Assessment of retinal and choroidal microvasculature in night shift medical workers by OCT angiography.

This study evaluated retinal and choroidal microvascular changes in night shift medical workers and its correlation with melatonin level. Night shift medical workers (group A, 25 workers) and non-night shift workers (group B, 25 workers) were recruited. The images of macula and optic nerve head were obtained by swept-source OCT-angiography. Vessel density of retina, choriocapillaris (CC), choriocapillaris flow deficit (CC FD), choroidal thickness (CT) and choroidal vascularity index (CVI) were measured. 6-sulfatoxymelatonin concentration was analyzed from the morning urine. CC FD and CVI were significantly decreased and CT was significantly increased in group A (all P < 0.05). 6-sulfatoxymelatonin concentration was significantly lower in group A (P < 0.05), which was significantly positively correlated with CC FD size (r = 0.318, P = 0.024) and CVI of the most regions (maximum r-value was 0.482, P < 0.001), and was significantly negatively associated with CT of all regions (maximum r-value was - 0.477, P < 0.001). In night shift medical workers, the reduction of melatonin was significantly correlated with CT thickening, CVI reduction and CC FD reduction, which suggested that they might have a higher risk of eye diseases. CC FD could be a sensitive and accurate indicator to reflect CC perfusion.

Assessment of retinal atrophy in mixed breed dogs using spectral domain optical coherence tomography (SD-OCT) and electroretinography.

The aim of the study was to characterize retinal atrophy (RA) with progressive retinal atrophy symptoms in mixed breed dogs using ophthalmoscopy, spectral domain optical coherence tomography (SD-OCT) and electroretinography (ERG).The study was performed on 13 mixed breed dogs affected by retinal atrophy (11 males and 2 females that were 1.5-14 years old). Depending on the advancement of RA, SD-OCT examinations identified retinal abnormalities ranging from layer disorganisation to advanced atrophy. The most advanced RA occurred ventral to the optic disc. Total retinal thickness in both eyes (mean ± SD) was lower in dogs with RA compared to controls dorsally (77.7 ± 39.5 µm vs 173.5 ± 13.3 µm), ventrally (33.4 ± 29.9 µm vs 139.5 ± 10.8 µm), nasally (65.0 ± 34.5 µm vs 163.9 ± 11.0 µm) and temporally (61.8 ± 41.7 µm vs 171.9 ± 11.1 µm) to the optic disc. In dogs with locally normal architecture of inner retina, loss of definition of outer retinal layers occurred in many regions. Dark and light-adapted ERGs were reduced in 2 dogs with RA and were unrecordable in 11 dogs. Lesions evident in SD-OCT scans of mixed breed dogs affected with retinal atrophy initially appear ventrally to the optic disc and ventro-dorsally in advanced RA. In all mixed breed dogs with retinal atrophy, clinical signs and SD-OCT results correlate with ERG findings.

Artificial intelligence in retinal screening using OCT images: A review of the last decade (2013-2023).

BACKGROUND AND OBJECTIVES: Optical coherence tomography (OCT) has ushered in a transformative era in the domain of ophthalmology, offering non-invasive imaging with high resolution for ocular disease detection. OCT, which is frequently used in diagnosing fundamental ocular pathologies, such as glaucoma and age-related macular degeneration (AMD), plays an important role in the widespread adoption of this technology. Apart from glaucoma and AMD, we will also investigate pertinent pathologies, such as epiretinal membrane (ERM), macular hole (MH), macular dystrophy (MD), vitreomacular traction (VMT), diabetic maculopathy (DMP), cystoid macular edema (CME), central serous chorioretinopathy (CSC), diabetic macular edema (DME), diabetic retinopathy (DR), drusen, glaucomatous optic neuropathy (GON), neovascular AMD (nAMD), myopia macular degeneration (MMD) and choroidal neovascularization (CNV) diseases. This comprehensive review examines the role that OCT-derived images play in detecting, characterizing, and monitoring eye diseases. METHOD: The 2020 PRISMA guideline was used to structure a systematic review of research on various eye conditions using machine learning (ML) or deep learning (DL) techniques. A thorough search across IEEE, PubMed, Web of Science, and Scopus databases yielded 1787 publications, of which 1136 remained after removing duplicates. Subsequent exclusion of conference papers, review papers, and non-open-access articles reduced the selection to 511 articles. Further scrutiny led to the exclusion of 435 more articles due to lower-quality indexing or irrelevance, resulting in 76 journal articles for the review. RESULTS: During our investigation, we found that a major challenge for ML-based decision support is the abundance of features and the determination of their significance. In contrast, DL-based decision support is characterized by a plug-and-play nature rather than relying on a trial-and-error approach. Furthermore, we observed that pre-trained networks are practical and especially useful when working on complex images such as OCT. Consequently, pre-trained deep networks were frequently utilized for classification tasks. Currently, medical decision support aims to reduce the workload of ophthalmologists and retina specialists during routine tasks. In the future, it might be possible to create continuous learning systems that can predict ocular pathologies by identifying subtle changes in OCT images.

