The SYN-OCT dataset contains a total of 200,000 synthetic cross-sectional circumpapillary optical coherence tomography (OCT) images, comprising of 100,000 images from a generative image model for glaucoma eyes and 100,000 from a generative image model for healthy normal eyes. The generative image models were developed using real OCT imaging data acquired from study participants at the Singapore Eye Research Institute, and were trained with the respective real images from glaucoma or healthy eyes. Structural characteristics of the synthetic data were validated and found to be comparable with the real data using an automated segmentation approach. These measurements are provided together with the synthetic images. We envision this dataset to be useful for the development or validation of deep learning applications for glaucoma analysis and detection, and as a dataset to study the synthetic generation of medical images and their usability. This dataset is publicly available.

Purpose:The purposes of this study were to assess whether optic nerve head (ONH) biomechanics, quantified by tissue strain, improves classification of progressive visual field (VF) loss patterns in glaucoma beyond morphology, and to use saliency maps to identify ONH regions associated with the predictions. Methods:We recruited 249 patients with glaucoma (mean age 69 ± 5 years, 54% female patients). One eye per subject was imaged under (1) primary gaze and (2) primary gaze with IOP elevated to approximately 35 millimeters of mercury (mm Hg) via ophthalmo-dynamometry. Twelve subjects were excluded due to poor scan quality/limited lamina cribrosa (LC) visibility. Experts classified subjects into four categories based on the presence of specific visual field defects (VFDs): (1) superior nasal step (N = 26), (2) superior partial arcuate (N = 62), (3) full superior hemifield defect (N = 25), and (4) other/non-specific defects (N = 124). Automatic segmentation and digital volume correlation computed neural tissue and LC strains. Biomechanical and structural features were input to a PointNet model. Three classification tasks were performed to detect: (1) superior nasal step, (2) superior partial arcuate, and (3) full superior hemifield defect. Data were split 80/20 (train/test). Area under the curve (AUC) assessed performance. Saliency maps (an explainable artificial intelligence [XAI] technique) highlighted ONH regions most critical to classification. Results:Models achieved AUCs of 0.77 to 0.88 across VFD classifications. The structure-only model reached an AUC of 0.83 ± 0.02 for superior arcuate defects, which significantly improved to 0.87 ± 0.02 (P < 0.05) with the addition of strain information, demonstrating that ONH biomechanics enhance prediction beyond morphology. Strain-sensitive regions were localized to the inferior and inferotemporal rim, expanding with increasing severity of VF loss. Conclusions:ONH strain enhances classification of glaucomatous VF loss patterns. The neuroretinal rim, rather than the LC, was most critical, suggesting rim strain may play a dominant role in axonal injury and functional loss.

Wide-field optical coherence tomography (OCT) imaging can enable monitoring of peripheral changes in the retina, beyond the conventional fields of view used in current clinical OCT imaging systems. However, wide-field scans can present significant challenges for retinal layer segmentation. Deep Convolutional Neural Networks (CNNs) have shown strong performance in medical imaging segmentation but typically require large-scale, high-quality, pixel-level annotated datasets to be effectively developed. To address this challenge, we propose an advanced semi-supervised learning framework that combines the detailed capabilities of convolutional networks with the broader perspective of transformers. This method efficiently leverages labelled and unlabelled data to reduce dependence on extensive, manually annotated datasets. We evaluated the model performance on a dataset of 74 volumetric OCT scans, each performed using a prototype swept-source OCT system following a wide-field scan protocol with a 15 x 9 mm field of view, comprising 11,750 labelled and 29,016 unlabelled images. Wide-field retinal layer segmentation using the semi-supervised approach show significant improvements (P-value < 0.001) of up to 11% against a UNet baseline model. Comparisons with a clinical spectral-domain-OCT system revealed significant correlations of up to 0.91 (P-value < 0.001) in retinal layer thickness measurements. These findings highlight the effectiveness of semi-supervised learning with cross-teaching between CNNs and transformers for automated OCT layer segmentation.

