Social determinants of health and health disparities in glaucoma: A review.

Social determinants of health and barriers to care can significantly impact patients' access to glaucoma care and treatment, resulting in disparities within disease presentation, progression, management, and treatment outcomes. The widespread adoption of electronic health record systems has allowed researchers and clinicians to further explore these relationships, identifying factors such as race, ethnicity, and socioeconomic status to be risk factors for more severe disease and lower treatment adherence. These disparities highlight potential targets for interventions to combat these disparities and improve overall patient outcomes. This article provides a summary of the available data on health disparities within glaucoma disease presentation, progression, management, treatment, and outcomes and discusses interventions to improve care delivery and outcomes among patients with glaucoma.

Association of exosomes in patients with compromised myocardial perfusion on functional imaging.

BACKGROUND: Exosomes are membrane vesicles that are actively secreted in response to microenvironmental stimuli. In this study, we quantified the amount of exosomes in patients with significant coronary artery disease (CAD) and evaluated its relationship with myocardial perfusion imaging (MPI) results. METHODS: Patients who underwent both MPI and coronary angiography were recruited. Plasma was collected during angiography, and exosomes were extracted via the precipitation method. The summed stress scores (SSS), summed difference scores, and ventricular functional parameters were calculated from the MPI and compared with the amounts of exosomes and extracted miRNAs. RESULTS: In total, 115 patients were enrolled (males: 78 %; mean age: 66.6 ± 10.6 years). Those with abnormal SSS according to the MPI had significantly fewer exosomes (p = 0.032). After multivariate analysis, the SSS remained significantly related to the amount of exosomes (p = 0.035). In forty randomly selected samples, miRNA-432-5p and miRNA-382-3p were upregulated in patients with abnormal SSS. CONCLUSION: Patients with compromised poststress myocardial perfusion on MPI tended to have fewer exosomes in association with CAD-related miRNAs. This is the first study to clarify the fundamental and pathophysiological causes of CAD using radiographic examinations.

Long-term Evolution of Estimated Glomerular Filtration Rate in Patients With Antiviral Treatment for Hepatitis C Virus Infection.

BACKGROUND & AIMS: Data regarding the long-term evolution of estimated glomerular filtration rate (eGFR) in patients receiving antiviral treatment for hepatitis C virus are limited. METHODS: A total of 1987 patients with eGFR ≥15 mL/min/1.73m2 who received interferon or direct-acting antiviral treatment were prospectively enrolled in this cohort study. The eGFR was assessed biannually by the Chronic Kidney Disease Epidemiology Collaboration equation from the time point of sustained virologic response (SVR12). Multivariate generalized estimated equation was used to assess the association between the factors of interest and evolution of eGFR following antiviral treatment. Multivariate Cox regression analysis was used to assess the relative risk of end-stage renal disease (ESRD), defined as an eGFR <15 mL/min/1.73m2. RESULTS: Patients who achieved SVR12 (adjusted slope coefficient difference: 2.36 mL/min/1.73 m2/year; 95% confidence interval [CI], 1.50 to 3.32; P < .001) were associated with eGFR improvement, compared with those who did not achieve SVR12. Among patients who achieved SVR12, the eGFR evolution was comparable (adjusted slope coefficient difference: 0.31 mL/min/1.73m2/year; 95% CI, -0.34 to 0.96; P = .35) in those treated with interferon or direct-acting antiviral. The incidence rates of ESRD in patients who achieved and did not achieve SVR12 were 0.06 per 100 person-years and 0.37 per 100 person-years. Patients who achieved SVR12 were associated with a lower risk of ESRD (adjusted hazard ratio, 0.24; 95% CI, 0.05-0.68; P = .021). CONCLUSIONS: The long-term eGFR evolution and risk of ESRD are significantly improved in patients who achieve SVR12 with anti- hepatitis C virus treatment.

Long-term durability of sustained virologic response for hepatitis C virus infection in solid organ transplant recipients receiving direct-acting antivirals.

