BACKGROUND:Despite an extensive armamentarium, the long-term prognosis of heart failure remains poor, and its pathophysiology is still not fully understood. Microvascular function is impaired early in the development of HF and linked to disease progression. Retinal imaging provides a unique opportunity for fast, non-invasive and affordable detection of early systemic microvascular disease. AIM:To provide a systematic overview of current literature regarding retinal microvascular changes in HF. METHODS:A literature search was performed using MEDLINE, EMBASE, Web of Science and Cochrane Library (Registration number: INPLASY202450114). Studies on retinal microvascular changes, visualized by fundus photography, adaptive optics, optical coherence tomography, scanning laser Doppler flowmetry and dynamic vessel analysis in patients with HF were included. RESULTS:Twenty-four articles were included for qualitative analysis. Compared to healthy controls, patients with HF consistently exhibited reduced flicker light-induced dilation of retinal arterioles and venules, as well as decreased vessel density around the optic nerve head. More limited evidence suggests an increase in arteriolar wall thickness and wall cross-sectional area. Findings supporting other structural changes in the retinal microvessels were inconsistent. The pathophysiology behind retinal vascular abnormalities in HF and their correlation with HF severity remain incompletely understood. Nevertheless, retinal imaging holds promise for identifying individuals at risk of developing HF and predicting prognosis. Overall, analysis of retinal microvascular structure and function could serve as a valid surrogate marker for future interventional studies in HF. CONCLUSION:This review provides a systematic overview on retinal imaging as a promising tool in the prevention, risk stratification and management of HF, and as a surrogate marker in clinical trials.

BACKGROUND:To compare the safety and efficacy of trabeculectomy, PRESERFLO MicroShunt (PRESERFLO) and XEN45 Gel Stent (XEN) in patients with open-angle glaucoma (OAG) during the first year. METHODS:A single-centre retrospective case-control study included 384 eyes undergoing standalone glaucoma surgery (2013-2020). Propensity score matching was used to balance baseline covariates. The primary outcome was surgical success at 1 year. Complete success was two-fold defined as an IOP of 6-15 or 6-18 mmHg, without loss of light perception, additional glaucoma surgery or IOP-lowering medication; qualified success allowed medication and/or selective laser trabeculoplasty. Secondary outcomes included IOP, best-corrected visual acuity, medication use and complications/interventions. RESULTS:We included 117 in the trabeculectomy, 82 eyes in the PRESERFLO group and 185 in the XEN group. Complete success was lower after XEN for both IOP criteria (44.0%, IOP 6-18 mmHg and 41.5%, IOP 6-15 mmHg) compared to trabeculectomy (59.8% and 59.3%, respectively; p < 0.05) and PRESERFLO (73.5% and 73.3%, respectively; p < 0.001). All procedures effectively and comparably reduced IOP to 12.3 ± 4.1 mmHg (trabeculectomy), 12.7 ± 3.5 mmHg (PRESERFLO), 13.4 ± 4.3 mmHg (XEN). The proportion of drop-free patients was higher after PRESERFLO (81.0% vs. 58.6% and 56.6%, after trabeculectomy and XEN, respectively). Significant hypotony was uncommon and comparably so. Minor post-operative interventions were more common in trabeculectomy patients compared with PRESERFLO and XEN. CONCLUSION:This study suggests equal success rates for PRESERFLO and trabeculectomy, both outperforming XEN at 1 year, with fewer post-operative interventions for PRESERFLO compared to trabeculectomy. Overall complication rates were comparable across groups.