The emergence and advancements in glaucoma treatment modalities have expanded the options available to clinicians, particularly for patients with mild to moderate glaucoma. These newer approaches, such as minimally invasive glaucoma surgeries and selective laser trabeculoplasty, aim to effectively reduce intraocular pressure and potentially improve patient outcomes. 'Interventional glaucoma' reflects a paradigm shift in the glaucoma management strategies and involves adopting a more proactive approach and offering these interventions at earlier stages of the disease. By administering them earlier, these interventions can modulate the course of the disease and prevent significant visual loss, thereby reducing or delaying the need for subsequent filtering surgeries. In this review, we discuss the need for interventional glaucoma and the evidence behind these interventional techniques. We highlight key considerations that should be considered when implementing interventional glaucoma approaches in the Asian context.

Purpose:To classify eyes as slow or fast glaucoma progressors in patients with primary angle closure glaucoma (PACG) using an integrated approach combining optic nerve head (ONH) structural features and sector-based visual field (VF) functional parameters. Design:Retrospective longitudinal study. Participants:PACG patients from glaucoma clinics. Methods:PACG patients with ≥5 reliable VF tests over ≥5 years were included. Progression was assessed in Zeiss Forum, with baseline VF within six months of OCT. Fast progression was VFI decline <-2.0% per year; slow progression ≥-2.0% per year. OCT volumes were AI-segmented to extract 31 ONH parameters. The Glaucoma Hemifield Test defined five regions per hemifield, aligned with RNFL distribution. Mean sensitivity per region was combined with structural parameters to train ML classifiers. Multiple models were tested, and SHAP identified key predictors. Main outcome measures:Classification of slow versus fast progressors using combined structural and functional data. Results:We analyzed 451 eyes from 299 patients. Mean VFI progression was -0.92% per year; 369 eyes progressed slowly and 82 rapidly. The Random Forest model combining structural and functional features achieved the best performance (AUC = 0.87±0.02, 2000 Monte Carlo iterations). SHAP identified six key predictors: inferior MRW, inferior and inferior-temporal RNFL thickness, nasal-temporal LC curvature, superior nasal VF sensitivity, and inferior RNFL and GCL+IPL thickness. Models using only structural or functional features performed worse with AUC of 0.82±0.03 and 0.78±0.03, respectively. Conclusions:Combining ONH structural and VF functional parameters significantly improves classification of progression risk in PACG. Inferior ONH features, MRW and RNFL thickness, were the most predictive, highlighting the critical role of ONH morphology in monitoring disease progression.

Background/ AimsThe lack of context for anterior segment optical coherence tomography (ASOCT) measurements impedes its clinical utility. We established the normative distribution of anterior chamber depth (ACD), area (ACA) and width (ACW) and lens vault (LV), and applied percentile cut-offs to detect primary angle closure disease (PACD; ≥180° posterior trabecular meshwork occluded).MethodsWe included subjects from the Singapore Chinese Eye Study with ASOCT scans. Eyes with ocular surgery or laser procedures, and ocular trauma were excluded. A deep-learning algorithm was used to obtain Visante ASOCT (Carl Zeiss Meditec, USA) measurements. Normative distribution was established using 80% of eyes with open angles. Multivariable logistic regression was performed on 80% open and 80% angle closure eyes. Diagnostic performance was evaluated using 20% open and 20% angle closure eyes.ResultsWe included 2157 eyes (1853 open angles; 304 angle closure) for analysis. ACD, ACA and ACW decreased with age and were smaller in females, and vice versa for LV (all p<0.022). ACD 20th percentile and LV 85th percentile had a balanced accuracy of 84.4% and 84.2% in detecting PACD, respectively. When combined, ACD 20th and LV 85th percentile had 88.68% sensitivity and 88.85% specificity in detecting PACD as compared with a multivariable regression model (ACA, angle opening distance, LV, iris area) with 88.33% sensitivity and 83.75% specificity.ConclusionAnterior chamber parameters varied with age and gender. The ACD 20th and LV 85th percentile values may be used in silos or in combination to detect PACD in the absence of more sophisticated classification algorithms.

