for visual acuity, external evaluation, tonometry, and refraction. Additionally, innovative workflows incorporating office-based testing into virtual care, termed 'hybrid telemedicine', enable high-quality ophthalmic testing to inform clinical decision-making. SUMMARY: Novel digital tools and workflows enable high-quality anterior segment evaluation and management for select ophthalmic concerns. This review highlights the clinical tools and workflows necessary to enable anterior segment telehealth.

Ocular involvement in Steven-Johnson syndrome/toxic epidermal necrolysis: recent insights into pathophysiology, biomarkers, and therapeutic strategies.

PURPOSE OF REVIEW: To review the pathophysiology, recent biomarkers related to the ocular aspects of Steven-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN), and to highlight notable evidence published in recent years. RECENT FINDINGS: Several studies reveal the relationship between tear cytokines and the pathological components in eyes of SJS/TEN patients. Specific clinical features and associated risk factors in the acute stage have shown significant correlations with chronic ocular sequelae. Recent treatment protocols, including early pulse systemic and topical steroids, as well as tumor necrosis factor-α inhibitors, have demonstrated positive effects on ocular outcomes. In addition to conventional surgical treatment, a new surgical technique, simple oral mucosal epithelial transplantation (SOMET), has been introduced as a simple ocular surface reconstruction for patient with SJS. SUMMARY: Advancements in knowledge and management strategies have notably enhanced ocular outcomes for SJS/TEN eyes. A deeper understanding of the biomarker changes in these eyes could facilitate the development of future targeted treatment options.

Diagnostic capabilities of ChatGPT in ophthalmology.

PURPOSE: The purpose of this study is to assess the diagnostic accuracy of ChatGPT in the field of ophthalmology. METHODS: This is a retrospective cohort study conducted in one academic tertiary medical center. We reviewed data of patients admitted to the ophthalmology department from 06/2022 to 01/2023. We then created two clinical cases for each patient. The first case is according to the medical history alone (Hx). The second case includes an addition of the clinical examination (Hx and Ex). For each case, we asked for the three most likely diagnoses from ChatGPT, residents, and attendings. Then, we compared the accuracy rates (at least one correct diagnosis) of all groups. Additionally, we evaluated the total duration for completing the assignment between the groups. RESULTS: ChatGPT, residents, and attendings evaluated 126 cases from 63 patients (history only or history and exam findings for each patient). ChatGPT achieved a significantly lower accurate diagnosis rate (54%) in the Hx, as compared to the residents (75%; p < 0.01) and attendings (71%; p < 0.01). After adding the clinical examination findings, the diagnosis rate of ChatGPT was 68%, whereas for the residents and the attendings, it increased to 94% (p < 0.01) and 86% (p < 0.01), respectively. ChatGPT was 4 to 5 times faster than the attendings and residents. CONCLUSIONS AND RELEVANCE: ChatGPT showed low diagnostic rates in ophthalmology cases compared to residents and attendings based on patient history alone or with additional clinical examination findings. However, ChatGPT completed the task faster than the physicians.

Neuro-ophthalmic complications of modern anti-cancer drugs.

PURPOSE: Targeted cancer therapies have been responsible for a dramatic shift in treatment strategies for cancer, and the number of drugs, classes, and indications are continually growing. Neuro-ophthalmic complications of these medications are an uncommon but important subset of adverse events which profoundly impact vision. This review aims to collate studies and reports of known neuro-ophthalmic complications of targeted therapies and describe their management. METHODS: The anti-cancer drugs included in the review were any drugs targeting specific molecules involved in the cancer disease process. PubMed, EMBASE, and Web of Science were searched using the generic names of each drug and keywords of neuro-ophthalmic conditions. The prescribing information published by the US Food and Drug Administration (FDA) for each drug was also reviewed. RESULTS: Several classes of targeted anti-cancer drugs were found to cause neuro-ophthalmic adverse effects. Immune checkpoint inhibitors are responsible for a raft of immune-related adverse events such as optic neuritis, ischemic optic neuropathy, PRES, and myasthenia gravis. Therapies with anti-VEGF activity can provoke posterior reversible leukoencephalopathy, which commonly presents with visual loss and can be fatal if not treated promptly. Inhibitors of BCR-ABL1, VEGF, ALK, and proteasomes have all been linked to optic nerve disorders which can have debilitating consequences for vision. CONCLUSION: The neuro-ophthalmic complications of modern anti-cancer drugs can limit or necessitate the withdrawal of these life-prolonging medications. Ophthalmologists should be alert for neuro-ophthalmic complications in these medications to facilitate prompt diagnosis and treatment and reduce the risk of severe and permanent consequences.

