In Vivo Imaging of Rodent Retina in Retinal Disease.

High-quality imaging of the retina is crucial to the diagnosis and monitoring of disease, as well as for evaluating the success of therapeutics in human patients and in preclinical animal models. Here, we describe the basic principles and methods for in vivo retinal imaging in rodents, including fundus imaging, fluorescein angiography, optical coherence tomography, fundus autofluorescence, and infrared imaging. After providing a concise overview of each method and detailing the retinal diseases and conditions that can be visualized through them, we will proceed to discuss the advantages and disadvantages of each approach. These protocols will facilitate the acquisition of optimal images for subsequent quantification and analysis. Additionally, a brief explanation will be given regarding the potential results and the clinical significance of the detected abnormalities.

Evaluation of insomnia effect on ganglion cell complex, middle retina, and choroid.

PURPOSE: Insomnia is a common psychiatric disorder that has oxidative and degenerative effects on the brain. It is thought that the brain's processes affect the retina through their synaptic connections. However, the effects of sleep disorders on the retina and choroid are not fully understood. We aimed to investigate the impact of insomnia on retinal nerve fiber layer (RNFL), central foveal thickness, retinal layers, and choroidal thickness. METHODS: The right eye of 16 healthy controls and 15 patients with insomnia complaints for 3 months, no history of psychiatric drug use, and an Insomnia Severity Index (ISI) score of 15 or higher were included in the study. The retinal layers and RNFL analyses were performed using optical coherence tomography (OCT), and choroidal layers were analyzed using enhanced depth imaging OCT. RESULTS: Nasal and temporal ganglion cell complex thicknesses were significantly lower in patients with insomnia compared to the controls (97 µm vs. 111 µm P = 0.004; 94 µm vs. 105 µm P = 0.012, respectively). A significant negative correlation was detected between the ISI score and global RNFL thickness (rho, P = 0.03) Additionally, pachychoroid-like vascular structures were observed in choroidal images. CONCLUSION: These changes in the retina and the choroid layers due to insomnia may be precursors to retinal degenerative conditions, such as age-related macular degeneration that may occur in the future. Multicenter studies including more patients are needed to demonstrate the importance of quality sleep for eye health.

Establishing Clinical Trial Endpoints in Selecting Patients for RPGR Retinal Gene Therapy.

Purpose: Clinical trials for X-linked retinitis pigmentosa (RP) often assess retinal structure using optical coherence tomography (OCT) and function using microperimetry to evaluate initial eligibility and endpoints. Therefore, we seek to determine which parameters might be most sensitive in screening new patients for enrollment. Methods: Thirty-one patients (62 eyes) with confirmed retinitis pigmentosa GTPase regulator (RPGR) mutations attending Oxford Eye Hospital were included in this retrospective analysis. Outer retinal structure was investigated by measuring the remaining ellipsoid zone (EZ) and external limiting membrane (ELM) on OCT. Visual function was evaluated by using 10-2 microperimetry mean sensitivity. Results: The median age of patients with RPGR was 31 years (interquartile range [IQR] = 22-39 years). For the right and left eyes, respectively, the median EZ length through the foveal section was 921 µm (IQR = 607-1570) and 865 µm (IQR = 508-1442) and median ELM length was 2056 µm (IQR = 1336-2764) and 1860 µm (IQR = 1152-2680). Similarly, the median microperimetry sensitivity (MS) was 2.0 decibel (dB; IQR = 0.4-5.4) and 1.1 dB (IQR = 0.1-5.4). Linear mixed model regression analysis showed that EZ was significantly positively correlated to ELM (P < 0.001, R² = 0.931). EZ and ELM were significantly correlated with the microperimetry sensitivity with exponential relationship (P < 0.001, R² = 0.71 and 0.72, respectively). Using the exponential equation of regression line, EZ below approximately 600 µm (RE = 637 µm, 95% confidence interval [CI] = 397-877, LE = 586 µm, 95% CI = 356-817) results in microperimetry sensitivity of approximately 0 dB. There was high degree of inter-eye symmetry for progression of EZ, ELM, and microperimetry sensitivity. Age was significantly correlated with the analyzed parameters (P < 0.001), although with low R² for each of them. Discussion: EZ may comprise a surrogate biomarker for prediction of visual function in X-linked RP caused by mutations in RPGR and, in turn, identification of appropriate patients for enrollment in clinical trials. As expected, age plays a role in predicting potential biomarkers and visual function, however, it should not be used to preclude patients for gene therapy due to the poor correlation and heterogeneity of disease onset. Translational Relevance: Biomarkers of visual function in RPGR-associated RP may lead to identification of appropriate patients for enrollment in clinical trials.