BACKGROUND:Identifying patients with glaucoma who are at risk of rapid disease progression is crucial to preventing vision loss. We aimed to develop and externally validate G-PROG, a deep learning model that predicts 2-5-year glaucoma progression from baseline colour fundus photographs (CFPs). METHODS:G-PROG was trained and validated on data from a single centre (UZ Leuven, Leuven, Belgium); the other datasets (Brussels, Belgium; Liège, Belgium; Tampere, Finland; Mainz, Germany; and Hangzhou, China) served as external test sets. Across six glaucoma departments, we analysed 161 827 fundus images from 127 962 visits (13 913 patients), totalling 128 021 eye-years of follow-up. Progression was defined by the G-RISK slope, calculated via within-eye linear regression on longitudinal G-RISK predictions over follow-up intervals of 2-5 years. G-RISK is a previously validated deep learning model that quantifies glaucomatous optic nerve damage from CFPs. We trained 20 G-PROG configurations with varying inclusion criteria applied to the number of visits, image quality, time between visits, and G-RISK at baseline. Performance was evaluated using the area under the receiver operating characteristic curve (AUC), the coefficient of determination (R2), and explained variance score (EVS). G-RISK slope as a progression biomarker was validated against the visual field mean deviation (MD) slope and average retinal nerve fibre layer thickness (RNFL) slope. FINDINGS:Significant AUC values were obtained in 18 out of 20 model configurations, with internal validation reaching a maximum AUC of 0·98 (95% CI 0·97-1·00) across follow-up intervals (2-5 years). In glaucomatous eyes with a baseline G-RISK exceeding 0·6, the maximum AUC was 0·92 (0·85-0·98). For external validation, the predictions from the eight top-performing configurations (selected based on positive R2 and minimal discrepancy between R2 and EVS in internal validation) were averaged. Maximum AUC values ranged from 0·74 to 0·86 across the five test datasets. G-RISK slope showed significant agreement with established progression markers, with maximum AUCs of 0·82 for MD slope and 1·00 for average RNFL slope. INTERPRETATION:Externally validated across five international cohorts, G-PROG predicts 2-5-year glaucoma progression from baseline CFPs. Prospective evaluation is warranted to assess whether G-PROG can improve risk stratification and resource allocation in glaucoma care. FUNDING:This work was funded and supported by grants from the National Medical Research Council, National Research Foundation Singapore, National Health Innovation Centre Singapore, SingHealth and Duke-NUS, Duke-NUS, the Singapore Eye Research Institute and Nanyang Technological University and the Singapore Eye Research Institute, the Competitive Research Funding of the Pirkanmaa Wellbeing Services County, the LUX-Foundation for Glaucoma Research, state funding for university-level health research at Tampere University Hospital, Wellbeing Services County of Pirkanmaa, the Tampere University Hospital Support Foundation, and the Belgian Ophthalmology Cooperation in Clinical Sciences initiative hosted by the Funds for Research in Ophthalmology.

Background/Objectives: To compare the five-year efficacy and safety of the 63 µm (XEN63) vs. 45 µm (XEN45) XEN® Gel Stent in patients with open-angle glaucoma (OAG). Methods: This retrospective matched (1:1) cohort study included adults with OAG who underwent standalone ab interno implantation of the XEN63 or the XEN45 between 2014 and 2021 at a tertiary referral center in Belgium. The primary outcome was IOP at five years. The secondary outcomes included surgical success, topical medication use, postoperative hypotony, complications and interventions. Results: Thirty eyes of 30 patients (15 XEN63 and 15 XEN45) were analyzed. The baseline characteristics were comparable. At five years, the mean IOP did not differ between the XEN63 and the XEN45 (11.5 vs. 11.0 mmHg; p = 0.54). The XEN63 demonstrated higher complete success rates than the XEN45 for both the IOP < 18 mmHg (10 vs. four eyes; p = 0.016) and <15 mmHg criteria (10 vs. three eyes; p = 0.003). The topical medication use was low and comparable (0.6 vs. 0.9 medications; p = 0.57). The numerical (13 vs. five eyes; p = 0.008) and symptomatic (six vs. two eyes; p = 0.2) hypotony were more frequent after the XEN63 implantation. The two eyes with XEN63 and none with XEN45 experienced clinically significant hypotony. The needling procedures and secondary glaucoma surgeries were more frequent after the XEN45. Conclusions: The XEN63 implantation was associated with higher long-term success rates and also with a higher incidence of early postoperative hypotony. These findings indicate a trade-off between efficacy and safety and suggest that careful patient selection and postoperative management are essential when considering larger lumen subconjunctival drainage devices.

Glaucomatous optic neuropathy (GON), affecting an estimated 64.3 million people globally, causes irreversible vision loss when not detected early. Traditional diagnosis requires time-consuming ophthalmic examinations by specialists. Recent deep learning models for automating GON detection from colour fundus photographs (CFP) have shown promise but often suffer from limited generalizability across different ethnicities, disease groups and examination settings. To address these limitations, we introduce GONet, a robust deep learning model developed using seven independent datasets, including over 119 000 CFPs with gold-standard annotations and from patients of diverse geographic backgrounds. GONet consists of a DINOv2 pre-trained self-supervised vision transformer fine-tuned using a multisource domain strategy. GONet demonstrated high out-of-distribution generalizability, with an AUC of 0.88-0.99 in target domains. GONet performance was similar or superior to state-of-the-art works and the cup-to-disc ratio, by up to 18.4%. GONet is available via Lirot.ai (www.aimlab-technion.com/lirot-ai). We also contribute a new dataset consisting of 747 CFPs with GON labels as open access, available at https://doi.org/10.13026/pdxv-m215.