Assessment of gaze direction during head and neck irradiation and dosimetric impact on the retina, macula and papilla in a cohort of 240 patients with paraoptic tumors.

In a prospective cohort of 240 paraoptic tumors patients treated with protons, there was 10° inter-individual gaze angle variability (up to 30°). In a random 21-patient subset with initial CTs versus and adaptive CTs, 6 (28.57 %) patients had at least twice a 10°-difference in their gaze angle, with > 5 Gy difference on the retina/macula or papilla in 2/21 (9.52 %) and 1/21 (4.76 %) based on cumulative dose from rescans, respectively.

Optical coherence tomography assessment of disease activity in cryopyrin-associated periodic syndrome.

BACKGROUND AND PURPOSE: Cryopyrin-associated periodic syndrome is a rare autoinflammatory disease caused by gain-of-function mutations or variants in the NLRP3 gene. Clinically, patients suffer from a broad spectrum of both systemic and neurological symptoms. The aim of this study was to determine whether systemic inflammation demonstrated by serum amyloid A (SAA) elevation is associated with neuroinflammation assessed by optical coherence tomography (OCT). METHODS: Thirty eyes of 15 patients with NLRP3 low penetrance mutations (PwNLRP3) and 20 eyes of 10 age- and sex-matched healthy controls were examined by spectral-domain OCT as part of routine clinical care. All retinal layers and clinical features were evaluated. RESULTS: At baseline no significant retinal neuroaxonal inflammation or degeneration was observed in all measured retinal layers amongst PwNLRP3 compared with healthy controls. In a pooled analysis of all individual OCT time points a significant difference regarding the macular retinal nerve fibre layer was detected. Increased levels of SAA showed a positive association with averaged combined outer plexiform layer and outer nuclear layer volumes (ρ < 0.0001, r2 = 0.35). CONCLUSION: In cryopyrin-associated periodic syndrome increased combined outer plexiform layer and outer nuclear layer volumes are mirrored by SAA increase, an acute phase reactant indicating systemic inflammation. Our findings identify OCT as a candidate biomarker to monitor subclinical neuroinflammation and to assess disease activity in PwNLRP3.

The socioeconomic epidemiology of inherited retinal diseases in Portugal.

BACKGROUND: Inherited retinal diseases (IRDs) are a group of rare degenerative disorders of the retina that can lead to blindness from birth to late middle age. Knowing the target population and its resources is essential to better plan support measures. The aim of this study was to evaluate the socioeconomic characteristics of regions in Portugal where IRD patients reside to inform the planning of vision aid and rehabilitation intervention measures. RESULTS: This study included 1082 patients from 973 families, aged 3 to 92 years, with a mean age of 44.8 ± 18.1 years. Patients living with an IRD were identified in 190 of the 308 municipalities. According to this study, the estimated IRD prevalence in Portugal was 10.4 per 100,000 inhabitants, and by municipalities, it ranged from 0 to 131.2 per 100,000 inhabitants. Overall, regions with a higher prevalence of IRD have a lower population density (r=-0.371, p < 0.001), a higher illiteracy rate (r = 0.404, p < 0.001) and an overall older population (r = 0.475, p < 0.001). Additionally, there is a lower proportion of doctor per capita (r = 0.350, p < 0.001), higher social security pensions beneficiaries (r = 0.439, p < 0.001), worse water quality for human consumption (r=-0.194, p = 0.008), fewer audiences at the cinema (r=-0.315, p < 0.001) and lower proportion of foreign guests in tourist accommodations (r=-0.287, p < 0.001). CONCLUSION: The number of identified patients with IRD varied between regions. Using data from national statistics (PORDATA), we observed differences in socioeconomic characteristics between regions. Multiple targeted aid strategies can be developed to ensure that all IRD patients are granted full clinical and socioeconomic support.