GWAS of primary angle-closure glaucoma have identified eight loci conferring risk in Asian populations. However, it remains unclear whether the genetic risk factors for the disease are consistent across different populations. Here, we present a discovery GWAS for primary angle-closure glaucoma in Europeans using the UK Biobank. We replicate our findings in six independent European populations and compare these results with results from 14 Asian cohorts. Five genomic regions in the discovery cohort are associated at genome-wide significance, including two loci previously identified in Asian cohorts. We next meta-analyse the discovery and replication cohorts to identify six additional novel loci, all previously associated with refractive error. Mendelian randomisation provides evidence for a causal role of shorter axial length and hypermetropic refractive error on primary angle-closure glaucoma. A polygenic risk score derived from the European ancestry meta-analysis demonstrates significant associations with quantitative ocular traits - including a shallower anterior chamber and higher intraocular pressure - in the independent EPIC-Norfolk cohort. Finally, a multi-ancestry meta-analysis of all 21 European and Asian cohorts identifies 12 further novel loci. This work shows that genetic factors associated with a darker iris and hypermetropia confer risk for primary angle-closure glaucoma.

PURPOSE:To evaluate the proportion of patients with, and anatomic predictors of, persistent angle closure 5 years after laser peripheral iridotomy (LPI) in primary angle-closure suspect and to assess anterior segment (AS) anatomic changes over the 5-year follow-up. DESIGN:Subanalysis of randomized controlled trial (the Singapore Asymptomatic Narrow Angles Laser Iridotomy Study). PARTICIPANTS:Of the 480 patients, 375 patients with phakia completed the 5-year follow-up, and 130 patients had complete imaging. METHODS:All patients underwent LPI in 1 randomly selected eye. The proportion of eyes with persistent gonioscopic angle closure (≥ 2 quadrants), its predictors, and the changes in biometric parameters were evaluated. MAIN OUTCOME MEASURES:Odds ratio (OR; with 95% confidence interval [CI]) for predictors. RESULTS:Among 375 participants with 5 years of follow-up, persistent gonioscopic angle closure occurred in 124 LPI-treated eyes (33.1%). At 5 years, LPI significantly reduced the risk of persistent gonioscopic angle closure (OR, 0.12 [95% CI, 0.09-0.17]; P < 0.001). In the imaging cohort (n = 130), 34 eyes (26.2%) had persistent gonioscopic angle closure, a proportion not significantly different from that of the entire cohort (P = 0.17). In multivariable analysis, greater iris thickness measured at 750 μm from the scleral spur (IT750) at baseline (per 0.1 mm; OR, 1.71 [95% CI, 1.21-2.57]; P = 0.004) and younger age at baseline (per 10 years; OR, 0.30 [95% CI, 0.13-0.61]; P = 0.002) were associated with persistent angle closure, whereas lower mean gonioscopic grade was borderline significant (per grade, OR, 0.35 [95% CI, 0.12-1.00]; P = 0.050). Additional analysis showed that greater IT750 was associated significantly with persistent angle closure only in eyes with baseline angle opening distance at 500 μm from the scleral spur below the median (P = 0.005). Angle width (P < 0.001 for all) increased within 2 years after LPI and remained stable thereafter. CONCLUSIONS:In approximately two-thirds of patients, LPI induces sustained angle widening. A thicker iris at baseline in eyes with a narrower angle was predictive of persistent angle closure despite treatment. FINANCIAL DISCLOSURE(S):The author(s) have no proprietary or commercial interest in any materials discussed in this article.

OBJECTIVE:To identify subgroups of angle closure disease by considering age-independent anterior segment parameters. METHODS:Anterior-segment optical coherence tomography (ASOCT) was performed in primary angle closure suspect (PACS) and primary angle closure glaucoma (PACG) patients. Clustering analysis using age-independent parameters, anterior chamber width (ACW), anterior vault (AV), posterior corneal arc length (PCAL), and iris area was performed. The optimum number of subgroups was determined using Bayesian Information Criterion and subjects were classified into subgroups by Gaussian Mixture Model methods. RESULTS:A total of 650 PACS and 411 PACG were analysed. The optimal number of subgroups of the combined PACS and PACG dataset was 3. Subgroup 1 (n = 186, 29.3%) has the largest anterior chamber dimension with large AV and total anterior chamber area, subgroup 2 (n = 16, 2.5%) has the widest ACW and shallowest anterior chamber depth (ACD), and subgroup 3 (n = 432; 68.1%) has large iris area with the smallest anterior chamber dimensions, characterised by a small ACW, AV, and PCAL. Subgroup 3 comprised a significantly greater proportion of PACG compared to PACS (74.2% vs 64.6%, p = 0.04) while subgroup 1 had the greatest proportion of PACS ≥ 70 years old, yet to have progressed to PACG. CONCLUSION:We identified 3 subgroups of angle closure eyes, each characterised by distinct structural components based on ASOCT. A greater proportion of older PACS yet to have progressed to PACG belonging to the subgroup with the largest anterior chamber dimensions suggests that a more spacious anterior chamber may be associated with PACS that remains stable.