IntroductionPrimary open-angle glaucoma (POAG) is a leading cause of irreversible blindness worldwide. Although intraocular pressure (IOP) reduction remains the cornerstone of management, increasing attention has focused on physical activity (PA) and structured exercise as potential adjunct strategies. Exercise induces systemic physiological adaptations, including changes in systemic vascular health, autonomic regulation, and perfusion dynamics, which may influence glaucoma pathophysiology and ocular health beyond IOP-dependent pathways.MethodsThis scoping review was conducted in accordance with PRISMA-ScR guidelines. MEDLINE, Embase, and SPORTDiscus were systematically searched from database inception to 13 June 2024. Eligible studies investigated associations or effects of PA or exercise on POAG-related outcomes, including ophthalmological parameters, systemic vascular markers, and patient-reported outcomes. All study designs were considered. Data were extracted and synthesized narratively across predefined clinical domains: incidence, progression, disease severity, and quality of life.ResultsEighteen studies met the inclusion criteria (14 observational, 4 randomized controlled trials). Aerobic exercise interventions were consistently associated with short-term reductions in IOP and increases in ocular perfusion pressure. Observational evidence suggested that higher habitual PA was associated with lower glaucoma prevalence, reduced incidence, and slower disease progression. However, findings across studies were heterogeneous, and no study directly evaluated disease severity or vision-related quality of life. Methodological limitations included inconsistent outcome definitions, inadequate patient characterization, reliance on self-reported PA, and short follow-up durations.ConclusionCurrent evidence suggests that higher levels of PA are associated with more favorable POAG-related outcomes, potentially mediated through both IOP-dependent and systemic vascular mechanisms affecting ocular perfusion. However, causal inference remains limited. Future research should prioritize adequately powered, long-term randomized trials incorporating objective PA assessment and comprehensive ophthalmological and patient-reported outcomes to clarify the role of exercise in glaucoma prevention and management.

Background/Objectives: Although advances in understanding glaucoma have been made, early detection remains challenging due to the asymptomatic nature of the disease. The Metabolomics In Surgical Ophthalmological Patients (MISO) study previously demonstrated that aqueous humor (AH) metabolomics can distinguish glaucoma patients from controls. We aimed to determine if the metabolic profile of AH has predictive power for overall survival and glaucoma progression after surgery. Methods: Glaucoma patients (n = 34) were retrospectively analyzed and classified into progression categories based on surgical and medical interventions and assessed for survival. Results: Glutamine and α-ketoglutarate were significantly associated with glaucoma progression, while N-acetylglutamate, lysine, and creatine correlated with mortality. These metabolites are linked to excitotoxicity, mitochondrial dysfunction, and oxidative stress, highlighting their potential role in glaucoma pathophysiology. Conclusions: These results suggest that metabolomic profiling of AH could provide valuable biomarkers for predicting surgical outcomes and overall survival, paving the way for individualized therapeutic approaches. Further studies are required to confirm these findings before they can be integrated into clinical practice.

BACKGROUND/AIMS:Minimally invasive glaucoma surgery (MIGS) procedures are commonly combined with phacoemulsification to provide additional intraocular pressure (IOP) and/or topical medication reduction in patients with mild-to-moderate glaucoma. This study compared the 1-year efficacy and safety of excimer laser trabeculostomy (ELIOS) versus trabecular micro-bypass stenting (iStent inject and iStent inject W), both performed in combination with cataract surgery. METHODS:This multicentre retrospective cohort study included patients undergoing combined phacoemulsification with either ELIOS (Phaco-ELIOS) or iStent implantation (Phaco-iStent) at three European centres between 2020 and 2025. The primary endpoint was IOP at 12 months postoperatively. Secondary endpoints included longitudinal IOP and medication use, surgical success, adverse events and the need for secondary glaucoma surgery. Longitudinal outcomes were analysed using multiple imputation. RESULTS:A total of 343 eyes were included (164 Phaco-ELIOS and 179 Phaco-iStent), with 1-year follow-up available in 70%. Mean IOP decreased by 21.6% for Phaco-ELIOS and 20.7% for Phaco-iStent and remained stable through 12 months (p=0.74). Both procedures were associated with a similar reduction in postoperative topical glaucoma medications (0.56 vs 0.41; p=0.2). With Phaco-ELIOS, a higher proportion of eyes achieved medication reduction (46.4% vs 31.3%; p=0.02). Rates of adverse events and secondary glaucoma surgery were low and comparable in both groups. CONCLUSION:Phaco-ELIOS and Phaco-iStent provided comparable 1-year IOP reduction and overall safety. Phaco-ELIOS showed a greater number of patients with topical medication reduction, supporting its role as an effective combined MIGS option in patients undergoing cataract surgery.