Chromatic vision and structural assessment in primary congenital glaucoma.

Primary congenital glaucoma is a rare disease that occurs in early birth and can lead to low vision. Evaluating affected children is challenging and there is a lack of studies regarding color vision in pediatric glaucoma patients. This cross-sectional study included 21 eyes of 13 children with primary congenital glaucoma who were assessed using the Farnsworth D-15 test to evaluate color vision discrimination and by spectral domain optical coherence tomography to measure retinal fiber layer thickness. Age, visual acuity, cup-to-disc ratio and spherical equivalent data were also collected. Global and sectional circumpapillary and macular retinal fiber layer thicknesses were measured and compared based on color vision test performance. Four eyes (19%) failed the color vision test with diffuse dyschromatopsia patterns. Only age showed statistical significance in color vision test performance. Global and sectional circumpapillary and macular retinal fiber layer thicknesses were similar between the color test outcomes dyschromatopsia and normal. While the color vision test could play a role in assessing children with primary congenital glaucoma, further studies are needed to correlate it with damage to retinal fiber layer thickness.

In Vivo Assessment of Retinal Phenotypes in Axenfeld-Rieger Syndrome.

Purpose: Axenfeld-Rieger syndrome (ARS) is characterized by ocular anomalies including posterior embryotoxon, iridocorneal adhesions, corectopia/iris hypoplasia, and developmental glaucoma. Although anterior segment defects and glaucoma contribute to decreased visual acuity, the role of potential posterior segment abnormalities has not been explored. We used high-resolution retinal imaging to test the hypothesis that individuals with ARS have posterior segment pathology. Methods: Three individuals with FOXC1-ARS and 10 with PITX2-ARS completed slit-lamp and fundus photography, optical coherence tomography (OCT), OCT angiography, and adaptive optics scanning light ophthalmoscopy (AOSLO). Quantitative metrics were compared to previously published values for individuals with normal vision. Results: All individuals demonstrated typical anterior segment phenotypes. Average ganglion cell and inner plexiform layer thickness was lower in PITX2-ARS, consistent with the glaucoma history in this group. A novel phenotype of foveal hypoplasia was noted in 40% of individuals with PITX2-ARS (but none with FOXC1-ARS). Moreover, the depth and volume of the foveal pit were significantly lower in PITX2-ARS compared to normal controls, even excluding individuals with foveal hypoplasia. Analysis of known foveal hypoplasia genes failed to identify an alternative explanation. Foveal cone density was decreased in one individual with foveal hypoplasia and normal in six without foveal hypoplasia. Two individuals (one from each group) demonstrated non-foveal retinal irregularities with regions of photoreceptor anomalies on OCT and AOSLO. Conclusions: These findings implicate PITX2 in the development of the posterior segment, particularly the fovea, in humans. The identified posterior segment phenotypes may contribute to visual acuity deficits in individuals with PITX2-ARS.

Longitudinal Assessment of OCT-Based Measures of Foveal Cone Structure in Achromatopsia.