Data are limited regarding the long-term durability of sustained virologic response (SVR) in solid organ transplant recipients who achieve SVR12 with direct-acting antivirals (DAAs) for hepatitis C virus (HCV). We reported the virologic outcomes in 42 recipients who received DAAs for acute or chronic HCV infection after heart, liver, and kidney transplantation. After achieving SVR12, all recipients received HCV RNA surveys at SVR24, and biannually until the last visit. If HCV viremia was detected during the follow-up period, direct sequencing and phylogenetic analysis were performed to confirm late relapse or reinfection. Sixteen (38.1%), 11 (26.2%), and 15 (35.7%) patients underwent heart, liver and, kidney transplantation. Thirty-eight (90.5%) received sofosbuvir (SOF)-based DAAs. No recipients had late relapse or reinfection after a median (range) of post-SVR12 follow-up 4.0 (1.0-6.0) years. We demonstrate that the durability of SVR in solid organ transplant recipients is excellent once SVR12 is achieved with DAAs.

Intraocular pressure-lowering efficacy and ocular safety of Rho-kinase inhibitor in glaucoma: a meta-analysis and systematic review of prospective randomized trials.

PURPOSE: To evaluate the intraocular pressure (IOP)-reducing efficacy and safety of Rho-kinase inhibitor (RKI). METHODS: Published studies in PubMed and EMBASE were searched on March 20, 2021. Study selection and data extraction were performed according to PRISMA. Meta-analysis of the IOP-lowering effect was performed with the bivariate random-effects model, with studies categorized into 2 classes: RKI versus placebo and RKI versus another medication. The main outcome was the difference in IOP reduction between RKI and non-RKI groups. Subgroup analysis of adjunctive RKI efficacy and additional review of its major ocular adverse events (AE) were also performed. RESULTS: Ten (2.6%) out of 391 studies were retrieved. In the RKI versus placebo class, RKI showed greater IOP reduction after 4-8 weeks (mean difference = - 1.69 mmHg [- 2.22, - 1.16], P < 0.001). In the RKI versus another medication class, IOP reduction by RKI was noninferior to timolol 0.5% twice-daily after 4-8 weeks (mean difference = 0.39 mmHg [0.01, 0.76], P = 0.043) and 12 weeks (mean difference = 0.48 mmHg [0.11, 0.85]; P = 0.011). In the subgroup analysis, the mean difference in IOP reduction by adjunctive RKI and placebo was - 1.42 mmHg (P < 0.001). The most common ocular AE of RKI was conjunctival hyperemia (19-65%), followed by conjunctival hemorrhage (6-20%) and cornea verticillata (13-26%). CONCLUSIONS: With a treatment duration of 1-3 months, RKI showed effective IOP reduction noninferior to timolol as monotherapy and as adjunctive therapy. Our results suggested RKI be a reliable IOP control medication; however, its higher incidence of some ocular complications should be attended to.

Performance and Limitation of Machine Learning Algorithms for Diabetic Retinopathy Screening: Meta-analysis.

BACKGROUND: Diabetic retinopathy (DR), whose standard diagnosis is performed by human experts, has high prevalence and requires a more efficient screening method. Although machine learning (ML)-based automated DR diagnosis has gained attention due to recent approval of IDx-DR, performance of this tool has not been examined systematically, and the best ML technique for use in a real-world setting has not been discussed. OBJECTIVE: The aim of this study was to systematically examine the overall diagnostic accuracy of ML in diagnosing DR of different categories based on color fundus photographs and to determine the state-of-the-art ML approach. METHODS: Published studies in PubMed and EMBASE were searched from inception to June 2020. Studies were screened for relevant outcomes, publication types, and data sufficiency, and a total of 60 out of 2128 (2.82%) studies were retrieved after study selection. Extraction of data was performed by 2 authors according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), and the quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Meta-analysis of diagnostic accuracy was pooled using a bivariate random effects model. The main outcomes included diagnostic accuracy, sensitivity, and specificity of ML in diagnosing DR based on color fundus photographs, as well as the performances of different major types of ML algorithms. RESULTS: The primary meta-analysis included 60 color fundus photograph studies (445,175 interpretations). Overall, ML demonstrated high accuracy in diagnosing DR of various categories, with a pooled area under the receiver operating characteristic (AUROC) ranging from 0.97 (95% CI 0.96-0.99) to 0.99 (95% CI 0.98-1.00). The performance of ML in detecting more-than-mild DR was robust (sensitivity 0.95; AUROC 0.97), and by subgroup analyses, we observed that robust performance of ML was not limited to benchmark data sets (sensitivity 0.92; AUROC 0.96) but could be generalized to images collected in clinical practice (sensitivity 0.97; AUROC 0.97). Neural network was the most widely used method, and the subgroup analysis revealed a pooled AUROC of 0.98 (95% CI 0.96-0.99) for studies that used neural networks to diagnose more-than-mild DR. CONCLUSIONS: This meta-analysis demonstrated high diagnostic accuracy of ML algorithms in detecting DR on color fundus photographs, suggesting that state-of-the-art, ML-based DR screening algorithms are likely ready for clinical applications. However, a significant portion of the earlier published studies had methodology flaws, such as the lack of external validation and presence of spectrum bias. The results of these studies should be interpreted with caution.