Alzheimer’s disease (AD) pathology is increasingly recognized to manifest in the retina, offering a non-invasive window for early biomarker discovery. This proof-of-concept study investigated whether multimodal retinal imaging—hyperspectral imaging (HSI), optical coherence tomography (OCT), and color fundus photography (CFP)—can differentiate individuals with and without cerebral amyloid-beta (Aβ) pathology in 40 participants with PET-confirmed Aβ status (17 Aβ+, cognitively normal or with mild cognitive impairment; 23 Aβ− cognitively normal controls). HSI-derived gray-level co-occurrence matrix (GLCM) texture, OCT-derived ganglion cell–inner plexiform layer (GC-IPL) thickness, and CFP-derived vascular biomarkers (VBMs) were extracted, and logistic regression with leave-one-out cross-validation assessed classification performance per modality, alone and combined; the cohort was supplemented with AD dementia patients for an exploratory cross-sectional comparison across disease-stage groups. HSI showed nominally lower GLCM correlation at 466 nm in Aβ+ participants, most pronounced in the inferior macula (AUC = 0.72). GC-IPL thickness showed a similar inferior-predominant regional pattern. Combining HSI and GC-IPL features yielded the best performance (AUC = 0.84; sensitivity = 0.82; specificity = 0.78), although this improvement over the unimodal models did not reach statistical significance, whereas vascular biomarkers contributed minimally. In an exploratory cross-sectional comparison across AD stage groups drawn from two cohorts, HSI features showed a non-monotonic pattern, decreasing in early Aβ+ stages and rising again in dementia. These findings provide preliminary evidence of complementary information between HSI and OCT for detecting retinal biomarkers of early-stage AD, supporting multimodal retinal imaging as a scalable screening approach warranting validation in larger, longitudinal cohorts.

Aims/Purpose: Challenges in modeling rates of visual field (VF) progression relate to flooring effects and sensitivity to inclusion criteria like follow‐up (FU) duration. We explored the relationship between VF progression and age, disease severity, and FU duration in primary open angle glaucoma (POAG).Methods: Mean Deviation (MD) of 655 POAG eyes of 424 patients from the UZ Leuven Glaucoma Clinic with at least 5 VFs and 2 years of follow‐up were used. Baseline severity was defined as Above 0 (≥0dB), mild ( < 0 and ≥‐6dB), moderate ( < ‐6 and ≥‐12dB), advanced ( < ‐12 and ≥‐15dB), and severe ( < ‐15dB) disease. Linear mixed models and changepoint detection were used. Sensitivity analysis of modeled progression rates within each severity group was done by varying maximally included duration of FU.Results: MD progression rates per year were ‐0.34dB (p < 0.001) for Above 0, ‐0.49dB (p < 0.001) for mild, ‐0.49dB (p < 0.001) for moderate, ‐0.26dB (p = 0.009) for advanced, and +0.1dB (p = 0.317) for severe POAG. Random effects correlation between baseline MD and progression rates was 0.36. The fixed effects for age and test related learning effect were non‐significant (p = 0.65) and ‐0.21 (p = 0.004) respectively. The correlation between the implied slope and baseline age was ‐0.26. Changepoint analysis showed that group level progression estimates stabilized when minimum FU times were at least 2.17, 1.99, 2.18, and 4.56 years for mild, moderate, advanced and severe POAG respectively.Conclusions: Older patients progress faster across severity levels and a significant learning effect is present when excluding patients with severe POAG. Excluding patients with a baseline MD above 0dB, the modeled average MD change is similar between mild and moderate POAG. Less progression is observed in advanced and no progression in severe POAG, consistent with the flooring effect. In mild and moderate POAG patients progression estimates converged after a minimum FU of at least 2 years.

