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Purpose: This study uses deep neural network-generated rim-to-disc area ratio (RADAR) measurements and the disc damage likelihood scale (DDLS) to measure the rate of optic disc rim loss in a large cohort of glaucoma patients. Methods: A deep neural network was used to calculate RADAR and DDLS for each optic disc photograph (ODP). Patient demographics, diagnosis, intraocular pressure (IOP), and mean deviation (MD) from perimetry were analyzed as risk factors for faster progression of RADAR. Receiver operating characteristic (ROC) curves were used to compare RADAR and DDLS in their utility to distinguish glaucoma from glaucoma suspect (GS) and for detecting glaucoma progression. Results: A total of 13,679 ODPs with evidence of glaucomatous optic nerve damage from 4106 eyes of 2407 patients with glaucoma or GS were included. Of these eyes, 3264 (79.5%) had a diagnosis of glaucoma, and 842 (20.5%) eyes were GS. Mean ± SD baseline RADAR of GS and glaucoma were 0.67 ± 0.13 and 0.57 ± 0.18, respectively (P < 0.001). Older age, greater IOP fluctuation, baseline MD, right eye, and diagnosis of secondary open-angle glaucoma were associated with slope of RADAR. The mean baseline DDLS of GS and glaucoma were 3.78 and 4.39, respectively. Both RADAR and DDLS showed a less steep slope in advanced glaucoma. In glaucoma, the change of RADAR and DDLS correlated with the corresponding change in MD. RADAR and DDLS had a similar ability to discriminate glaucoma from GS and detect disease progression. Area under the ROC curve of RADAR and DDLS was 0.658 and 0.648. Conclusions: Automated calculation of RADAR and DDLS with a neural network can be used to evaluate the extent and long-term rate of optic disc rim loss and is further evidence of long-term nerve fiber loss in treated patients with glaucoma. Translational Relevance: Our study provides a large clinic-based experience for RADAR and DDLS measurements in GS and glaucoma with a neural network.

Asunto(s)

Progresión de la Enfermedad , Glaucoma , Presión Intraocular , Redes Neurales de la Computación , Disco Óptico , Curva ROC , Humanos , Disco Óptico/patología , Disco Óptico/diagnóstico por imagen , Masculino , Femenino , Persona de Mediana Edad , Presión Intraocular/fisiología , Glaucoma/diagnóstico , Glaucoma/fisiopatología , Anciano , Fotograbar , Enfermedades del Nervio Óptico/diagnóstico , Campos Visuales/fisiología , Pruebas del Campo Visual/métodos , Adulto , Estudios Retrospectivos

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PURPOSE: To compare ganglion cell complex (GCC) and retinal nerve fiber layer (RNFL) rates of change (RoC) in eyes with central or moderate to advanced glaucoma. DESIGN: Prospective cohort study. PARTICIPANTS: A total of 918 matched macular and RNFL OCT scan pairs from 109 eyes (109 patients) enrolled in the Advanced Glaucoma Progression Study with ≥2 years of follow-up and ≥4 OCT scans. METHODS: We exported GCC and RNFL thickness measurements in 49 central macular superpixels and 12 RNFL clock-hour sectors, respectively. We applied our latest Bayesian hierarchical longitudinal model to estimate population and subject-specific baseline thickness (intercepts) and rates of change (RoC) in macular superpixels and RNFL sectors. Global RNFL and GCC RoC were analyzed in a single bivariate longitudinal model to properly compare them accounting for the correlation between their RoC. MAIN OUTCOME MEASURES: Proportion of significant negative (deteriorating) and positive (improving) RoC expressed in µm/year. Standardized RoC were calculated by dividing RoC by the corresponding population SD. Analyses were repeated in eyes with visual field mean deviation (MD) ≤-6 and > -6 dB. RESULTS: Average (SD) 24-2 visual field MD and follow-up length were -8.6 (6.3) dB and 4.2 (0.5) years, respectively. Global RNFL RoC (-0.70 µm/year) were faster than GCC (-0.44 µm/year) (P < .001); corresponding normalized RoC were not significantly different (P = .052). In bivariate analysis, patients with a significant negative global RNFL RoC (n = 63, 57%) or GCC (n = 56, 51%) frequently did so for both outcomes (n = 49, 45%). The average proportion of significantly decreasing RNFL sectors within an eye was 30.7% in eyes with MD > -6 dB compared to 20.5% in those with MD ≤ -6 dB (P = .014); the proportions for GCC superpixels were 21.1% versus 18.7%, respectively (P = .63). CONCLUSIONS: Both GCC and RNFL measures can detect structural progression in glaucoma patients with central damage or moderate to advanced glaucoma. The clinical utility of RNFL imaging decreases with worsening severity of glaucoma.