AMD-SD: An Optical Coherence Tomography Image Dataset for wet AMD Lesions Segmentation.

Wet Age-related Macular Degeneration (wet AMD) is a common ophthalmic disease that significantly impacts patients' vision. Optical coherence tomography (OCT) examination has been widely utilized for diagnosing, treating, and monitoring wet AMD due to its cost-effectiveness, non-invasiveness, and repeatability, positioning it as the most valuable tool for diagnosis and tracking. OCT can provide clear visualization of retinal layers and precise segmentation of lesion areas, facilitating the identification and quantitative analysis of abnormalities. However, the lack of high-quality datasets for assessing wet AMD has impeded the advancement of related algorithms. To address this issue, we have curated a comprehensive wet AMD OCT Segmentation Dataset (AMD-SD), comprising 3049 B-scan images from 138 patients, each annotated with five segmentation labels: subretinal fluid, intraretinal fluid, ellipsoid zone continuity, subretinal hyperreflective material, and pigment epithelial detachment. This dataset presents a valuable opportunity to investigate the accuracy and reliability of various segmentation algorithms for wet AMD, offering essential data support for developing AI-assisted clinical applications targeting wet AMD.

Inner retinal layer thickness alterations in adult and pediatric patients with neurofibromatosis 1.

This study compared the thickness of each intraretinal layer in patients with neurofibromatosis 1 (NF1) and controls to analyze the association between intraretinal layer thickness and visual function. The macular spectral-domain optical coherence tomography volumetric dataset obtained from 68 eyes (25 adult eyes, 43 pediatric eyes) with NF1 without optic glioma and 143 control eyes (100 adult eyes, 43 pediatric eyes) was used for image auto-segmentation. The intraretinal layers segmented from the volumetric data included the macular retinal nerve fiber layer (RNFL), ganglion cell-inner plexiform layer (GCIPL), inner nuclear layer, outer plexiform layer, outer nuclear layer, and photoreceptor layer. Cases and controls were compared after adjusting for age, sex, refractive error, and binocular use. The association between retinal layer thickness and visual acuity was also analyzed. The GCIPL was significantly thinner in both adult and pediatric patients with NF1 compared with healthy controls. Average RNFL and GCIPL thicknesses were associated with visual acuity in adult patients with NF1. In pediatric patients, average GCIPL thickness was associated with visual acuity. These results suggest that changes in the inner retinal layer could be a biomarker of the structural and functional status of patients with NF1.

Relationship between binocular vision and Govetto's stage in monocular idiopathic epiretinal membrane.