PRÉCIS:Interocular comparison of primary angle closure glaucoma subjects with asymmetrical and symmetrical visual field loss, revealed significantly thinner central corneal thickness and higher presenting intraocular pressure in the worse eye of the asymmetrical group. PURPOSE:To compare the interocular clinical and biometric parameters of primary angle closure glaucoma (PACG) with asymmetrical and symmetrical visual-field loss at presentation. PATIENT AND METHODS:A retrospective study in which the following clinical data were extracted: presenting intraocular pressure (IOP), gonioscopy, visual-field mean deviation (MD), central corneal thickness (CCT), anterior chamber depth (ACD), and axial length (AL). Asymmetrical PACG was defined as the inter-eye visual-field MD difference >6 dB, symmetrical PACG <3 dB, and those with inter-eye differences between 3 and 6 dB were excluded. Linear mixed effects model was used to adjust for the interdependence of the right and left eyes. RESULTS:Of 243 PACG subjects, 122 (50.3%) presented with asymmetrical, and 69 (28.4%) with symmetrical disease. The worse eyes in subjects with asymmetrical PACG had significantly higher presenting IOP ( P <0.001), narrower angles ( P <0.001), more myopic refraction ( P <0.001), and thinner CCT (529.2±36.1 vs. 535.8±38.5 μm; P <0.001) compared with the fellow eyes; but no inter-eye differences were observed for AL ( P =0.93) and ACD ( P =0.53). In symmetric PACG, no significant inter-eye differences were observed for CCT (532.3±33.1 vs. 533.1±34.6 μm, P =0.67), AL ( P =0.85) and ACD ( P =0.18), but the relatively worse eye had higher presenting IOP ( P =0.003). In the stepwise multiple linear regression analysis in the asymmetrical group, CCT was the only significant variable ( P =0.006), explaining 12% of the variability of the visual-field MD of the worse eye. CONCLUSIONS:In asymmetrical PACG, worse eyes have thinner CCT and higher presenting IOP. Difference in CCT could either be inherent or acquired, and more tests would be needed to tease that out.

Précis: Approximately 38% of 467 asymptomatic primary angle closure glaucoma subjects had severe visual field loss (<−20 dB) at first presentation. Gender-based differences in prevalence and biometry suggests the need for an integrated approach for assessing risk. Purpose: To compare the clinical characteristics of patients with asymptomatic primary angle-closure glaucoma (PACG) across varying disease severity at presentation. Methods: Of 681 PACG patients recruited, 196 were excluded due to acute primary angle-closure and 18 due to pre-treatment. Clinical data from 467 patients were analysed, including age at presentation, presenting intraocular pressure (IOP), pre-intervention gonioscopy, vertical cup-to-disc ratio, biometry, pre-surgery refractive data, and visual field (VF) mean deviation (MD) at presentation (excluding the first VF). Disease severity was classified based on the VF MD as early-to-moderate (≥−12 dB), advanced (−12.01 to −20 dB), and severe (<−20 dB). Results: Of the 467 patients, 304 had reliable VFs within 1.5 years of presentation and were categorized as early-to-moderate (n=129; 42.4%), advanced (n=57; 18.8%) and severe PACG (n=118; 38.8%). Mean age at presentation was 64.7±8.6 years and 52.6% were male. Patients with severe PACG were more likely to be male (61.9%), with the highest presenting IOP ( P <0.001), and narrowest anterior chamber angle ( P <0.001). Significantly smaller anterior chamber depth and shorter axial length across worsening disease severity were only observed in female but not in male subjects. There was no significant difference in mean age at presentation across groups ( P =0.12). Presenting IOP of ≤21 mm Hg was observed in 49.1% (n=28) advanced and 29.7% (n=35) severe PACG. Conclusions: Similar age at presentation of severe PACG and those with less severe disease suggests that the severe group either developed PACG at an earlier age or underwent rapid disease progression. Gender-based differences of prevalence and biometry may also impact disease risk.