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PURPOSE: To develop a patient-reported outcome measure to assess the impact of glaucoma and treatment, including minimally invasive glaucoma surgery (MIGS). DESIGN: Observational study before and after concomitant cataract and Food and Drug Administration-approved implantable MIGS device surgery. SETTING: Survey administration was on a computer, iPad, or similar device. PATIENT POPULATION: 184 adults completed the baseline survey, 124 a survey 3 months after surgery, and 106 the 1-month test-retest reliability survey. The age range was 37 to 89 (average age = 72). Most were female (57%), non-Hispanic White (81%), and had a college degree (56%). MAIN OUTCOME MEASURES: The Glaucoma Outcomes Survey (GOS) assesses functional limitations (27 items), vision-related symptoms (7 items), psychosocial issues (7 items), and satisfaction with microinvasive glaucoma surgery (1 item). These multiple-item scales were scored on a 0 to 100 range, with a higher score indicating worse health. RESULTS: Internal consistency reliability estimates ranged from 0.75 to 0.93, and 1-month test-retest intraclass correlations ranged from 0.83 to 0.92 for the GOS scales. Product-moment correlations among the scales ranged from 0.56 to 0.60. Improvement in visual acuity in the study eye from baseline to the 3-month follow-up was significantly related to improvements in GOS functional limitations (r = 0.18, P = .0485), vision-related symptoms (r = 0.19, P = .0386), and psychosocial concerns (r = 0.18, P = .0503). Responders to treatment ranged from 17% for vision-related symptoms to 48% for functional limitations. CONCLUSIONS: This study supports using the GOS for ophthalmic procedures such as MIGS. Further evaluation of the GOS in different patient subgroups and clinical settings is needed.

Asunto(s)

Glaucoma , Procedimientos Quirúrgicos Mínimamente Invasivos , Medición de Resultados Informados por el Paciente , Calidad de Vida , Agudeza Visual , Humanos , Femenino , Masculino , Anciano , Persona de Mediana Edad , Adulto , Anciano de 80 o más Años , Agudeza Visual/fisiología , Reproducibilidad de los Resultados , Encuestas y Cuestionarios , Glaucoma/cirugía , Glaucoma/fisiopatología , Presión Intraocular/fisiología , Perfil de Impacto de Enfermedad , Implantes de Drenaje de Glaucoma , Satisfacción del Paciente

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PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progression with deep learning (DL). DESIGN: Development of a DL algorithm to predict VF progression. METHODS: 3,079 eyes (1,765 patients) with various types of glaucoma and ≥5 VFs, and ≥3 years of follow-up from a tertiary academic center were included. Serial VF mean deviation (MD) rates of change were estimated with linear-regression. VF progression was defined as negative MD slope with p<0.05. A Siamese Neural Network with ResNet-152 backbone pre-trained on ImageNet was designed to predict VF progression using serial optic-disc photographs (ODP), and baseline retinal nerve fiber layer (RNFL) thickness. We tested the model on a separate dataset (427 eyes) with RNFL data from different OCT. The Main Outcome Measure was Area under ROC curve (AUC). RESULTS: Baseline average (SD) MD was 3.4 (4.9)dB. VF progression was detected in 900 eyes (29%). AUC (95% CI) for model incorporating baseline ODP and RNFL thickness was 0.813 (0.757-0.869). After adding the second and third ODPs, AUC increased to 0.860 and 0.894, respectively (p<0.027). This model also had highest AUC (0.911) for predicting fast progression (MD rate <1.0 dB/year). Model's performance was similar when applied to second dataset using RNFL data from another OCT device (AUC=0.893; 0.837-0.948). CONCLUSIONS: DL model predicted VF progression with clinically relevant accuracy using baseline RNFL thickness and serial ODPs and can be implemented as a clinical tool after further validation.