Evaluation of the test-retest and inter-mode comparability of the Impact of Vision Impairment questionnaire in people with chronic eye diseases.

PURPOSE: The main objective of this study is to assess the test-retest and inter-administration mode reliability of the Impact of Vision Impairment profile (IVI), a common patient-reported outcome measure (PROM) for people with chronic eye diseases. METHODS: The IVI was administered to adult patients with stable, chronic eye diseases two to four times per participant (average intervals between administrations 12 to 20 days; maximum two phone interviews, paper administration, electronic administration) by two trained interviewers. Rasch models were fit to the data. Intra-class correlation coefficients (ICCs), mean differences and Cronbach's alpha between test-retest administrations (two phone interviews) and inter-mode comparisons were calculated. RESULTS: Two hundred-sixteen patients (mean age 67 ± 12 years, 40% male) were included in the study. The IVI met all psychometric requirements of the Rasch model, and the division into the domains of functional items (IVI_F) and emotional items (IVI_E) corresponded to the German validation study. ICCs (all for IVI_F and IVI_E, respectively) for the retest administrations were 0.938 and 0.912, and 0.853 and 0.893 for inter-mode comparisons phone/paper, 0.939 and 0.930 for phone/electronic, and 0.937 and 0.920 for paper/electronic (all p < 0.01). Mean differences (all for IVI_F and IVI_E, respectively) for the retest administrations were 2.8% and 0.7% and ranged from 2.0% to 6.2% and from 0.4 % to 4.9% between administration modes. Cronbach's alpha ranged from 0.886 to 0.944 for retest and inter-mode comparisons. CONCLUSION: Due to the high test-retest reliability and the almost equally high comparability of different modes of administration of the IVI, the study endorses its use as a robust PROM to capture vision-related quality of life. Our results further support the use of the IVI as an endpoint in clinical trials and may simplify implementing it in both clinical trials or real-world evidence generation by offering multiple administration modes with high reliability.

Personality traits and symptoms of anxiety and depression in patients with primary vitreous floaters.

PURPOSE: We investigated personality traits and symptoms of anxiety and depression in patients with primary vitreous floaters. METHODS: A U.K. sample of adult patients (> 18 years old) with vitreous floaters of a minimum of three months severe enough to seek a consultation was assessed for personality traits (The Big Five Inventory (BFI)), symptoms of depression (Patient Health Questionnaire-9), and symptoms of anxiety (Generalized Anxiety Disorder Questionnaire-7). RESULTS: 149 patients participated in the study. Compared to the general population, our sample had a significantly increased score in the domain of BFI-neuroticism (3.27 vs 2.97, ρ < 0.0001, d = 0.38) and reduced score in the domain of extraversion (2.97 vs 3.24, ρ < 0.0001, d = 0.33). Female patients scored significantly higher than male patients on BFI-neuroticism (ρ = 0.01), and on BFI-agreeableness (ρ = 0.01). Age was positively correlated with BFI-Conscientiousness (r = 0.19, ρ = 0.02) and with BFI-Agreeableness (r = 0.20, ρ = 0.01). 36% of our sample had moderate to severe symptoms of depression, and 43% had moderate to severe symptoms of anxiety. CONCLUSIONS: Our study highlights the underlying psychological traits of patients with severe vitreous floaters and particular mental health needs that deserve further consideration by ophthalmological and vision science clinicians.

AUTOMATED DETECTION OF VITRITIS USING ULTRAWIDE-FIELD FUNDUS PHOTOGRAPHS AND DEEP LEARNING.