Primary angle-closure glaucoma is a major cause of irreversible blindness worldwide afflicting >20 million people. Through whole exome sequencing, we analysed the association between gene-based burden of rare, protein-altering genetic variants and disease risk in 4,667 affected individuals and 5,473 unaffected controls. We tested genes surpassing exome-wide significance (P < 2.5 × 10-6) for replication in a further 2,519 cases and 472,189 controls. We observed carriers of rare, protein-altering variants at UBOX5 (observed in 154 out of 7,186 affected individuals [2.1%] and in 3,975 out of 477,197 unaffected controls [0.83%]) to be associated with 2.13-fold increased risk of PACG (95%ci, 1.69 - 2.69; P = 1.25 × 10-10). We performed substrate trapping assays coupled with mass spectrometry and observed Binding Immunoglobulin Protein (BIP) as a key substrate for UBOX5. Biological assays showed UBOX5 acts by ubiquitinating BIP. We evaluated the functional status of 35 UBOX5 variants and observed that functionally deficient variants were enriched in affected individuals compared to controls. We validated this finding in an independent collection where 3 persons carrying functionally deficient variants were observed out of 208 cases (1.4%), whereas none were observed in 600 controls. Our findings suggest the UBOX5-BIP signalling pathway might be involved in biology of primary angle-closure glaucoma.

Purpose:To use finite element (FE) analysis to assess what morphologic and biomechanical factors of the iris and anterior chamber are more likely to influence angle narrowing during pupil dilation. Methods:The study consisted of 1344 FE models comprising the cornea, sclera, lens, and iris to simulate pupil dilation. For each model, we varied the following parameters: anterior chamber depth (ACD = 2-4 mm) and anterior chamber width (ACW = 10-12 mm), iris convexity (IC = 0-0.3 mm), iris thickness (IT = 0.3-0.5 mm), stiffness (E = 4-24 kPa), and Poisson's ratio (v = 0-0.3). We evaluated the change in (△∠) and the final dilated angles (∠f) from baseline to dilation for each parameter. Results:The final dilated angles decreased with a smaller ACD (∠f = 53.4° ± 12.3° to 21.3° ± 14.9°), smaller ACW (∠f = 48.2° ± 13.5° to 26.2° ± 18.2°), larger IT (∠f = 52.6° ± 12.3° to 24.4° ± 15.1°), larger IC (∠f = 45.0° ± 19.2° to 33.9° ± 16.5°), larger E (∠f = 40.3° ± 17.3° to 37.4° ± 19.2°), and larger v (∠f = 42.7° ± 17.7° to 34.2° ± 18.1°). The change in angles increased with larger ACD (△∠ = 9.37° ± 11.1° to 15.4° ± 9.3°), smaller ACW (△∠ = 7.4° ± 6.8° to 16.4° ± 11.5°), larger IT (△∠ = 5.3° ± 7.1° to 19.3° ± 10.2°), smaller IC (△∠ = 5.4° ± 8.2° to 19.5° ± 10.2°), larger E (△∠ = 10.9° ± 12.2° to 13.1° ± 8.8°), and larger v (△∠ = 8.1° ± 9.4° to 16.6° ± 10.4°). Conclusions:The morphology of the iris (IT and IC) and its innate biomechanical behavior (E and v) were crucial in influencing the way the iris deformed during dilation, and angle closure was further exacerbated by decreased anterior chamber biometry (ACD and ACW).