Detection and agreement of event-based OCT and OCTA analysis for glaucoma progression.

OBJECTIVE: To examine event-based glaucoma progression using optical coherence tomography (OCT) and OCT angiography (OCTA). METHODS: In this retrospective study, glaucoma eyes with ≥2-year and 4-visits of OCT/OCTA imaging were included. Peripapillary capillary density (CD) and retinal nerve fibre layer thickness (RNFL) were obtained from 4.5 mm × 4.5 mm optic nerve head (ONH) scans. Event-based OCT/OCTA progression was defined as decreases in ONH measurements exceeding test-retest variability on ≥2 consecutive visits. Visual field (VF) progression was defined as significant VF mean deviation worsening rates on ≥2 consecutive visits. Inter-instrument agreement on progression detection was compared using kappa(κ) statistics. RESULTS: Among 147 eyes (89 participants), OCTA and OCT identified 33(22%) and 25(17%) progressors, respectively. They showed slight agreement (κ = 0.06), with 7(5%) eyes categorized as progressors by both. When incorporating both instruments, the rate of progressors identified increased to 34%. Similar agreement was observed in diagnosis- and severity-stratified analyses (κ < 0.10). Compared to progressors identified only by OCT, progressors identified only by OCTA tended to have thinner baseline RNFL and worse baseline VF. VF progression was identified in 11(7%) eyes. OCT and VF showed fair agreement (κ = 0.26), with 6(4%) eyes categorized as progressors by both. OCTA and VF showed slight agreement (κ = 0.08), with 4(3%) eyes categorized as progressors by both. CONCLUSIONS: OCT and OCTA showed limited agreement on event-based progression detection, with OCT showing better agreement with VF. Both OCT and OCTA detected more progressors than VF. OCT and OCTA may provide valuable, yet different and complementary, information about glaucoma progression.

Social Factors Associated with the Risk of Glaucoma Suspect Conversion to Glaucoma: Analysis of the Nationwide All of Us Program.

PURPOSE: To examine social factors associated with the 5-year risk of glaucoma suspects (GS) converting to open-angle glaucoma (OAG). DESIGN: Retrospective cohort analysis. SUBJECTS: We screened for participants diagnosed with GS in the All of Us database. Cases that converted to OAG within 5 years of GS diagnosis (the "conversion group") were compared with control cases that did not convert. METHODS: Demographic, socioeconomic and health-care utilization data of the cases were extracted and compared between the conversion group and the control group. Multivariable Cox proportional hazards modeling was used to identify potential factors associated with the risk of conversion. MAIN OUTCOME MEASURES: Hazard ratios (HRs) of significant factors associated with the risk of conversion. RESULTS: A total of 5274 GS participants were identified, and 786 (15%) cases converted to OAG within 5-year follow-up. The 2 groups showed significant differences in age, race, gender, employment status, income/education level, history of intraocular surgery, and health-care utilization patterns. In the multivariable model, African American/Black race (HR : 1.70 [95% confidence interval (CI) 1.44-2.00]), older age at GS diagnosis (1.17 [95% CI 1.09-1.25]), male gender (1.30 [95% CI 1.13-1.50], no history of recreational drug use (1.23 [1.07-1.42]), history of intraocular surgery (1.60 [95% CI 1.02-1.53]), and having more reasons for delayed health-care access (2.27 [95% CI 1.23-4.18]) were associated with a greater hazard of conversion, while being employed (0.71 [95% CI 0.60-0.86]) was associated with a smaller hazard of conversion (P < 0.05 for all). CONCLUSIONS: Several social factors were associated with the conversion from GS to OAG, which may help to identify patients at higher risk of disease progression. Future studies are needed to examine the basis for these findings and the potential interventions that could address them. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Racial Differences in the Diagnostic Accuracy of OCT Angiography Macular Vessel Density for Glaucoma.