Purpose: Achromatopsia (ACHM) is an autosomal recessive retinal disease associated with reduced or absent cone function. There is debate regarding the extent to which cone structure shows progressive degeneration in patients with ACHM. Here, we used optical coherence tomography (OCT) images to evaluate outer nuclear layer (ONL) thickness and ellipsoid zone (EZ) integrity over time in individuals with ACHM. Methods: Sixty-three individuals with genetically confirmed ACHM with follow-up ranging from about 6 months to 10 years were imaged using either Bioptigen or Cirrus OCT. Foveal cone structure was evaluated by assessing EZ integrity and ONL thickness. Results: A total of 470 OCT images were graded, 243 OD and 227 OS. The baseline distribution of EZ grades was highly symmetrical between eyes (P = 0.99) and there was no significant interocular difference in baseline ONL thickness (P = 0.12). The EZ grade remained unchanged over the follow-up period for 60 of 63 individuals. Foveal ONL thickness showed a clinically significant change in only 1 of the 61 individuals analyzed, although detailed adaptive optics imaging revealed no changes in cone density in this individual. Conclusions: ACHM appears to be a generally stable condition, at least over the follow-up period assessed here. As cones are the cellular targets for emerging gene therapies, stable EZ and ONL thickness demonstrate therapeutic potential for ACHM, although other aspects of the visual system need to be considered when determining the best timing for therapeutic intervention.

In-Depth Retinal Sensitivity Assessment With the MP3 Type S Microperimeter: A Methods Study.

Purpose: Retinal sensitivity is frequently listed as an end point in clinical trials, often with long working practices. The purpose of this methods study was to provide a new workflow and reduced test time for in-depth characterization of retinal sensitivity. Methods: A workflow for the MP3-S microperimeter with detailed functional characterization of the retina under photopic, mesopic, and scotopic conditions was evaluated. Grids of 32 and 28 test positions for photopic/mesopic and scotopic, respectively, were tested in 12 healthy individuals and compared with an established 68-point grid for test time, mean sensitivity (MS), and bivariate contour ellipse area (BCEA). Results: The mean test time (range; ±SD) was 10.5 minutes (8.4-14.9; ±2.0) in the 68-point grid and 4.3 minutes (3.8-5.0; ±0.4) in the 32-point grid, which was significantly different (P < 0.0001). The mean of difference in test time (±SD; 95% confidence interval) was 6.1 minutes (±2.0; 4.6-7.6). MS and BCEA were significantly correlated between grids (r = 0.89 and 0.74; P = 0.0005 and 0.014, respectively). Mean test time of subjects who underwent the full protocol (n = 4) was 2.15 hours. Conclusions: The protocol suggested herein appears highly feasible with in-depth characterization of retinal function under different testing conditions and in a short test time. Translational Relevance: The protocol described herein allows for characterization of the retina under different testing conditions and in a short test time, which is relevant due to its potential for patient prognostication and follow-up in clinical settings and also given its increasing role as a clinical trial end point.

Assessment of Time Lag Between Blood Flow, Retinal Nerve Fiber Layer Thickness and Visual Field Sensitivity Changes in Glaucoma.

Purpose: This study investigates the temporal relationship between blood flow changes and alterations in retinal nerve fiber layer thickness (RNFLT) and mean deviation (MD) in individuals with glaucoma. Methods: Blood flow, measured by mean blur rate in optic nerve head vessels (MBRv) and tissues (MBRt) using laser speckle flowgraphy (LSFG)-NAVI, was analyzed using structural equation models (SEMs). SEMs assessed whether the previous rate of one parameter predicted the current rate of the other parameter, adjusted for its own rate in the previous time interval. Data from 345 eyes of 174 participants were gathered from visits every six months. Results: Rates of change of both MBRv and MBRt were significantly predicted by their own rate in the previous time interval and by the rate of change of MD in the previous time interval (P < 0.001 and P = 0.043, respectively), but not by the rate of MD in the concurrent interval (P = 0.947 and P = 0.549), implying that changes in MD precede changes in blood flow. Rates of change of RNFLT were predicted by their own previous rate and the rate of change of MBRv and MBRt in either the previous interval (P = 0.002 and P = 0.008) or the concurrent interval (P = 0.001 and P = 0.018), suggesting that MBR may change before RNFLT. Conclusions: The evidence supports a temporal sequence where MD changes precede blood flow changes, which, in turn, may precede alterations in RNFLT.

Enhancing Retinal Fundus Image Quality Assessment With Swin-Transformer-Based Learning Across Multiple Color-Spaces.