PURPOSE:(1) To assess whether neural tissue structure and biomechanics could predict functional loss in glaucoma; (2) To evaluate the importance of biomechanics in making such predictions. DESIGN:Clinic-based cross-sectional study. METHODS:We recruited 238 glaucoma subjects (Chinese ethnicity, more than 50 years old). For one eye of each subject, we imaged the optic nerve head (ONH) using spectral-domain OCT under the following conditions: (1) primary gaze and (2) primary gaze with acute IOP elevation (to approximately 35 mmHg) achieved through ophthalmo-dynamometry. We utilized automatic segmentation of optic nerve head (ONH) tissues and digital volume correlation (DVC) analysis to compute intraocular pressure (IOP)-induced neural tissue strains. A robust geometric deep learning approach, known as Point-Net, was employed to predict the full Humphrey 24-2 pattern standard deviation (PSD) maps from ONH structural and biomechanical information. For each point in each PSD map, we predicted whether it exhibited no defect or a PSD value of less than 5%. Predictive performance was evaluated using 5-fold cross-validation and the F1-score. We compared the model's performance with and without the inclusion of IOP-induced strains to assess the impact of biomechanics on prediction accuracy. RESULTS:Integrating biomechanical (IOP-induced neural tissue strains) and structural (tissue morphology and neural tissues thickness) information yielded a significantly better predictive model (F1-score: 0.76 ± 0.02) across validation subjects, as opposed to relying only on structural information, which resulted in a significantly lower F1-score of 0.71 ± 0.02 (p < 0.05). Our subjects had a mean age of 69±5 years. Among them, 88 were female. The cohort included a wide range of glaucoma severity, with Mean Deviation (MD) values ranging from -1.8 (mild) to -25.2 (severe), and an average MD value of -7.25 ± 5.05. CONCLUSION:Our study has shown that the integration of biomechanical data can significantly improve the accuracy of visual field loss predictions and highlights the importance of the biomechanics-function relationship in glaucoma.

Background/aims To identify ocular determinants of iridolenticular contact area (ILCA), a recently introduced swept-source optical coherence tomography (SSOCT) derived parameter, and assess the association between ILCA and angle closure. Methods In this population-based cross-sectional study, right eyes of 464 subjects underwent SSOCT (SS-1000, CASIA, Tomey Corporation, Nagoya, Japan) imaging in the dark. Eight out of 128 cross-sectional images (evenly spaced 22.5° apart) were selected for analysis. Matlab (Matworks, Massachusetts, USA) was used to measure ILCA, defined as the circumferential extent of contact area between the pigmented iris epithelium and anterior lens surface. Gonioscopic angle closure (GAC) was defined as non-visibility of the posterior trabecular meshwork in two or more angle quadrants. Results The mean age of subjects was 62±6.6 years, with the majority being female (65.5%). 143/464 subjects (28.6%) had GAC. In multivariable linear regression analysis, ILCA was significantly associated with anterior chamber width (β=1.03, p=0.003), pupillary diameter (β=−1.9, p<0.001) and iris curvature (β=−17.35, p<0.001). ILCA was smaller in eyes with GAC compared with those with open angles (4.28±1.6 mm 2 vs 6.02±2.71 mm 2 , p<0.001). ILCA was independently associated with GAC (β=−0.03, p<0.001), iridotrabecular contact index (β=−6.82, p<0.001) or angle opening distance (β=0.02, p<0.001) after adjusting for covariates. The diagnostic performance of ILCA for detecting GAC was acceptable (AUC=0.69). Conclusions ILCA is a significant predictor of angle closure independent of other biometric factors and may reflect unique anatomical information associated with pupillary block. ILCA represents a novel biometric risk factor in eyes with angle closure.