PURPOSE: To evaluate and compare the diagnostic accuracy of macular vessel density (VD) measured by OCT angiography (OCTA) in individuals of African descent (AD) and European descent (ED) with open-angle glaucoma. DESIGN: Observational, cross sectional study. PARTICIPANTS: A total of 176 eyes of 123 patients with glaucoma and 140 eyes of 88 healthy participants from the Diagnostic Innovations in Glaucoma Study. METHODS: Whole-image ganglion cell complex (wiGCC) thickness and macular VD (parafoveal VD and perifoveal VD) were obtained from 6 × 6 macula scans. Area under the receiver operating characteristic (AUROC) curves were used to evaluate the diagnostic accuracy of macular VD and ganglion cell complex (GCC) thickness in AD and ED participants after adjusting for confounders such as age, visual field mean deviation (VF MD), signal strength index, axial length, self-reported hypertension and diabetes. MAIN OUTCOME MEASURES: Macular VD and wiGCC measurements. RESULTS: Parafoveal and perifoveal VD were significantly lower in ED than AD patients with glaucoma. Parafoveal and perifoveal VD performed significantly worse in AD participants compared with ED participants for detection of glaucoma (adjusted AUROC, 0.75 [95% confidence interval (CI), 0.62, 0.87], 0.85 [95% CI, 0.79, 0.90], P = 0.035; and 0.82 [95% CI, 0.70, 0.92], 0.91 [95% CI, 0.87, 0.94], respectively; P = 0.020). In contrast to VD, diagnostic accuracy of GCC thickness was similar in AD and ED individuals (adjusted AUROC, 0.89 [95% CI, 0.79, 0.96], 0.92 [95% CI, 0.86, 0.96], respectively; P = 0.313). The diagnostic accuracies of both macular VD and GCC thickness for differentiating between glaucoma and healthy eyes increased with increasing VF MD in both AD and ED participants. CONCLUSIONS: Diagnostic performance of OCTA macular VD, but not GCC thickness, for glaucoma detection varies by race. Moreover, macular VD parameters had lower accuracy for detecting glaucoma in AD individuals than in ED individuals. The diagnostic performance of macular VD is race-dependent, and, therefore, race should be taken into consideration when interpreting macular OCTA results. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Association between metformin use with circumpapillary retinal nerve fibre layer thickness and capillary vessel density in glaucoma.

BACKGROUND/AIMS: To investigate the association between use of metformin and circumpapillary retinal nerve fibre layer (cpRNFL) thickness, as well as whole image capillary density (wiCD), in patients with glaucoma. METHODS: This cross-sectional study included patients with glaucoma suspect or primary open-angle glaucoma (POAG) underwent optical coherence tomography angiography imaging. Use and duration of antidiabetic medications were assessed at the time of imaging. Multivariable linear mixed-effect modelling was used to estimate the effect of diabetes medication on wiCD and cpRNFL while controlling for covariates including age, race, body mass index, diagnosis, 24-2 visual field mean deviation, and intraocular pressure, average signal strength index as well as any variables that showed a p <0.1 in the univariable analysis. RESULTS: A total of 577 eyes (330 POAG and 247 glaucoma suspect) of 346 patients were included. Sixty-five patients (23%) had diabetes, of whom 55 (78.5%) used metformin, and 17 (26.2%) used insulin. After adjusting for covariates, the association between metformin use and wiCD (1.56 (95% CI 0.40 to 2.71); p=0.008), duration of metformin use and wiCD (0.12 (95% CI 0.02 to 0.22) per 1 year longer; p=0.037), and metformin use and cpRNFL thickness (5.17 (95% CI 1.24 to 9.10) µm; p=0.010) had statistically significant associations in each model. CONCLUSIONS: Metformin use was associated with higher wiCD and thicker cpRNFL. These findings indicate a potential association, underscoring the need for longitudinal studies to determine if metformin plays a role in the retinal conditions of patients with glaucoma. TRIAL REGISTRATION NUMBER: NCT00221897.

Convolutional Neural Network-Based Prediction of Axial Length Using Color Fundus Photography.