Purpose: The assessment of retinal image (RI) quality holds significant importance in both clinical trials and large datasets, because suboptimal images can potentially conceal early signs of diseases, thereby resulting in inaccurate medical diagnoses. This study aims to develop an automatic method for Retinal Image Quality Assessment (RIQA) that incorporates visual explanations, aiming to comprehensively evaluate the quality of retinal fundus images (RIs). Methods: We developed an automatic RIQA system, named Swin-MCSFNet, utilizing 28,792 RIs from the EyeQ dataset, as well as 2000 images from the EyePACS dataset and an additional 1,000 images from the OIA-ODIR dataset. After preprocessing, including cropping black regions, data augmentation, and normalization, a Swin-MCSFNet classifier based on the Swin-Transformer for multiple color-space fusion was proposed to grade the quality of RIs. The generalizability of Swin-MCSFNet was validated across multiple data centers. Additionally, for enhanced interpretability, a Score-CAM-generated heatmap was applied to provide visual explanations. Results: Experimental results reveal that the proposed Swin-MCSFNet achieves promising performance, yielding a micro-receiver operating characteristic (ROC) of 0.93 and ROC scores of 0.96, 0.81, and 0.96 for the "Good," "Usable," and "Reject" categories, respectively. These scores underscore the accuracy of RIQA based on Swin-MCSF in distinguishing among the three categories. Furthermore, heatmaps generated across different RIQA classification scores and various color spaces suggest that regions in the retinal images from multiple color spaces contribute significantly to the decision-making process of the Swin-MCSFNet classifier. Conclusions: Our study demonstrates that the proposed Swin-MCSFNet outperforms other methods in experiments conducted on multiple datasets, as evidenced by the superior performance metrics and insightful Score-CAM heatmaps. Translational Relevance: This study constructs a new retinal image quality evaluation system, which will contribute to the subsequent research of retinal images.

Neuron-level explainable AI for Alzheimer's Disease assessment from fundus images.

Alzheimer's Disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia. Early diagnosis is critical for patients to benefit from potential intervention and treatment. The retina has emerged as a plausible diagnostic site for AD detection owing to its anatomical connection with the brain. However, existing AI models for this purpose have yet to provide a rational explanation behind their decisions and have not been able to infer the stage of the disease's progression. Along this direction, we propose a novel model-agnostic explainable-AI framework, called Granu la ̲ r Neuron-le v ̲ el Expl a ̲ iner (LAVA), an interpretation prototype that probes into intermediate layers of the Convolutional Neural Network (CNN) models to directly assess the continuum of AD from the retinal imaging without the need for longitudinal or clinical evaluations. This innovative approach aims to validate retinal vasculature as a biomarker and diagnostic modality for evaluating Alzheimer's Disease. Leveraged UK Biobank cognitive tests and vascular morphological features demonstrate significant promise and effectiveness of LAVA in identifying AD stages across the progression continuum.

Retinal imaging for the assessment of stroke risk: a systematic review.

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

Disparities Between Teleretinal Imaging Findings and Patient-Reported Diabetic Retinopathy Status and Follow-up Eye Care Interval: A 10-Year Prospective Study.

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

Comparison of cognitive workload and surgical outcomes between a three-dimensional and conventional microscope macular hole surgery.

BACKGROUND: Performing a surgical task subjects the surgeon to multitudinal stressors, especially with the newer 3D technology. The quantum of cognitive workload using this modern surgical system in comparison to the Conventional microscope system remains unexplored. We evaluate the surgeon's cognitive workload and the surgical outcomes of macular hole(MH) surgery performed on a 3D versus a Conventional microscope operating system. METHODS: 50 eyes of 50 patients with MH undergoing surgery using the 3D or Conventional microscope visualization system. Cognitive workload assessment was done by real-time tools(Surgeons' heart rate [HR] and oxygen saturation[SPO2]) and self-report tool(Surgery Task Load Index[SURG-TLX] questionnaire) of three Vitreoretinal surgeons. Based on the SURG-TLX questionnaire, an assessment of the workload was performed. RESULTS: Of the 50 eyes, 30 eyes and 20 eyes underwent surgery with the Conventional microscope and the 3D system, respectively. No difference was noted in the MH basal-diameter(p = 0.128), total surgical-duration(p = 0.299), internal-limiting membrane(ILM) peel time(p = 0.682), and the final visual acuity (VA; p = 0.515) between the two groups. Both groups showed significant improvement in VA(p < 0.001) with a 90% closure rate at one-month post-surgery. Cognitive workload comparison, the intraoperative HR(p = 0.024), total workload score(P = 0.005), and temporal-demand dimension(p = 0.004) were significantly more in Conventional microscope group as compared to 3D group. In both the groups, the HR increased significantly from the baseline while performing ILM peeling and at the end. CONCLUSION: The surgeon's cognitive workload is markedly reduced while performing macular hole surgery with a 3D viewing system. Moreover, duration of surgery including ILM peel time, MH closure rates, and visual outcomes remains unaffected irrespective of the operating microscope system.