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Aprendizaje Profundo , Progresión de la Enfermedad , Presión Intraocular , Fibras Nerviosas , Disco Óptico , Curva ROC , Células Ganglionares de la Retina , Tomografía de Coherencia Óptica , Pruebas del Campo Visual , Campos Visuales , Humanos , Campos Visuales/fisiología , Células Ganglionares de la Retina/patología , Tomografía de Coherencia Óptica/métodos , Femenino , Masculino , Fibras Nerviosas/patología , Disco Óptico/patología , Disco Óptico/diagnóstico por imagen , Persona de Mediana Edad , Presión Intraocular/fisiología , Anciano , Glaucoma/fisiopatología , Glaucoma/diagnóstico , Estudios de Seguimiento , Algoritmos , Trastornos de la Visión/fisiopatología , Trastornos de la Visión/diagnóstico , Enfermedades del Nervio Óptico/diagnóstico , Enfermedades del Nervio Óptico/fisiopatología , Estudios Retrospectivos , Área Bajo la Curva , Glaucoma de Ángulo Abierto/fisiopatología , Glaucoma de Ángulo Abierto/diagnóstico

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Purpose: To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE)-smoothing algorithms to reduce variability and enhance the performance of glaucoma visual field (VF) progression models. Design: Longitudinal cohort study. Subjects: 7150 eyes (4232 patients), with ≥ 5 years of follow-up and ≥ 6 visits. Methods: Vsual field thresholds were smoothed with the NN and VAE algorithms. The mean total deviation (mTD) and VF index rates, pointwise linear regression (PLR), permutation of PLR (PoPLR), and the glaucoma rate index were applied to the unsmoothed and smoothed data. Main Outcome Measures: The proportion of progressing eyes and the conversion to progression were compared between the smoothed and unsmoothed data. A simulation series of noiseless VFs with various patterns of glaucoma damage was used to evaluate the specificity of the smoothing models. Results: The mean values of age and follow-up time were 62.8 (standard deviation: 12.6) years and 10.4 (standard deviation: 4.7) years, respectively. The proportion of progression was significantly higher for the NN and VAE smoothed data compared with the unsmoothed data. VF progression occurred significantly earlier with both smoothed data compared with unsmoothed data based on mTD rates, PLR, and PoPLR methods. The ability to detect the progressing eyes was similar for the unsmoothed and smoothed data in the simulation data. Conclusions: Smoothing VF data with NN and VAE algorithms improves the signal-to-noise ratio for detection of change, results in earlier detection of VF progression, and could help monitor glaucoma progression more effectively in the clinical setting. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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PURPOSE: Demonstrate that a novel Bayesian hierarchical spatial longitudinal (HSL) model identifies macular superpixels with rapidly deteriorating ganglion cell complex (GCC) thickness more efficiently than simple linear regression (SLR). DESIGN: Prospective cohort study. SETTING: Tertiary Glaucoma Center. SUBJECTS: One hundred eleven eyes (111 patients) with moderate to severe glaucoma at baseline and ≥4 macular optical coherence tomography scans and ≥2 years of follow-up. OBSERVATION PROCEDURE: Superpixel-patient-specific GCC slopes and their posterior variances in 49 superpixels were derived from our latest Bayesian HSL model and Bayesian SLR. A simulation cohort was created with known intercepts, slopes, and residual variances in individual superpixels. MAIN OUTCOME MEASURES: We compared HSL and SLR in the fastest progressing deciles on (1) proportion of superpixels identified as significantly progressing in the simulation study and compared to SLR slopes in cohort data; (2) root mean square error (RMSE), and SLR/HSL RMSE ratios. RESULTS: Cohort- In the fastest decile of slopes per SLR, 77% and 80% of superpixels progressed significantly according to SLR and HSL, respectively. The SLR/HSL posterior SD ratio had a median of 1.83, with 90% of ratios favoring HSL. Simulation- HSL identified 89% significant negative slopes in the fastest progressing decile vs 64% for SLR. SLR/HSL RMSE ratio was 1.36 for the fastest decile of slopes, with 83% of RMSE ratios favoring HSL. CONCLUSION: The Bayesian HSL model improves the estimation efficiency of local GCC rates of change regardless of underlying true rates of change, particularly in fast progressors.