Purpose: To develop convolutional neural network (CNN)-based models for predicting the axial length (AL) using color fundus photography (CFP) and explore associated clinical and structural characteristics. Methods: This study enrolled 1105 fundus images from 467 participants with ALs ranging from 19.91 to 32.59 mm, obtained at National Taiwan University Hospital between 2020 and 2021. The AL measurements obtained from a scanning laser interferometer served as the gold standard. The accuracy of prediction was compared among CNN-based models with different inputs, including CFP, age, and/or sex. Heatmaps were interpreted by integrated gradients. Results: Using age, sex, and CFP as input, the mean ± standard deviation absolute error (MAE) for AL prediction by the model was 0.771 ± 0.128 mm, outperforming models that used age and sex alone (1.263 ± 0.115 mm; P < 0.001) and CFP alone (0.831 ± 0.216 mm; P = 0.016) by 39.0% and 7.31%, respectively. The removal of relatively poor-quality CFPs resulted in a slight MAE reduction to 0.759 ± 0.120 mm without statistical significance (P = 0.24). The inclusion of age and CFP improved prediction accuracy by 5.59% (P = 0.043), while adding sex had no significant improvement (P = 0.41). The optic disc and temporal peripapillary area were highlighted as the focused areas on the heatmaps. Conclusions: Deep learning-based prediction of AL using CFP was fairly accurate and enhanced by age inclusion. The optic disc and temporal peripapillary area may contain crucial structural information for AL prediction in CFP. Translational Relevance: This study might aid AL assessments and the understanding of the morphologic characteristics of the fundus related to AL.

Rate of Initial Optic Nerve Head Capillary Density Loss and Risk of Visual Field Progression.

Importance: Rapid initial optic nerve head capillary density loss may be used to assess the risk of glaucoma visual field progression. Objective: To investigate the association between the rate of initial optic nerve head capillary density loss from optical coherence tomography angiography (OCTA) and visual field progression. Design, Setting, Participants: This was a retrospective study of a longitudinal cohort at a glaucoma referral center. A total of 167 eyes (96 with primary open-angle glaucoma and 71 with glaucoma suspect) of 109 patients were monitored for a mean (SD) of 5.7 (1.4) years from January 2015 to December 2022. Data analysis was undertaken in April 2023. Main Outcomes and Measures: The rates of initial capillary density and average retinal nerve fiber layer loss were calculated from the first 3 optic nerve head OCTA and OCT scans, respectively, during the initial follow-up (mean [SD], 2.0 [1.0] years). Based on the median rate, eyes were categorized into fast and slow progressor groups. The association between initial capillary density change or retinal nerve fiber layer thinning and visual field progression was evaluated using linear-mixed and time-varying Cox models. Results: A total of 167 eyes of 109 patients (mean [SD] age, 69.0 [11.1] years; 56 [51.4%] female and 53 [48.6%] male) were assessed. Eighty-three eyes were slow OCTA progressors, while 84 eyes were fast with mean capillary density loss of -0.45% per year and -1.17% per year, respectively (mean difference, -0.72%/year; 95% CI,-0.84 to -0.60; P < .001). Similarly, 83 eyes were slow OCT progressors, while 84 eyes were fast with mean retinal nerve fiber layer thinning of -0.09 µm per year and -0.60 µm per year, respectively (mean difference, -0.51 µm/year; 95% CI,-0.59 to -0.43; P < .001). The fast OCTA and OCT progressors were associated with more rapid visual field loss (mean difference, -0.18 dB/year; 95% CI,-0.30 to -0.06; P = .004 and -0.17 dB/year; 95% CI,-0.29 to -0.06; P = .002, respectively). Fast OCTA progressing eyes were more likely to have visual field progression (hazard ratio, 1.96; 95% CI, 1.04-3.69; P = .04). Seventeen of 52 eyes (32.7%; 95% CI, 32.5-32.8) with fast OCTA and OCT progression developed subsequent visual field likely progression. Conclusion and Relevance: Rapid initial optic nerve head capillary density loss from OCTA was associated with a faster rate of visual field progression and a doubling of the risk of developing event progression in this study. These findings may support clinical use of OCTA and OCT optic nerve head measurements for risk assessment of glaucoma progression.

Time to glaucoma progression detection by optical coherence tomography and visual field in glaucoma individuals of African descent.