Aims/Purpose: Alzheimer's disease (AD), the leading cause of dementia, affects millions, underscoring the need for early diagnostic methods. The retina, which can exhibit AD‐related pathological processes, offers a promising diagnostic site. This study aims to utilize Hyperspectral Retinal Imaging (HSRI) to differentiate between positive (+) and negative (‐) PET‐amyloid beta (Aβ) status. Within this cohort, a subset is Aβ+ while remaining cognitively healthy, indicating preclinical amyloid accumulation. Unlike most research targeting later symptomatic stages, our approach could facilitate interventions before clinically apparent neurodegeneration occurs. Methods: Data was used from 37 Aβ‐ and 25 Aβ+ individuals of which 8 with mild cognitive impairment (MCI). HSRI were captured using an easy‐to‐use hyperspectral snapshot camera, covering a spectral range of 460–630 nm. Images were taken from primary, inferior, and superior views of the retina, with further regions of interest (ROI) defined in the primary view. After preprocessing, these spectra were used to train machine learning classifiers [1]. Results: The best classifier performance was observed using XGBoost with the superior spectra (AUC = 0.72), and using a Linear Discriminant Analysis classifier in superior quadrants (S1 AUC = 0.74, S2 AUC = 0.68). Lower performance in other ROI underscored the variability in amyloid deposition across the retina, correlating with previous findings that retinal Aβ deposits in AD patients are frequently concentrated in the superior quadrants. Conclusions: We were able to achieve similar performance of previous research in AD patients [1], but in a preclinical cohort of cognitively normal participants up to MCI patients. Consistent with the literature, the superior retinal regions seem most discriminative for Aβ status. Further exploration of the specificity of the HSRI signal will pave the way for early AD detection, potentially improving outcomes through earlier therapeutic intervention. Reference S. Lemmens et al ., ‘Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer's disease patients’, Alzheimer's Research & Therapy , vol. 12, no. 1, p. 144, Nov. 2020, doi: 10.1186/s13195‐020‐00715‐1.

Aims/Purpose: Dynamic Vessel Analysis (DVA) is a non‐invasive imaging modality that evaluates the reactivity of retinal arteriolar and venular vessels in response to flicker light stimulation. This study aims to introduce a novel data‐processing pipeline that involves noise reduction techniques localized to different locations along the vessel wall. Additionally, it employs standardized parameter extraction, allowing for a more precise assessment of retinal vessel responses across these locations. Methods: Previous studies used robust principal component analysis (RPCA) on averaged time series data for arteries and veins, combining one averaged time series per patient into arterial and venous matrices. Our method retains individual location time series for each arteriole and venule, preserving local responses. We combine these individual time series into arteriolar and venular matrices and apply RPCA, resulting in sparse matrices containing noise and low‐rank matrices capturing common features. The low‐rank matrices, containing the noise‐reduced information, are then used for further analysis. This approach maintains the granularity of local vascular responses. Results: We identified and integrated key parameters from existing literature to delineate vasodilation and vasoconstriction profiles. By applying analysis of covariance (ANCOVA) for age, sex, baseline vessel dilation, and mean arterial pressure, we identified significantly lower Baseline‐Corrected Flicker Response of the proximal retinal venules in normal tension glaucoma patients (2.46%, n = 23) compared to healthy controls (4.23%, n = 21, p = 0.049). Conclusions: Our novel pipeline adds to all previously published methods and effectively identified altered neurovascular responses in glaucoma patients after the necessary adjustments. This standardized and automated approach is a promising catalysator for DVA research, offering a more localized and precise understanding of retinal vascular dynamics.

Aims/Purpose: Deriving vascular features of retinal images is a proposed noninvasive method to assess vascular health. Although several studies have linked cardiovascular risk to retinal image features, they often rely on limited datasets or have used deep learning approaches with limited explainability. This research introduces an end‐to‐end method for analyzing the retinal vasculature in large retinal image datasets, applied for primary open angle glaucoma (POAG).Methods: 115,237 retinal images of the UZ Leuven Glaucoma Clinic were extracted. 4858 unique images remain of POAG patients (n = 3010) and controls (n = 1848) after image quality assessment, optic disk detection, region of interest definition, automated segmentation of arterioles and venules (LUNet algorithm), and parametrization of the vascular biomarkers (PVBM toolbox). Analysis of covariance and linear mixed models were used to adjust for age, sex and disc size.Results: Both arteriolar and venular diameter, area, length, tortuosity, branching angle, endpoints, intersection points and both mono‐ as multifractal dimension levels are independently lower in POAG patients and older patients (all p < 0.001), after adjustment for sex, disc size and multiple testing. The multivariate linear mixed models additionally show that the vascular features are significantly influenced by sex and disc size, which necessitates correct adjustment.Conclusions: This is the first time a fully automated end‐to‐end pipeline is published for the analysis of retinal vascular geometry in a large cohort (n = 4858). Given the independent similarities in retinal vascular geometry changes between older age and POAG prevalence the theory of pronounced vascular ageing in POAG patients is proposed. This novel approach enables quantitative analysis of eye vasculature and supports the study of its correlation with specific diseases, facilitating reproducible analysis of large datasets and providing explainability to deep learning approaches.