Asunto(s)

Glaucoma , Presión Intraocular , Humanos , Modelos Lineales , Estudios Prospectivos , Teorema de Bayes , Campos Visuales , Fibras Nerviosas , Células Ganglionares de la Retina , Glaucoma/diagnóstico , Tomografía de Coherencia Óptica/métodos

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Purpose: Demonstrate that a novel Bayesian hierarchical spatial longitudinal (HSL) model improves estimation of local macular ganglion cell complex (GCC) rates of change compared to simple linear regression (SLR) and a conditional autoregressive (CAR) model. Methods: We analyzed GCC thickness measurements within 49 macular superpixels in 111 eyes (111 patients) with four or more macular optical coherence tomography scans and two or more years of follow-up. We compared superpixel-patient-specific estimates and their posterior variances derived from the latest version of a recently developed Bayesian HSL model, CAR, and SLR. We performed a simulation study to compare the accuracy of intercept and slope estimates in individual superpixels. Results: HSL identified a significantly higher proportion of significant negative slopes in 13/49 superpixels and a significantly lower proportion of significant positive slopes in 21/49 superpixels than SLR. In the simulation study, the median (tenth, ninetieth percentile) ratio of mean squared error of SLR [CAR] over HSL for intercepts and slopes were 1.91 (1.23, 2.75) [1.51 (1.05, 2.20)] and 3.25 (1.40, 10.14) [2.36 (1.17, 5.56)], respectively. Conclusions: A novel Bayesian HSL model improves estimation accuracy of patient-specific local GCC rates of change. The proposed model is more than twice as efficient as SLR for estimating superpixel-patient slopes and identifies a higher proportion of deteriorating superpixels than SLR while minimizing false-positive detection rates. Translational Relevance: The proposed HSL model can be used to model macular structural measurements to detect individual glaucoma progression earlier and more efficiently in clinical and research settings.

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Glaucoma , Humanos , Teorema de Bayes , Glaucoma/diagnóstico , Ojo , Nonoxinol , Tomografía de Coherencia Óptica