PURPOSE: To examine the time to glaucoma progression detection by retinal nerve fiber layer thickness (RNFLT) and visual field (VF) among African descent (AD) individuals. DESIGN: Retrospective cohort study. METHODS: Setting: Multi-center. STUDY POPULATION: We included AD glaucoma eyes from DIGS/ADAGES with ≥2-year/5-visits of optic nerve head RNFLT and 24-2 VF examinations. Intervention or Observation Procedure: Rates of VF mean deviation (MD) and RNFLT worsening were analyzed using linear mixed-effects models, and longitudinal data was simulated using the variability estimates. MAIN OUTCOME MEASURE: The simulated time to detect trend-based glaucoma progression was assessed with assumed rates of VF MD and RNFLT change derived from the cohort (25th, 50th, 75th percentile [p25, median, p75] slopes and mean slopes). Severity-stratified analyses were also performed. RESULTS: We included 184 eyes from 128 AD subjects (mean baseline age: 63.4 years; VF MD: -4.2 dB, RNFLT: 80.2 µm). The p25, median, mean and p75 rates of change were -0.43, -1.01, -1.15 and -1.64 µm/year for RNFLT, and 0.00, -0.21, -0.30 and -0.51 dB/year for VF MD, respectively. Compared to VF MD, RNFLT showed an overall shorter mean time to progression detection (time difference: 0.4-1.7 years), with the mean rates showing the largest difference (RNFLT: 5.2 years vs. VF MD: 6.9 years). Similarly, we found an overall shorter time to detect RNFLT progression, compared to that of VF MD progression, in mild glaucoma eyes (≥1 year earlier) and in moderate-advanced glaucoma eyes (∼0.5 year earlier). CONCLUSIONS: Computer simulation showed potentially shorter time to detect RNFLT progression than VF MD progression in AD eyes. Our findings support the importance of using RNFLT to detect progressive glaucoma in AD individuals.

Long-term variability of retinal nerve fibre layer thickness measurement in patients with glaucoma of African and European descents.

BACKGROUND: To examine long-term retinal nerve fibre layer thickness (RNFLT) variability and associated clinical factors in African (AD) and European descent (ED) individuals with glaucoma. METHODS: This retrospective cohort study included glaucoma eyes of AD and ED from Diagnostic Innovations in Glaucoma Study/The African Descent and Glaucoma Evaluation Study with ≥4 visits/2 years of follow-up. We calculated optic nerve head RNFLT variability per-examination/visit as the absolute error of its residuals across follow-up. Full, baseline and parsimonious linear-mixed models were fit to evaluate the effects of clinical factors (demographics and ocular characteristics, prior/intervening glaucoma surgeries and cataract extraction (CE), RNFLT thinning rate, scan quality, visit/testing frequency, etc) on RNFLT variability in both races. RESULTS: There were 376 and 625 eyes (226 and 349 participants) of AD and ED, and the mean (95% CI) RNFLT variability was 1.62 (1.52, 1.71) µm and 1.42 (1.34, 1.50) µm, respectively (p=0.002). AD and ED had some shared predictors of RNFLT variability, including intraocular pressure fluctuation and scan quality, although the effects varied (p<0.05). In both races, intervening CE was most strongly correlated with higher RNFLT variability (ß: 0.24-0.92, p<0.05). After excluding eyes with intervening CE, RNFLT variability was reduced and the small racial difference was no longer significant (AD: 1.40 (1.31, 1.48) µm vs ED: 1.34 (1.27, 1.40) µm; p=0.280). CONCLUSIONS: Although some predictors were identified, long-term RNFLT variability appeared small for both AD and ED eyes. Moreover, the racial difference did not remain once intervening CE, the strongest predictor of variability, was eliminated. Our findings inform on strategies to optimise structural assessment and suggest that, when accounting for relevant factors, RNFLT is reliable across races.

Association of foveal avascular zone change and glaucoma progression.

BACKGROUND/AIMS: To investigate the association between longitudinal changes of foveal avascular zone (FAZ) area and the rate of structural and functional progression in glaucoma. METHODS: A longitudinal cohort included 115 eyes (46 glaucoma suspect and 66 primary open-angle glaucoma) of 81 patients having ≥2 year follow-up, and ≥4 visits with optical coherence tomography angiography and visual field (VF). Eyes in the longitudinal cohort with a slope greater than that found in 95 percentile of separate healthy test-retest series for FAZ area were categorised into FAZ progressors; all other eyes were defined as FAZ non-progressors. A generalised linear mixed-effect model was used to investigate the association of FAZ progressors with demographic and clinical characteristics. RESULTS: Faster ganglion cell complex (GCC) thinning and faster VF mean deviation (MD) loss were found in eyes with FAZ progressors compared with FAZ non-progressors (mean difference: -0.7 (95% CI, -1.4 to -0.1) µm/y; p=0.026, -0.3 (-0.5 to -0.1) dB/y; p=0.017, respectively), while whole image vessel density was not associated with FAZ progressors (p=0.929). SD of intraocular pressure (IOP) and IOP range were also associated with FAZ progressors in separate multivariable models (OR: 1.54 (1.02 to 2.32) per 1 mm Hg higher, p=0.041; OR: 1.20 (1.01 to 1.41) per 1 mm Hg higher; p=0.035, respectively). CONCLUSIONS: Significant FAZ increase was weakly associated with moderately faster rates of both GCC thinning and VF MD loss, but not macular vessel density change in glaucoma eyes. Additional studies are needed to elucidate the pathophysiological associations between macula GCC thinning and FAZ area increases in glaucoma.