Background: To compare intraocular pressure (IOP) and anterior segment parameters between eyes with unilateral primary angle closure glaucoma (PACG) and their fellow eyes with primary angle closure (PAC) or primary angle closure suspect (PACS). Methods: Subjects underwent anterior segment imaging using 360-degree swept-source optical coherence tomography (SS-OCT, CASIA Tomey, Nagoya, Japan) and ocular investigations including gonioscopy and IOP measurement. Each SS-OCT scan (divided into 8 frames, 22.5 degrees apart) was analysed and an average was obtained for the following anterior segment parameters: iridotrabecular contact (ITC), angle opening distance (AOD750), iris thickness and curvature, anterior chamber width, depth and area (ACW, ACD and ACA) and lens vault (LV). Results: Among 132 unilateral PACG subjects (mean age: 62.91 +/- 7.2 years; 59.1% male), eyes with PACG had significantly higher presenting IOP (24.81 +/- 0.94 vs. 18.43 +/- 0.57 mmHg, p < 0.001), smaller gonioscopic Shaffer grade (2.07 +/- 0.07 vs. 2.31 +/- 0.07, p < 0.001) and a greater extent of peripheral anterior synechiae (PAS, 1.21 +/- 0.21 vs. 0.54 +/- 0.16 clock hours, p = 0.001). PACG eyes also exhibited increased ITC, ITC area, greater LV and smaller AOD750, ACD and ACA (all p < 0.05). Using the forward stepwise regression model, an increase in 1 mmHg in presenting IOP before laser peripheral iridotomy (LPI) increases the odds of having PACG by 9% (95% confidence interval 5%-14%). Conclusions: PACG eyes have higher presenting IOP, smaller anterior segment parameters, greater extent of PAS, and larger LV compared to their fellow eyes with angle closure. Narrower anterior chamber dimensions and higher presenting IOP before LPI may increase risk of chronic elevated IOP and glaucomatous optic neuropathy after LPI.

Aims/Purpose: To determine whether subjects with asymmetric primary angle closure glaucoma (PACG) demonstrate greater central corneal thickness (CCT) asymmetry compared to those with symmetrical disease severity. Methods: The following clinical data were retrospectively extracted from the case records of 281 PACG subjects: presenting intraocular pressure (IOP), visual field mean deviation (MD) at presentation, CCT, anterior chamber depth (ACD), and axial length (AL). The eye with the worse visual field MD was considered the worse eye. Asymmetric PACG was defined as the inter‐eye visual field MD difference of greater than 5 dB; and symmetrical PACG disease as an inter‐eye difference of less than 5 dB. Subjects with previous acute primary angle closure were excluded. Results: Based on the definitions, a total of 160 out of 281 PACG subjects (56.9%) presented with asymmetrical disease and 121 (43.1%) with symmetrical disease. Subjects with asymmetric disease had a significantly thinner CCT in the worse eye (529.2 ± 35.2 μm) compared to the fellow eye (535.3 ± 37.2 μm) ( p < 0.001), and higher presenting IOP (28.8 ± 12.0 vs 20.1 ± 8.4 mmHg, p < 0.001), but no inter‐eye differences were observed for measurements of AL ( p = 0.71) and ACD ( p = 0.51) respectively. For patients with symmetric disease, no significant inter‐eye differences were observed for CCT (531.7 ± 31.2 vs 532.9 ± 32.4 μm, p = 0.38), AL ( p = 0.30) and ACD ( p = 0.31), but the worse eye had significantly higher IOP (22.7 ± 7.9 vs 20.6 ± 6.9 mmHg, p < 0.001). In the asymmetric disease group, 30.6% of subjects had a thinner CCT (≥ 10 μm) in the worse eye compared to 16% of subjects in the symmetric group. There was no correlation between inter‐eye CCT difference and inter‐eye difference of visual field MD ( p = 0.17). Conclusions: In PACG subjects with asymmetric disease at presentation, eyes with more severe disease have a thinner CCT and higher presenting IOP. Whether CCT is an independent risk factor for PACG through mechanisms beyond its influence on IOP measurements remains to be established.