Govetto's staging system (stages 1-4) for epiretinal membrane (ERM) based on optical coherence tomography images is a useful predictor of monocular visual function; however, an association between Govetto's stage and binocular vision has not been reported. This study aimed to investigate the factors associated with Govetto's stage among the monocular and binocular parameters. This retrospective study included consecutive patients with treatment-naïve eyes with unilateral ERM without pseudo-hole. We investigated Govetto's stage, degrees of aniseikonia and metamorphopsia, foveal avascular zone area, central retinal and choroidal thickness, vertical ocular deviation, stereopsis, and binocular single vision (BSV). We compared the parameters between the BSV-present and BSV-absent groups and investigated correlations between Govetto's stage and the monocular and binocular parameters. Twenty-eight eyes of 28 patients were examined (age, 66.6 ± 10.2 years). In multivariate correlation analyses, Govetto's stage correlated with BSV (P = 0.04, ß = - 0.36) and central retinal thickness (P < 0.001, ß = 0.74). Of the eyes, 18 were assigned to the BSV-present group and 10 to the BSV-absent group. Govetto's stage was significantly more advanced in the BSV-absent group than in the BSV-present group (3.2 ± 0.8 vs 2.5 ± 0.7, P = 0.03). Of the 28 patients, 11 (39%) showed small-angle vertical deviations (1-12Δ). In conclusion, our findings showed that Govetto's stage correlated with binocular vision in patients with monocular ERM. Govetto's staging is a useful parameter for predicting not only monocular but also binocular vision.

Evaluation of optical coherence tomography angiography and pattern and flash electroretinography in diabetes mellitus without retinopathy.

PURPOSE: To evaluate the findings and the correlation of optical coherence tomography angiography and pattern and flash electroretinography in diabetes mellitus without retinopathy. METHODS: Seventy-six eyes of 38 diabetic patients and age- and gender-matched control subjects were included in the study. The foveal avascular zone (FAZ), whole, foveal, parafoveal and perifoveal vascular densities of the superficial capillary plexus (SCP), deep capillary plexus (DCP) and choriocapillary plexus (CCP) layers were analyzed using optical coherence tomography angiography (OCTA). The amplitudes and implicit times of P50 and N95 waves of the pattern ERG (pERG) and the amplitudes and implicit times of the scotopic and photopic b-waves and oscillatory potentials (OP) of the flash ERG (fERG) tests were evaluated using the Metrovision brand monpack model device. RESULTS: The mean age of the patients was 59.7 ± 7.9 [range 43-79] years. Eighteen (47%) of the patients were female and 20 (53%) were male. The mean duration of diabetes was 7.45 ± 6.2 [range 1-20] years. No significant difference in FAZ area was found between study subjects and controls. Vascular density (VD) values of the superficial capillary plexus (SCP) layer were significantly lower (whole VD, 44.7 ± 3.3 vs. 46.6 ± 3.2%, p = 0.01, foveal VD 16.8 ± 6.4 vs. 24.9 ± 6.1%, p < 0.01, parafoveal VD 45.6 ± 4.5 vs. 47.1 ± 4.4%, p = 0.27 and perifoveal VD 45.5 ± 3.3 vs. 47.3 ± 3.1%, p = 0.01, respectively) in the diabetic group except the parafoveal area. VD measurements in deep and choriocapillary plexuses did not significantly differ between the groups (p > 0.05). ERG tests revealed significantly lower scotopic b-wave amplitudes (130.2 ± 39.3 µV vs.163.3 ± 47.8 µV, p < 0.01) and photopic b-wave amplitudes (83.2 ± 20.7 µV vs. 99.6 ± 29.4 µV, p < 0.01) in the diabetic patients. The implicit time of the photopic responses was significantly prolonged (28.9 ± 1.3 ms vs. 27.8 ± 2.1 ms, p = 0.01) in the patients. Oscillatory potentials in all components consisting of O1 to O4 and the sum of the OP potentials were lower in the diabetic group than the control subjects (p < 0.001). The P50 and N95 amplitudes and implicit times were comparable between the groups (p > 0.05). Correlation analysis showed a positive correlation between N95 amplitudes in pERG and the superficial vessel densities in OCTA (r = 0.26, p = 0.04). A negative correlation was found between photopic implicit times in fERG and the choriocapillary vessel densities (r=-0.27, p = 0.03). CONCLUSION: OCTA revealed decreased superficial vascular densities with the onset of the metabolic process of diabetes mellitus. As a result of these structural changes, lower scotopic and photopic amplitudes, decreased OP amplitudes, and prolonged implicit times in flash ERG were obtained.