Smoking Intensity is Associated With Progressive Optic Nerve Head Vessel Density Loss in Glaucoma.

PRCIS: A lifetime history of greater smoking consumption was associated with faster vessel density loss over time. Smoking intensity should be considered when assessing the risk of glaucoma progression, as well as its management. PURPOSE: To investigate the relationship of smoking and smoking intensity, with the rate of optic nerve head (ONH) whole image capillary density (wiCD) loss in primary open angle glaucoma (POAG) and glaucoma suspect patients. METHODS: In this longitudinal study, patients with POAG who had at least 2 years of follow-up and optical coherence tomography angiography (OCTA) performed at a minimum of 4 visits were selected for study. The smoking intensity was calculated as the pack-year at the baseline OCTA. Univariable and multivariable linear mixed models were used to determine the effect of each parameter on the rates of wiCD loss over time. Nonlinear least-squares estimation with piecewise regression model was used to investigate the cutoff point for the relationship between wiCD loss and smoking intensity. RESULTS: One hundred sixty-four eyes (69 glaucoma suspect and 95 POAG) of 110 patients were included with a mean (95% CI) follow-up of 4.0 (3.9 to 4.1) years. Of the 110 patients, 50 (45.5%) had a reported history of smoking. Greater smoking intensity was associated with faster wiCD loss [-0.11 (-0.23 to 0.00)] %/year per 10 pack-year higher; P =0.048) after adjusting for covariates. The wiCD thinning became significantly faster when smoking intensity was greater than 22.2 pack-years. Smoking had no effect on the rate of wiCD thinning in patients who smoked <22.2 pack-years during their lifetime. CONCLUSIONS: A history of greater smoking consumption was associated with faster vessel density loss, suggesting smoking intensity as a potential risk factor for glaucoma.

Time to Glaucoma Progression Detection by Optical Coherence Tomography in Individuals of African and European Descents.

PURPOSE: To examine the time to detectable retinal nerve fiber layer thickness (RNFLT) progression by optical coherence tomography (OCT) among glaucoma patients of African descent (AD) and European descent (ED). DESIGN: Retrospective cohort study. METHODS: AD and ED glaucoma eyes from the Diagnostic Innovations in Glaucoma Study (DIGS)/African Descent and Glaucoma Evaluation Study (ADAGES) with ≥2 years/4 visits of optic nerve head RNFLT measurements were included after homogenization on age, diagnosis, and baseline visual field (VF) measurement. RNFLT variability estimates based on linear mixed-effects models were used to simulate longitudinal RNFLT data for both races. Times to trend-based RNFLT progression detection were calculated under standardized scenarios (same RNFLT baseline/thinning rates for both races) and real-world scenarios (AD and ED cohort-specific RNFLT baseline/thinning rates). RESULTS: We included 332 and 542 eyes (216 and 317 participants) of AD and ED, respectively. In standardized scenarios, the time to detect RNFLT progression appeared to be similar (difference, <0.2 years) for AD and ED across different assumed RNFLT thinning rates/baseline. In real-world scenarios, compared to ED, AD had a faster RNFLT thinning rate (-0.8 vs -0.6 µm/y) and thicker baseline RNFLT (84.6 vs 81.8 µm). With a faster thinning rate, the mean (SD) time to progression detection was shorter in AD (4.8 [2.0] vs ED: 5.4 [2.4] years), and the 5-year progression rate appeared to be higher (AD: 59% vs ED: 47%). CONCLUSIONS: Time to progression detection was similar for both races when assuming identical RNFLT baseline/thinning rates, and shorter in AD eyes under real-world simulation when AD had faster RNFLT thinning. In contrast to prior results on VF, which detected progression later in AD eyes than in ED eyes, OCT may detect progression more consistently across these races.

Detection of glaucoma progression on longitudinal series of en-face macular optical coherence tomography angiography images with a deep learning model.