Ophthalmologists' assessment of the handling characteristics of the novel Finesse Reflex Handle in comparison to those of a conventional handle.

Internal limiting membrane (ILM) peeling requires a delicate handling technique. It is also important that ophthalmologists can use the ILM forceps handle of their preference. This study objectively and subjectively evaluated the handling of the novel Finesse Reflex Handle (Reflex) in comparison with that of a conventional handle. The force required to close the forceps tips, evaluated using a digital force gauge, was significantly lesser for Reflex than for the conventional handle (3.14 ± 0.09 N vs. 3.84 ± 0.06 N, P < 0.001). Twenty-one ophthalmologists with various levels of experience answered a questionnaire after using both handles, and the total questionnaire score for Reflex was higher than that for the conventional handle (35.0 ± 3.7 vs. 30.0 ± 6.9, P = 0.01). Furthermore, the duration of experience as an ophthalmologist was negatively correlated with the vertical motion, assessed by video analysis, for the conventional handle (P = 0.02, r = - 0.50) but not for Reflex (P = 0.26). In conclusion, objective and subjective analyses revealed that compared with the conventional handle, the novel Reflex handle had more favourable handling characteristics. Most ophthalmologists preferred the handling of Reflex. Reflex may compensate for a lack of surgical experience.

Assessment of the relationship between structural and functional tests in patients with idiopathic intracranial hypertension.

PURPOSE: To assess the relationship between structural and functional tests in mild and moderate idiopathic intracranial hypertension (IIH). METHODS: Patients with mild and moderate IIH and a control group were enrolled. Best-corrected visual acuity (BCVA), macular ganglion cell layer (MGCL) thickness, peripapillary retinal nerve fiber layer (pp RNFL) thickness, perimetric mean deviation (MD), and photopic negative responses (PhNR) of the electroretinogram were recorded. The associations between structural (pp RNFL and MGCL thickness) and functional (PhNR amplitude, MD and BCVA) parameters were assessed. RESULTS: 154 eyes from 78 subjects (74 eyes from IIH patients and 80 eyes from healthy subjects) were included in this comparative observational study. The MGCL thickness, VA, pp RNFL, and PhNR base-to-trough (BT) amplitude were significantly worse in moderate IIH. The BCVA and MD were associated with MGCL thickness only in moderate IIH. The relationship between MD and MGCL thickness started when MD fell below -5.7 dB. CONCLUSIONS: The association between functional and structural parameters varies between mild and moderate IIH. The MD and MGCL thickness outperformed in assessing disease severity in mild and moderate IIH, respectively. The association between MD and MGCL thickness could be considered in IIH severity categorization.

Assessment of a Large Language Model's Responses to Questions and Cases About Glaucoma and Retina Management.