Study of corneal and retinal thicknesses at five years after FS-LASIK and SMILE for myopia.

BACKGROUND: This study aimed to observe corneal and retinal thicknesses at 5 years after femtosecond laser-assisted in situ keratomileusis (FS-LASIK) and small incision lenticule extraction (SMILE) for myopia, investigate the effect of epithelial remodeling on refractive status and visual quality, and compare retinal thicknesses among fundus tessellation grades. METHODS: Patients who received FS-LASIK or SMILE 5 years before were enrolled in this cross-sectional study. After 1:1 propensity score matching, each surgical group obtained 177 patients (177 eyes). Examinations including visual acuity, refraction, corneal and retinal thicknesses, corneal higher-order aberrations (HOAs), and fundus photography were performed in this visit at 5 years after surgery. The Quality of Vision (QoV) questionnaire was used to assess visual symptoms and overall satisfaction. Corneal and retinal thicknesses between groups were compared, contributing factors were analyzed, and correlations with postoperative refractive status, HOAs, QoV scores and overall satisfaction were evaluated. RESULTS: The discrepancy of epithelial thickness between central and pericentral zones in FS-LASIK group was larger than that in SMILE group, which was negatively correlated with postoperative spherical equivalent (SE), positively correlated with spherical aberration (all P < 0.05), but not correlated with QoV scores and overall satisfaction (all P > 0.05) in both surgical groups. There was no statistical difference in stromal thickness and total corneal thickness (all P > 0.05). Most annuluses of epithelial and stromal thicknesse were linearly related to preoperative SE (all P < 0.05). The macular thickness, ganglion cell complex thickness, and retinal nerve fiber layer thickness exhibited comparable values between two surgical groups and four fundus tessellation grades, with no significant association observed with postoperative SE (all P > 0.05). CONCLUSION: The tendency that epithelial thickness in central zone was thicker than peripheral zone was more obvious at 5 years after FS-LASIK compared to SMILE. This uneven distribution of epithelial thickness might play a role in myopic regression and the changes in HOAs, especially in patients with high myopia, but it had little effect on patients' subjective visual quality and satisfaction. Retinal thicknesses were not affected by these two surgical methods, and they did not appear to be the clinical indicators for myopic regression or fundus tessellation progression.

Oculomic stratification of COVID-19 patients' intensive therapy unit admission status and mortality by retinal morphological findings.

To investigate if retinal thickness has predictive utility in COVID-19 outcomes by evaluating the statistical association between retinal thickness using OCT and of COVID-19-related mortality. Secondary outcomes included associations between retinal thickness and length of stay (LoS) in hospital. In this retrospective cohort study, OCT scans from 230 COVID-19 patients admitted to the Intensive Care Unit (ITU) were compared with age and gender-matched patients with pneumonia from before March 2020. Total retinal, GCL + IPL, and RNFL thicknesses were recorded, and analysed with systemic measures collected at the time of admission and mortality outcomes, using linear regression models, Pearson's R correlation, and Principal Component Analysis. Retinal thickness was significantly associated with all-time mortality on follow up in the COVID-19 group (p = 0.015), but not 28-day mortality (p = 0.151). Retinal and GCL + IPL layer thicknesses were both significantly associated with LoS in hospital for COVID-19 patients (p = 0.006 for both), but not for patients with pneumonia (p = 0.706 and 0.989 respectively). RNFL thickness was not associated with LoS in either group (COVID-19 p = 0.097, pneumonia p = 0.692). Retinal thickness associated with LoS in hospital and long-term mortality in COVID-19 patients, suggesting that retinal structure could be a surrogate marker for frailty and predictor of disease severity in this group of patients, but not in patients with pneumonia from other causes.

Applying Super-Resolution and Tomography Concepts to Identify Receptive Field Subunits in the Retina.