BACKGROUND/AIMS: To design a deep learning (DL) model for the detection of glaucoma progression with a longitudinal series of macular optical coherence tomography angiography (OCTA) images. METHODS: 202 eyes of 134 patients with open-angle glaucoma with ≥4 OCTA visits were followed for an average of 3.5 years. Glaucoma progression was defined as having a statistically significant negative 24-2 visual field (VF) mean deviation (MD) rate. The baseline and final macular OCTA images were aligned according to centre of fovea avascular zone automatically, by checking the highest value of correlation between the two images. A customised convolutional neural network (CNN) was designed for classification. A comparison of the CNN to logistic regression model for whole image vessel density (wiVD) loss on detection of glaucoma progression was performed. The performance of the model was defined based on the confusion matrix of the validation dataset and the area under receiver operating characteristics (AUC). RESULTS: The average (95% CI) baseline VF MD was -3.4 (-4.1 to -2.7) dB. 28 (14%) eyes demonstrated glaucoma progression. The AUC (95% CI) of the DL model for the detection of glaucoma progression was 0.81 (0.59 to 0.93). The sensitivity, specificity and accuracy (95% CI) of DL model were 67% (34% to 78%), 83% (42% to 97%) and 80% (52% to 95%), respectively. The AUC (95% CI) for the detection of glaucoma progression based on the logistic regression model was lower than the DL model (0.69 (0.50 to 0.88)). CONCLUSION: The optimised DL model detected glaucoma progression based on longitudinal macular OCTA images showed good performance. With external validation, it could enhance detection of glaucoma progression. TRIAL REGISTRATION NUMBER: NCT00221897.

Vision transformers: The next frontier for deep learning-based ophthalmic image analysis.

Deep learning is the state-of-the-art machine learning technique for ophthalmic image analysis, and convolutional neural networks (CNNs) are the most commonly utilized approach. Recently, vision transformers (ViTs) have emerged as a promising approach, one that is even more powerful than CNNs. In this focused review, we summarized studies that applied ViT-based models to analyze color fundus photographs and optical coherence tomography images. Overall, ViT-based models showed robust performances in the grading of diabetic retinopathy and glaucoma detection. While some studies demonstrated that ViTs were superior to CNNs in certain contexts of use, it is unclear how widespread ViTs will be adopted for ophthalmic image analysis, since ViTs typically require even more training data as compared to CNNs. The studies included were identified from the PubMed and Google Scholar databases using keywords relevant to this review. Only original investigations through March 2023 were included.

Comparative analysis of alignment algorithms for macular optical coherence tomography imaging.

BACKGROUND: Optical coherence tomography (OCT) is the most important and commonly utilized imaging modality in ophthalmology and is especially crucial for the diagnosis and management of macular diseases. Each OCT volume is typically only available as a series of cross-sectional images (B-scans) that are accessible through proprietary software programs which accompany the OCT machines. To maximize the potential of OCT imaging for machine learning purposes, each OCT image should be analyzed en bloc as a 3D volume, which requires aligning all the cross-sectional images within a particular volume. METHODS: A dataset of OCT B-scans obtained from 48 age-related macular degeneration (AMD) patients and 50 normal controls was used to evaluate five registration algorithms. After alignment of B-scans from each patient, an en face surface map was created to measure the registration quality, based on an automatically generated Laplace difference of the surface map-the smoother the surface map, the smaller the average Laplace difference. To demonstrate the usefulness of B-scan alignment, we trained a 3D convolutional neural network (CNN) to detect age-related macular degeneration (AMD) on OCT images and compared the performance of the model with and without B-scan alignment. RESULTS: The mean Laplace difference of the surface map before registration was 27 ± 4.2 pixels for the AMD group and 26.6 ± 4 pixels for the control group. After alignment, the smoothness of the surface map was improved, with a mean Laplace difference of 5.5 ± 2.7 pixels for Advanced Normalization Tools Symmetric image Normalization (ANTs-SyN) registration algorithm in the AMD group and a mean Laplace difference of 4.3 ± 1.4.2 pixels for ANTs in the control group. Our 3D CNN achieved superior performance in detecting AMD, when aligned OCT B-scans were used (AUC 0.95 aligned vs. 0.89 unaligned). CONCLUSIONS: We introduced a novel metric to quantify OCT B-scan alignment and compared the effectiveness of five alignment algorithms. We confirmed that alignment could be improved in a statistically significant manner with readily available alignment algorithms that are available to the public, and the ANTs algorithm provided the most robust performance overall. We further demonstrated that alignment of OCT B-scans will likely be useful for training 3D CNN models.