Importance: Large language models (LLMs) are revolutionizing medical diagnosis and treatment, offering unprecedented accuracy and ease surpassing conventional search engines. Their integration into medical assistance programs will become pivotal for ophthalmologists as an adjunct for practicing evidence-based medicine. Therefore, the diagnostic and treatment accuracy of LLM-generated responses compared with fellowship-trained ophthalmologists can help assess their accuracy and validate their potential utility in ophthalmic subspecialties. Objective: To compare the diagnostic accuracy and comprehensiveness of responses from an LLM chatbot with those of fellowship-trained glaucoma and retina specialists on ophthalmological questions and real patient case management. Design, Setting, and Participants: This comparative cross-sectional study recruited 15 participants aged 31 to 67 years, including 12 attending physicians and 3 senior trainees, from eye clinics affiliated with the Department of Ophthalmology at Icahn School of Medicine at Mount Sinai, New York, New York. Glaucoma and retina questions (10 of each type) were randomly selected from the American Academy of Ophthalmology's commonly asked questions Ask an Ophthalmologist. Deidentified glaucoma and retinal cases (10 of each type) were randomly selected from ophthalmology patients seen at Icahn School of Medicine at Mount Sinai-affiliated clinics. The LLM used was GPT-4 (version dated May 12, 2023). Data were collected from June to August 2023. Main Outcomes and Measures: Responses were assessed via a Likert scale for medical accuracy and completeness. Statistical analysis involved the Mann-Whitney U test and the Kruskal-Wallis test, followed by pairwise comparison. Results: The combined question-case mean rank for accuracy was 506.2 for the LLM chatbot and 403.4 for glaucoma specialists (n = 831; Mann-Whitney U = 27976.5; P < .001), and the mean rank for completeness was 528.3 and 398.7, respectively (n = 828; Mann-Whitney U = 25218.5; P < .001). The mean rank for accuracy was 235.3 for the LLM chatbot and 216.1 for retina specialists (n = 440; Mann-Whitney U = 15518.0; P = .17), and the mean rank for completeness was 258.3 and 208.7, respectively (n = 439; Mann-Whitney U = 13123.5; P = .005). The Dunn test revealed a significant difference between all pairwise comparisons, except specialist vs trainee in rating chatbot completeness. The overall pairwise comparisons showed that both trainees and specialists rated the chatbot's accuracy and completeness more favorably than those of their specialist counterparts, with specialists noting a significant difference in the chatbot's accuracy (z = 3.23; P = .007) and completeness (z = 5.86; P < .001). Conclusions and Relevance: This study accentuates the comparative proficiency of LLM chatbots in diagnostic accuracy and completeness compared with fellowship-trained ophthalmologists in various clinical scenarios. The LLM chatbot outperformed glaucoma specialists and matched retina specialists in diagnostic and treatment accuracy, substantiating its role as a promising diagnostic adjunct in ophthalmology.

Assessment of area and structural irregularity of retinal layers in diabetic retinopathy using machine learning and image processing techniques.

Diabetes retinopathy prevention necessitates early detection, monitoring, and treatment. Non-invasive optical coherence tomography (OCT) shows structural changes in the retinal layer. OCT image evaluation necessitates retinal layer segmentation. The ability of our automated retinal layer segmentation to distinguish between normal, non-proliferative (NPDR), and proliferative diabetic retinopathy (PDR) was investigated in this study using quantifiable biomarkers such as retina layer smoothness index (SI) and area (S) in horizontal and vertical OCT images for each zone (fovea, superior, inferior, nasal, and temporal). This research includes 84 eyes from 57 individuals. The study shows a significant difference in the Area (S) of inner nuclear layer (INL) and outer nuclear layer (ONL) in the horizontal foveal zone across the three groups (p < 0.001). In the horizontal scan, there is a significant difference in the smoothness index (SI) of the inner plexiform layer (IPL) and the upper border of the outer plexiform layer (OPL) among three groups (p < 0.05). There is also a significant difference in the area (S) of the OPL in the foveal zone among the three groups (p = 0.003). The area (S) of the INL in the foveal region of horizontal slabs performed best for distinguishing diabetic patients (NPDR and PDR) from normal individuals, with an accuracy of 87.6%. The smoothness index (SI) of IPL in the nasal zone of horizontal foveal slabs was the most accurate at 97.2% in distinguishing PDR from NPDR. The smoothness index of the top border of the OPL in the nasal zone of horizontal slabs was 84.1% accurate in distinguishing NPDR from PDR. Smoothness index of IPL in the temporal zone of horizontal slabs was 89.8% accurate in identifying NPDR from PDR patients. In conclusion, optical coherence tomography can assess the smoothness index and irregularity of the inner and outer plexiform layers, particularly in the nasal and temporal regions of horizontal foveal slabs, to distinguish non-proliferative from proliferative diabetic retinopathy. The evolution of diabetic retinopathy throughout severity levels and its effects on retinal layer irregularity need more study.