Spatially nonlinear stimulus integration by retinal ganglion cells lies at the heart of various computations performed by the retina. It arises from the nonlinear transmission of signals that ganglion cells receive from bipolar cells, which thereby constitute functional subunits within a ganglion cell's receptive field. Inferring these subunits from recorded ganglion cell activity promises a new avenue for studying the functional architecture of the retina. This calls for efficient methods, which leave sufficient experimental time to leverage the acquired knowledge for further investigating identified subunits. Here, we combine concepts from super-resolution microscopy and computed tomography and introduce super-resolved tomographic reconstruction (STR) as a technique to efficiently stimulate and locate receptive field subunits. Simulations demonstrate that this approach can reliably identify subunits across a wide range of model variations, and application in recordings of primate parasol ganglion cells validates the experimental feasibility. STR can potentially reveal comprehensive subunit layouts within only a few tens of minutes of recording time, making it ideal for online analysis and closed-loop investigations of receptive field substructure in retina recordings.

Gold Nanoparticles for Retinal Molecular Optical Imaging.

The incorporation of gold nanoparticles (GNPs) into retinal imaging signifies a notable advancement in ophthalmology, offering improved accuracy in diagnosis and patient outcomes. This review explores the synthesis and unique properties of GNPs, highlighting their adjustable surface plasmon resonance, biocompatibility, and excellent optical absorption and scattering abilities. These features make GNPs advantageous contrast agents, enhancing the precision and quality of various imaging modalities, including photoacoustic imaging, optical coherence tomography, and fluorescence imaging. This paper analyzes the unique properties and corresponding mechanisms based on the morphological features of GNPs, highlighting the potential of GNPs in retinal disease diagnosis and management. Given the limitations currently encountered in clinical applications of GNPs, the approaches and strategies to overcome these limitations are also discussed. These findings suggest that the properties and efficacy of GNPs have innovative applications in retinal disease imaging.

Assessment of Clinical Metadata on the Accuracy of Retinal Fundus Image Labels in Diabetic Retinopathy in Uganda: Case-Crossover Study Using the Multimodal Database of Retinal Images in Africa.

BACKGROUND: Labeling color fundus photos (CFP) is an important step in the development of artificial intelligence screening algorithms for the detection of diabetic retinopathy (DR). Most studies use the International Classification of Diabetic Retinopathy (ICDR) to assign labels to CFP, plus the presence or absence of macular edema (ME). Images can be grouped as referrable or nonreferrable according to these classifications. There is little guidance in the literature about how to collect and use metadata as a part of the CFP labeling process. OBJECTIVE: This study aimed to improve the quality of the Multimodal Database of Retinal Images in Africa (MoDRIA) by determining whether the availability of metadata during the image labeling process influences the accuracy, sensitivity, and specificity of image labels. MoDRIA was developed as one of the inaugural research projects of the Mbarara University Data Science Research Hub, part of the Data Science for Health Discovery and Innovation in Africa (DS-I Africa) initiative. METHODS: This is a crossover assessment with 2 groups and 2 phases. Each group had 10 randomly assigned labelers who provided an ICDR score and the presence or absence of ME for each of the 50 CFP in a test image with and without metadata including blood pressure, visual acuity, glucose, and medical history. Specificity and sensitivity of referable retinopathy were based on ICDR scores, and ME was calculated using a 2-sided t test. Comparison of sensitivity and specificity for ICDR scores and ME with and without metadata for each participant was calculated using the Wilcoxon signed rank test. Statistical significance was set at P<.05. RESULTS: The sensitivity for identifying referrable DR with metadata was 92.8% (95% CI 87.6-98.0) compared with 93.3% (95% CI 87.6-98.9) without metadata, and the specificity was 84.9% (95% CI 75.1-94.6) with metadata compared with 88.2% (95% CI 79.5-96.8) without metadata. The sensitivity for identifying the presence of ME was 64.3% (95% CI 57.6-71.0) with metadata, compared with 63.1% (95% CI 53.4-73.0) without metadata, and the specificity was 86.5% (95% CI 81.4-91.5) with metadata compared with 87.7% (95% CI 83.9-91.5) without metadata. The sensitivity and specificity of the ICDR score and the presence or absence of ME were calculated for each labeler with and without metadata. No findings were statistically significant. CONCLUSIONS: The sensitivity and specificity scores for the detection of referrable DR were slightly better without metadata, but the difference was not statistically significant. We cannot make definitive conclusions about the impact of metadata on the sensitivity and specificity of image labels in our study. Given the importance of metadata in clinical situations, we believe that metadata may benefit labeling quality. A more rigorous study to determine the sensitivity and specificity of CFP labels with and without metadata is recommended.