Précis: The microvasculature of the optic disc and macula in eyes with acute primary angle closure and primary angle closure glaucoma was lower across the disease spectrum, but the significant difference was only observed in primary angle closure glaucoma. Purpose: To assess the microvasculature in the optic nerve head (ONH) and macula across the primary angle closure disease (PACD) spectrum using optical coherence tomography angiography (OCTA). Materials and Methods: OCTA (AngioVue, Fremont, CA) imaging was performed on 122 PACD subjects. Flow area (FA) and vessel density (VD) in the ONH, radial peripapillary capillary (RPC) network, and superficial and deep capillary plexuses of the macula were calculated and compared across the PACD spectrum using linear regression models with generalized estimating equations adjusted for inter-eye correlation. Results: A total of 234 eyes including 44 primary angle closure suspects (PACS), 93 primary angle closure (PAC), 79 primary angle closure glaucoma (PACG), and 18 PAC with a history of previous acute primary angle closure (APAC) were included in the analysis. Compared with other groups, PACG eyes showed smaller FA in the ONH (1.35±0.02 mm2), RPC (0.78±0.03 mm2), and the superficial retinal layer (1.08±0.03 mm2) (all P<0.05). Lower VD was also observed in the “whole image,” “inside disc,” and “peripapillary” regions of the ONH and RPC, and the “whole image” and “parafoveal” regions of the retinal layer in the PACG group when compared with other groups (all P<0.05). No significant differences were found for the other groups (all P>0.05). Lower VD in the ONH, RPC, and superficial retinal layer significantly correlated with worse visual field loss in PACG eyes (all P<0.05). Conclusions: Significant reduction in the microvasculature of the optic disc and macula in PACG suggests that glaucoma development may contribute to lower VD in these regions.

Wide-field optical coherence tomography (OCT) imaging can enable monitoring of peripheral changes in the retina, beyond the conventional fields of view used in current clinical OCT imaging systems. However, wide-field scans can present significant challenges for retinal layer segmentation. Deep Convolutional Neural Networks (CNNs) have shown strong performance in medical imaging segmentation but typically require large-scale, high-quality, pixel-level annotated datasets to be effectively developed. To address this challenge, we propose an advanced semi-supervised learning framework that combines the detailed capabilities of convolutional networks with the broader perspective of transformers. This method efficiently leverages labelled and unlabelled data to reduce dependence on extensive, manually annotated datasets. We evaluated the model performance on a dataset of 74 volumetric OCT scans, each performed using a prototype swept-source OCT system following a wide-field scan protocol with a 15x9 mm field of view, comprising 11,750 labelled and 29,016 unlabelled images. Wide-field retinal layer segmentation using the semi-supervised approach show significant improvements (P-value < 0.001) of up to 11% against a UNet baseline model. Comparisons with a clinical spectral-domain-OCT system revealed significant correlations of up to 0.91 (P-value < 0.001) in retinal layer thickness measurements. These findings highlight the effectiveness of semi-supervised learning with cross-teaching between CNNs and transformers for automated OCT layer segmentation.

Purpose: To determine the efficiency, precision, and agreement of GlauCAT-Asian and its corresponding validity and reliability. Methods: In this cross-sectional study, 219 participants (mean +/- standard deviation age, 66.59 +/- 8.61 years; 34% female) across the spectrum of glaucoma severity and 50 glaucoma suspects were recruited from glaucoma clinics in Singapore. Participants answered seven computerized adaptive testing (CAT) evaluations (Ocular Comfort, Activity Limitation, Lighting, Mobility, Concerns, Psychosocial, Glaucoma Management) and underwent eye examinations. Efficiency (mean number of items required for each CAT and time taken for CAT versus full item banks [IBs]), agreement (concordance between CATs and full IB person measures, henceforth referred to as scores), and precision (standard error of measurement [SE]) were evaluated. Other validity and reliability metrics were also assessed. Results: The mean number of items administered ranged from 9 (Mobility/Glaucoma Management) to 12 (Ocular Comfort). Compared to answering the full IBs, CATs provided an average time saving of 38.3% (range, 10% to 70.6% for Lighting and Activity Limitation, respectively). Agreement between scores obtained by CAT versus full IB was high (intracorrelation coefficient >= 0.75), as was precision of score estimates (mean SE range: 0.35 for Psychosocial to 0.29 for Mobility). Scores from Activity Limitation, Mobility, Lighting, and Concerns decreased significantly as glaucoma severity increased (criterion validity; P-trend <0.05). All tests displayed good convergent/divergent validity and test-retest reliability. Conclusions: GlauCAT-Asian provides efficient, precise, accurate, valid, and reliable measurement of the patient-centered impact of glaucoma. Translational Relevance: GlauCAT-Asian may provide a valuable clinical tool for ophthalmologists to monitor impact of disease progression and the effectiveness of therapies.