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PURPOSE: Review hypotony failure criteria used in glaucoma surgical outcome studies and evaluate their impact on success rates. DESIGN: Systematic literature review and application of hypotony failure criteria to 2 retrospective cohorts. PARTICIPANTS: A total of 934 eyes and 1765 eyes undergoing trabeculectomy and deep sclerectomy (DS) with a median follow-up of 41.4 and 45.4 months, respectively. METHODS: Literature-based hypotony failure criteria were applied to patient cohorts. Intraocular pressure (IOP)-related success was defined as follows: (A) IOP ≤ 21 mmHg with ≥ 20% IOP reduction; (B) IOP ≤ 18 mmHg with ≥ 20% reduction; (C) IOP ≤ 15 mmHg with ≥ 25% reduction; and (D) IOP ≤ 12 mmHg with ≥ 30% reduction. Failure was defined as IOP exceeding these criteria in 2 consecutive visits > 3 months after surgery, loss of light perception, additional IOP-lowering surgery, or hypotony. Cox regression estimated failure risk for different hypotony criteria, using no hypotony as a reference. Analyses were conducted for each criterion and hypotony type (i.e., numerical [IOP threshold], clinical [clinical manifestations], and mixed [combination of numerical or clinical criteria]). MAIN OUTCOME MEASURES: Hazard ratio (HR) for failure risk. RESULTS: Of 2503 studies found, 278 were eligible, with 99 studies (35.6%) lacking hypotony failure criteria. Numerical hypotony was predominant (157 studies [56.5%]). Few studies used clinical hypotony (3 isolated [1.1%]; 19 combined with low IOP [6.8%]). Forty-nine different criteria were found, with IOP < 6 mmHg, IOP < 6 mmHg on ≥ 2 consecutive visits after 3 months, and IOP < 5 mmHg being the most common (41 [14.7%], 38 [13.7%], and 13 [4.7%] studies, respectively). In both cohorts, numerical hypotony posed the highest risk of failure (HR, 1.51-1.21 for criteria A to D; P < 0.001), followed by mixed hypotony (HR, 1.41-1.20 for criteria A to D; P < 0.001), and clinical hypotony (HR, 1.12-1.04; P < 0.001). Failure risk varied greatly with various hypotony definitions, with the HR ranging from 1.02 to 10.79 for trabeculectomy and 1.00 to 8.36 for DS. CONCLUSIONS: Hypotony failure criteria are highly heterogenous in the glaucoma literature, with few studies focusing on clinical manifestations. Numerical hypotony yields higher failure rates than clinical hypotony and can underestimate glaucoma surgery success rates. Standardizing failure criteria with an emphasis on clinically relevant hypotony manifestations is needed. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Asunto(s)

Glaucoma , Presión Intraocular , Hipotensión Ocular , Tonometría Ocular , Trabeculectomía , Insuficiencia del Tratamiento , Humanos , Presión Intraocular/fisiología , Hipotensión Ocular/fisiopatología , Estudios Retrospectivos , Glaucoma/cirugía , Glaucoma/fisiopatología , Esclerostomía/métodos , Femenino , Estudios de Seguimiento , Masculino , Agudeza Visual/fisiología

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PURPOSE: To determine the prevalence and magnitude of optical coherence tomography (OCT) exposed neural canal (ENC), externally oblique choroidal border tissue (EOCBT), and exposed scleral flange (ESF) regions in 362 non-highly myopic (spherical equivalent -6.00 to 5.75 diopters) eyes of 362 healthy subjects. DESIGN: Cross-sectional study. METHODS: After OCT optic nerve head (ONH) imaging, Bruch membrane opening (BMO), the anterior scleral canal opening (ASCO), and the scleral flange opening (SFO) were manually segmented. BMO, ASCO, and SFO points were projected to the BMO reference plane. The direction and magnitude of BMO/ASCO offset as well as the magnitude of ENC, EOCBT, and ESF was calculated within 30° sectors relative to the foveal-BMO axis. Hi-ESF eyes demonstrated an ESF ≥100 µm in at least 1 sector. Sectoral peri-neural canal choroidal thickness (pNC-CT) was measured and correlations between the magnitude of sectoral ESF and proportional pNC-CT were assessed. RESULTS: Seventy-three Hi-ESF (20.2%) and 289 non-Hi-ESF eyes (79.8%) were identified. BMO/ASCO offset as well as ENC, EOCBT, and ESF prevalence and magnitude were greatest inferior temporally where the pNC-CT was thinnest. Among Hi-ESF eyes, the magnitude of each ENC region correlated with the BMO/ASCO offset magnitude, and the sectors with the longest ESF correlated with the sectors with proportionally thinnest pNC-CT. CONCLUSIONS: ONH BMO/ASCO offset, either as a cause or result of ONH neural canal remodeling, corresponds with the sectoral location of maximum ESF and minimum pNC-CT in non-highly myopic eyes. Longitudinal studies to characterize the development and clinical implications of ENC Hi-ESF regions in non-highly myopic and highly myopic eyes are indicated.