APPLICATIONS OF MULTIMODAL GENERATIVE ARTIFICIAL INTELLIGENCE IN A REAL-WORLD RETINA CLINIC SETTING.

PURPOSE: This study evaluates a large language model, Generative Pre-trained Transformer 4 with vision, for diagnosing vitreoretinal diseases in real-world ophthalmology settings. METHODS: A retrospective cross-sectional study at Bascom Palmer Eye Clinic, analyzing patient data from January 2010 to March 2023, assesses Generative Pre-trained Transformer 4 with vision's performance on retinal image analysis and International Classification of Diseases 10th revision coding across 2 patient groups: simpler cases (Group A) and complex cases (Group B) requiring more in-depth analysis. Diagnostic accuracy was assessed through open-ended questions and multiple-choice questions independently verified by three retina specialists. RESULTS: In 256 eyes from 143 patients, Generative Pre-trained Transformer 4-V demonstrated a 13.7% accuracy for open-ended questions and 31.3% for multiple-choice questions, with International Classification of Diseases 10th revision code accuracies at 5.5% and 31.3%, respectively. Accurately diagnosed posterior vitreous detachment, nonexudative age-related macular degeneration, and retinal detachment. International Classification of Diseases 10th revision coding was most accurate for nonexudative age-related macular degeneration, central retinal vein occlusion, and macular hole in OEQs, and for posterior vitreous detachment, nonexudative age-related macular degeneration, and retinal detachment in multiple-choice questions. No significant difference in diagnostic or coding accuracy was found in Groups A and B. CONCLUSION: Generative Pre-trained Transformer 4 with vision has potential in clinical care and record keeping, particularly with standardized questions. Its effectiveness in open-ended scenarios is limited, indicating a significant limitation in providing complex medical advice.

PREVALENCE OF DIDANOSINE-RELATED RETINAL TOXICITY AT AN URBAN ACADEMIC CENTER AS DIAGNOSED WITH ULTRA-WIDEFIELD IMAGING.

PURPOSE: Antiretroviral therapy has revolutionized HIV treatment with didanosine (DDI) as a pioneering drug. However, DDI has been associated with retinal toxicity, characterized by peripheral chorioretinal degeneration with macular sparing. Despite its clinical recognition, the prevalence and risk factors for didanosine-induced retinopathy are not well described. METHODS: This retrospective case series analyzed 127 DDI-treated patients at Weill Cornell Medicine Department of Ophthalmology. Inclusion criteria included at least 6 months of DDI use and available ultra-widefield imaging. Patients were categorized as affected or unaffected based on retinal imaging assessed by two reviewers. The affected group was further divided into "probable" or "possible" retinopathy. Patient demographics, DDI usage characteristics, and imaging findings were analyzed with statistical comparisons drawn between affected and unaffected cohorts. RESULTS: Of the 127 patients, 9 (7%) showed signs of didanosine-induced retinal toxicity. On average, the affected group was older compared with the unaffected group (65.1 vs. 56.5 years, P = 0.025), with lower BMI (23.2 vs. 27.4, P = 0.04), and older at the start of the treatment (51.6 vs. 40.8 years, P = 0.026). Mild phenotypes with peripheral pigmentary changes were also identified using ultra-widefield imaging. CONCLUSION: This pioneering academic study highlighted a notable prevalence of DDI-induced retinal toxicity. Statistical analysis demonstrated age, BMI, and age at treatment initiation as potential risk factors. Ultra-widefield autofluorescence emerged as a valuable tool in detecting and delineating findings. Follow-up studies are needed to determine the necessity of regular screening for individuals on or with a history of didanosine use.