BACKGROUND/PURPOSE: Evaluate the performance of a deep learning algorithm for the automated detection and grading of vitritis on ultrawide-field imaging. METHODS: Cross-sectional noninterventional study. Ultrawide-field fundus retinophotographs of uveitis patients were used. Vitreous haze was defined according to the six steps of the Standardization of Uveitis Nomenclature classification. The deep learning framework TensorFlow and the DenseNet121 convolutional neural network were used to perform the classification task. The best fitted model was tested in a validation study. RESULTS: One thousand one hundred eighty-one images were included. The performance of the model for the detection of vitritis was good with a sensitivity of 91%, a specificity of 89%, an accuracy of 0.90, and an area under the receiver operating characteristics curve of 0.97. When used on an external set of images, the accuracy for the detection of vitritis was 0.78. The accuracy to classify vitritis in one of the six Standardization of Uveitis Nomenclature grades was limited (0.61) but improved to 0.75 when the grades were grouped into three categories. When accepting an error of one grade, the accuracy for the six-class classification increased to 0.90, suggesting the need for a larger sample to improve the model performances. CONCLUSION: A new deep learning model based on ultrawide-field fundus imaging that produces an efficient tool for the detection of vitritis was described. The performance of the model for the grading into three categories of increasing vitritis severity was acceptable. The performance for the six-class grading of vitritis was limited but can probably be improved with a larger set of images.

Multimodal imaging observation of primary vitreous cysts.

BACKGROUND: Primary vitreous cyst is a clinical variant delineated by the existence of a vesicle within the vitreous cavity from birth. This particular disease tends to be uncommon, and the underlying mechanisms contributing to its pathogenesis remain obscure. CASE PRESENTATION: A 37-year-old male patient manifested blurry vision and floaters in his right eye, a symptomology first noticed three months prior. Upon slit-lamp examination, a pigmented, round, 1 papilla diameter-sized mass was discerned floating in the vitreous. A meticulous examination of the floaters was conducted using an array of multimodal imaging techniques. Other potential conditions, including cysticercosis, toxoplasmosis, and tumors, were conclusively excluded through comprehensive diagnostic tests such as blood examinations, liver ultrasound, and cranial magnetic resonance imaging (MRI), resulting in the diagnosis of a primary vitreous cyst. The patient did not report any other discomforts and did not receive any subsequent interventions or treatments. CONCLUSION: We furnish an exhaustive case report of a patient diagnosed with a primary vitreous cyst. The incorporation of multimodal images in the characterization of the disease anticipates facilitating an enriched comprehension by medical practitioners.

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.

Advancements and turning point of artificial intelligence in ophthalmology: A comprehensive analysis of research trends and collaborative networks.

Artificial intelligence (AI) has emerged as a transformative force with great potential in various fields, including healthcare. In recent years, AI has garnered significant attention due to its potential to revolutionise ophthalmology, leading to advancements in patient care such as disease detection, diagnosis, treatment and monitoring of disease progression. This study presents a comprehensive analysis of the research trends and collaborative networks at the intersection of AI and ophthalmology. In this study, we conducted an extensive search of the Web of Science Core Collection to identify articles related to 'artificial intelligence' in ophthalmology published from 1968 to 2023. We performed co-occurrence keywords and co-authorship network analyses using VOSviewer software to explore the relationships between keywords and country collaboration. We found a remarkable surge in articles applying AI in ophthalmology after 2017, marking a turning point in the integration of AI within the medical field. The primary application of AI shifted towards the diagnosis of ocular disease, which was particularly evident through keywords such as glaucoma, diabetic retinopathy and age-related macular degeneration. Analysis of the collaboration networks of countries revealed a global expansion of ophthalmology-related AI research. This study provides valuable insights into the evolving landscape of AI integration in ophthalmology, indicating its growing potential for enhancing disease detection, diagnosis, treatment planning and monitoring of disease progression. In order to translate AI technologies into clinical practice effectively, it is imperative to comprehend the evolving research trends and advancements at the intersection of AI and ophthalmology.

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.

Ocular Manifestations of Multiple Sclerosis: A Population-Based Study.