Generalization in medical segmentation models is challenging due to limited annotated datasets and imaging variability. To address this, we propose Retinal Layout-Aware Diffusion (RLAD), a novel diffusion-based framework for generating controllable layout-aware images. RLAD conditions image generation on multiple key layout components extracted from real images, ensuring high structural fidelity while enabling diversity in other components. Applied to retinal fundus imaging, we augmented the training datasets by synthesizing paired retinal images and vessel segmentations conditioned on extracted blood vessels from real images, while varying other layout components such as lesions and the optic disc. Experiments demonstrated that RLAD-generated data improved generalization in retinal vessel segmentation by up to 8.1 present REYIA, a comprehensive dataset comprising 586 manually segmented retinal images. To foster reproducibility and drive innovation, both our code and dataset will be made publicly accessible.

Objective: To develop and validate an automated end-to-end methodology for analyzing retinal vasculature in large datasets of digital fundus images (DFIs), aiming to assess the influence of demographic and clinical factors on retinal microvasculature. Design: This study employs a retrospective cohort design to achieve its objectives. Participants: The research utilized a substantial dataset consisting of 32 768 DFIs obtained from individuals undergoing routine eye examinations. There was no inclusion of a separate control group in this study. Methods: The proposed methodology integrates multiple stages: initial image quality assessment, detection of the optic disc (OD), definition of the region of interest surrounding the OD, automated segmentation of retinal arterioles and venules, and the engineering of digital biomarkers representing vasculature characteristics. To analyze the impact of demographic variables (age, sex) and clinical factors (disc size, primary open-angle glaucoma [POAG]), statistical analyses were performed using linear mixed-effects models. Main Outcome Measures: The primary outcomes measured were changes in the retinal vascular geometry. Special attention was given to evaluating the independent effects of age, sex, disc size, and POAG on the newly engineered microvasculature biomarkers. Results: The analysis revealed significant independent similarities in the retinal vascular geometry alterations associated with both advanced age and POAG. These findings suggest a potential mechanism of accelerated vascular aging in patients with POAG. Conclusions: This novel methodology allows for the comprehensive and quantitative analysis of retinal vasculature, facilitating the investigation of its correlations with specific diseases. By enabling the reproducible analysis of extensive datasets, this approach provides valuable insights into the state of retinal vascular health and its broader implications for cardiovascular and ocular health. The software developed through this research will be made publicly available upon publication, offering a critical tool for ongoing and future studies in retinal vasculature. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The aim of this literature study is to investigate the specific visual field defects for each glaucoma subtype and evaluate their pattern of progression. A systematic search was performed in accordance with the PRISMA guidelines in Medline (via PubMed), Embase, Web of Science, and the Cochrane Library on January 23, 2024. The literature search identified 3332 records after deduplication. Sixty-nine articles were included after screening and assessment for eligibility. Specific visual field patterns for primary open-angle glaucoma, normal-tension glaucoma, primary angle-closure glaucoma, and juvenile open-angle glaucoma were summed up. Since the search results on visual field progression only covered primary open-angle glaucoma and normal-tension glaucoma, the further analysis was confined to these glaucoma subtypes. This systematic review summarizes the literature concerning visual field patterns in glaucoma for the ophthalmologist.

The Leuven-Haifa dataset contains 240 disc-centered fundus images of 224 unique patients (75 patients with normal tension glaucoma, 63 patients with high tension glaucoma, 30 patients with other eye diseases and 56 healthy controls) from the University Hospitals of Leuven. The arterioles and venules of these images were both annotated by master students in medicine and corrected by a senior annotator. All senior segmentation corrections are provided as well as the junior segmentations of the test set. An open-source toolbox for the parametrization of segmentations was developed. Diagnosis, age, sex, vascular parameters as well as a quality score are provided as metadata. Potential reuse is envisioned as the development or external validation of blood vessels segmentation algorithms or study of the vasculature in glaucoma and the development of glaucoma diagnosis algorithms. The dataset is available on the KU Leuven Research Data Repository (RDR).