VMseg: Using spatial variance to automatically segment retinal non-perfusion on OCT-angiography.

BACKGROUND AND OBJECTIVES: To develop and test VMseg, a new image processing algorithm performing automatic segmentation of retinal non-perfusion in widefield OCT-Angiography images, in order to estimate the non-perfusion index in diabetic patients. METHODS: We included diabetic patients with severe non-proliferative or proliferative diabetic retinopathy. We acquired images using the PlexElite 9000 OCT-A device with a photomontage of 5 images of size 12 x 12 mm. We then developed VMseg, a Python algorithm for non-perfusion detection, which binarizes a variance map calculated through convolution and morphological operations. We used 70% of our data set (development set) to fine-tune the algorithm parameters (convolution and morphological parameters, binarization thresholds) and evaluated the algorithm performance on the remaining 30% (test set). The obtained automatic segmentations were compared to a ground truth corresponding to manual segmentation from a retina expert and the inference processing time was estimated. RESULTS: We included 51 eyes of 30 patients (27 severe non-proliferative, 24 proliferative diabetic retinopathy). Using the optimal parameters found on the development set to tune the algorithm, the mean dice for the test set was 0.683 (sd = 0.175). We found a higher dice coefficient for images with a higher area of retinal non-perfusion (rs = 0.722, p < 10-4). There was a strong correlation (rs = 0.877, p < 10-4) between VMseg estimated non-perfusion indexes and indexes estimated using the ground truth segmentation. The Bland-Altman plot revealed that 3 eyes (5.9%) were significantly under-segmented by VMseg. CONCLUSION: We developed VMseg, an automatic algorithm for retinal non-perfusion segmentation on 12 x 12 mm OCT-A widefield photomontages. This simple algorithm was fast at inference time, segmented images in full-resolution and for the OCT-A format, was accurate enough for automatic estimation of retinal non-perfusion index in diabetic patients with diabetic retinopathy.

A cross-sectional study on the impact of hemodialysis duration on retinal nerve fiber layer thinning in hemodialysis patients.

This study aimed to investigate the relationship between hemodialysis duration (HDD) and retinal nerve fiber layer (RNFL) thickness. A total of 60 patients receiving maintenance hemodialysis and 67 healthy controls were analyzed. Spectral domain optical coherence tomography (SD-OCT) was employed to measure annular RNFL thicknesses. The hemodialysis group exhibited reduced temporal and inferior RNFL thicknesses relative to the control group. In hemodialysis patients, the inferior RNFL thickness was negatively correlated with HDD and positively correlated with intraocular pressure (IOP). Moreover, IOP was positively correlated with HDD. Mediation analysis showed that the negative correlation between HDD and inferior RNFL thickness was mediated by IOP. In conclusion, hemodialysis leads to temporal and inferior RNFL thinning, and the thickness reduction is proportional to hemodialysis duration. However, such changes are not induced by an increase in IOP.

Evaluation of thickness of individual macular retinal layers in diabetic eyes from optical coherence tomography.