BACKGROUND: To evaluate the population-based frequency and severity of multiple sclerosis (MS)-related ocular diseases. METHODS: Retrospective, population-based study examining patients with MS between January 1, 1998 and December 31, 2011. Patients were identified using the Rochester Epidemiology Project, which is a record-linkage system of medical records for all patient-physician encounters among Olmsted County, Minnesota residents. Diagnosis of MS was confirmed based on neuroimaging, cerebrospinal fluid studies, and serum studies for each patient according to the 2017 McDonald criteria. Patient data were obtained using the medical records and followed through April 1, 2018. RESULTS: Of the 116 patients with MS, 66% were female and the median age of onset was 36 years (interquartile range 27.5-43.5 years). About half (61/116, 53%) had MS-related neuro-ophthalmic manifestations during their disease course, and about one-fourth (33/116, 28%) had visual symptoms as their presenting symptom of MS, most commonly as optic neuritis (26/116, 22%). Optic neuritis was the leading MS-related ocular condition (37%), followed by internuclear ophthalmoplegia (16%) and nystagmus (13%). Optic neuritis was mostly unilateral (40/43, 93%), with 16% (6/43) having a visual acuity of 20/200 or worse at nadir but ultimately 95% (35/37) improving to a visual acuity of 20/40 or better. CONCLUSIONS: This study provides the population-based frequency of MS-related ocular disease, which demonstrates a high frequency of ocular manifestations in MS both at disease onset and during the disease course, emphasizing the utility of neuro-ophthalmologists, or collaboration between neurologists and ophthalmologists, in the care of patients with MS.

Smart Vision Transparency: Efficient Ocular Disease Prediction Model Using Explainable Artificial Intelligence.

The early prediction of ocular disease is certainly an obligatory concern in the domain of ophthalmic medicine. Although modern scientific discoveries have shown the potential to treat eye diseases by using artificial intelligence (AI) and machine learning, explainable AI remains a crucial challenge confronting this area of research. Although some traditional methods put in significant effort, they cannot accurately predict the proper ocular diseases. However, incorporating AI into diagnosing eye diseases in healthcare complicates the situation as the decision-making process of AI demonstrates complexity, which is a significant concern, especially in major sectors like ocular disease prediction. The lack of transparency in the AI models may hinder the confidence and trust of the doctors and the patients, as well as their perception of the AI and its abilities. Accordingly, explainable AI is significant in ensuring trust in the technology, enhancing clinical decision-making ability, and deploying ocular disease detection. This research proposed an efficient transfer learning model for eye disease prediction to transform smart vision potential in the healthcare sector and meet conventional approaches' challenges while integrating explainable artificial intelligence (XAI). The integration of XAI in the proposed model ensures the transparency of the decision-making process through the comprehensive provision of rationale. This proposed model provides promising results with 95.74% accuracy and explains the transformative potential of XAI in advancing ocular healthcare. This significant milestone underscores the effectiveness of the proposed model in accurately determining various types of ocular disease. It is clearly shown that the proposed model is performing better than the previously published methods.

Thermal mapping the eye: A critical review of advances in infrared imaging for disease detection.

Infrared thermography (IRT) has become more accessible due to technological advancements, making thermal cameras more affordable. Infrared thermal cameras capture the infrared rays emitted by objects and convert it into temperature representations. IRT has emerged as a promising and non-invasive approach for examining the human eye. Ocular surface temperature assessment based on IRT is vital for the diagnosis and monitoring of various eye conditions like dry eye, diabetic retinopathy, glaucoma, allergic conjunctivitis, and inflammatory diseases. A collective sum of 192 articles was sourced from various databases, and through adherence to the PRISMA guidelines, 29 articles were ultimately chosen for systematic analysis. This systematic review article seeks to provide readers with a thorough understanding of IRT's applications, advantages, limitations, and recent developments in the context of eye examinations. It covers various aspects of IRT-based eye analysis, including image acquisition, processing techniques, ocular surface temperature measurement, three different approaches to identifying abnormalities, and different evaluation metrics used. Our review also delves into recent advancements, particularly the integration of machine learning and deep learning algorithms into IRT-based eye examinations. Our systematic review not only sheds light on the current state of research but also outlines promising future prospects for the integration of infrared thermography in advancing eye health diagnostics and care.