The effect of diabetes mellitus (DM) on individual retinal layers remains incompletely understood. We evaluated the intra-retinal layer thickness alterations in 71 DM eyes with no diabetic retinopathy (DR), 90 with mild DR, and 63 with moderate DR without macular edema, using spectral-domain optical coherence tomography (SD-OCT) and the Iowa Reference Algorithm for automated retinal layer segmentation. The average thickness of 10 intra-retinal layers was then corrected for ocular magnification using axial length measurements, and pairwise comparisons were made using multivariable linear regression models adjusted for gender and race. In DM no DR eyes, significant thinning was evident in the ganglion cell layer (GCL; p < 0.001), inner nuclear layer (INL; p = 0.001), and retinal pigment epithelium (RPE; p = 0.014) compared to normal eyes. Additionally, mild DR eyes exhibited a thinner inner plexiform layer (IPL; p = 0.008) than DM no DR eyes. Conversely, moderate DR eyes displayed thickening in the INL, outer nuclear layer, IPL, and retinal nerve fiber layer (all p ≤ 0.002), with notably worse vision. These findings highlight distinctive patterns: early diabetic eyes experience thinning in specific retinal layers, while moderate DR eyes exhibit thickening of certain layers and slightly compromised visual acuity, despite the absence of macular edema. Understanding these structural changes is crucial for comprehending diabetic eye complications.

Evaluating the potential of retinal photography in chronic kidney disease detection: a review.

Background: Chronic kidney disease (CKD) is a significant global health concern, emphasizing the necessity of early detection to facilitate prompt clinical intervention. Leveraging the unique ability of the retina to offer insights into systemic vascular health, it emerges as an interesting, non-invasive option for early CKD detection. Integrating this approach with existing invasive methods could provide a comprehensive understanding of patient health, enhancing diagnostic accuracy and treatment effectiveness. Objectives: The purpose of this review is to critically assess the potential of retinal imaging to serve as a diagnostic tool for CKD detection based on retinal vascular changes. The review tracks the evolution from conventional manual evaluations to the latest state-of-the-art in deep learning. Survey Methodology: A comprehensive examination of the literature was carried out, using targeted database searches and a three-step methodology for article evaluation: identification, screening, and inclusion based on Prisma guidelines. Priority was given to unique and new research concerning the detection of CKD with retinal imaging. A total of 70 publications from 457 that were initially discovered satisfied our inclusion criteria and were thus subjected to analysis. Out of the 70 studies included, 35 investigated the correlation between diabetic retinopathy and CKD, 23 centered on the detection of CKD via retinal imaging, and four attempted to automate the detection through the combination of artificial intelligence and retinal imaging. Results: Significant retinal features such as arteriolar narrowing, venular widening, specific retinopathy markers (like microaneurysms, hemorrhages, and exudates), and changes in arteriovenous ratio (AVR) have shown strong correlations with CKD progression. We also found that the combination of deep learning with retinal imaging for CKD detection could provide a very promising pathway. Accordingly, leveraging retinal imaging through this technique is expected to enhance the precision and prognostic capacity of the CKD detection system, offering a non-invasive diagnostic alternative that could transform patient care practices. Conclusion: In summary, retinal imaging holds high potential as a diagnostic tool for CKD because it is non-invasive, facilitates early detection through observable microvascular changes, offers predictive insights into renal health, and, when paired with deep learning algorithms, enhances the accuracy and effectiveness of CKD screening.

Multimodal Eye Imaging, Retina Characteristics, and Psychological Assessment Dataset.

The eyes provide insights into psychology, potentially offering a distinctive perspective for psychological health profiles. However, there exist a notable deficiency in datasets that simultaneously encompass eye features and psychological assessments. To address this gap, our study presents a dataset that included Fundus Photography, Psychological Assessment, Retina Characteristics, and Multimodal Imaging (FPRM). FPRM dataset comprise fundus images at different wavelengths (548 nm and 605 nm), image of oxygen saturation for the retina and 8 specific retinal vessels, videos of retinal blood flow and pupillary light reflex, along with 61 items of multimodal quantitative measurement from 384 participants. Additionally, it features psychological assessments across five dimensions (geriatric depression, generalized anxiety disorder, insomnia, activities of daily living, and deterioration), accompanied by fundus photographs and 6 items of retina characteristics from 1683 participants. FPRM dataset is the first to integrate multimodal ophthalmic data and psychological assessments, not only advancing the development of machine learning applications but also facilitating in-depth research into the relationship between eye health and psychological health profiles.