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Miopía , Disco Óptico , Humanos , Tomografía de Coherencia Óptica/métodos , Tubo Neural , Estudios Transversales , Miopía/diagnóstico , Lámina Basal de la Coroides , Presión Intraocular

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PURPOSE: To identify factors associated with glaucomatous progression in individuals with small and large optic discs. DESIGN: Retrospective review. SUBJECTS: 4505 individuals with glaucoma at UCLA; 233 (59.7%) with small discs, 157 (40.3%) with large discs. METHODS: Small and large disc sizes were defined by OCT or Heidelberg Retinal Tomography as disc area ≤ 5% (≤ 1.3 mm2) and ≥ 95% (≥ 2.9 mm2), respectively. Medical records were reviewed for demographics, systemic comorbidities, glaucoma type, ocular comorbidities, and ocular surgery. Logistic regression was used to identify predictors of visual field (VF) progression in individuals with small and large discs and predictors of large versus small discs. MAIN OUTCOME MEASURES: The VF deterioration with mean deviation, pointwise linear regression, and glaucoma rate index (GRI); large vs. small disc. RESULTS: In individuals with small discs, Asian versus non-Hispanic White ethnicity was associated with increased progression (adjusted odds ratio [aOR] = 4.05; 95% confidence interval [CI] = 1.12-14.59 for GRI). Higher intraocular pressure (IOP) range and peak were associated with increased progression in individuals with both small discs (aOR = 1.12; 95% CI = 1.00-1.27 and aOR = 1.05; 95% CI = 1.00-1.10 per 1 mmHg for range and peak with GRI) and large discs (aOR = 1.35; 95% CI = 1.12-1.66 and aOR = 1.11; 95% CI = 1.03-1.20 per 1 mmHg for range and peak with GRI). Multivariable predictors of having large vs. small discs included vasospastic phenotype (aOR = 2.58; 95% CI = 1.35-5.19) and Black (aOR = 20.46; 95% CI = 8.33-61.84), Hispanic/Latino (aOR = 9.65; 95% CI = 4.14-25.39), Asian (aOR = 4.87; 95% CI = 2.96-8.1), and other (aOR = 2.79; 95% CI = 1.69-4.63) versus non-Hispanic White ethnicity. CONCLUSIONS: Increased odds of glaucomatous progression were associated with Asian vs. non-Hispanic White ethnicity in glaucoma patients with small optic discs, as well as with increased IOP range and peak in those with small and large discs. Individuals with a vasospastic phenotype and those from racial and ethnic minority backgrounds had increased odds of having large vs. small optic discs. Further characterization of discernible phenotypes would improve disease prognostication and help individualize glaucoma treatment. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Asunto(s)

Glaucoma , Disco Óptico , Humanos , Etnicidad , Presión Intraocular , Grupos Minoritarios , Glaucoma/diagnóstico

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PURPOSE: To report the contributing factors to the successful long-term treatment outcomes of a large series of patients with malignant glaucoma (MG). DESIGN: Retrospective, interventional, consecutive case series. PARTICIPANTS: This study used data collected from 1997 to 2022 from the Glaucoma Division of the Stein Eye Institute, University of California, Los Angeles (UCLA). All patients with MG who underwent treatment at UCLA were enrolled. METHODS: The following demographic and clinical data were collected and analyzed for their relevance to successful treatment: age, gender, ethnicity, glaucoma family history, visual acuity (VA), intraocular pressure (IOP), lens status, prior glaucoma diagnosis, prior ocular surgery, prior use of antiglaucoma agents, ultrasonic axial length, qualitative anterior chamber (AC) depth, and treatment methods and outcomes. MAIN OUTCOME MEASURES: Anatomical success was defined as restoration of normal AC depth, indicating relief of the MG episode. Complete success was defined as anatomical success and the reduction of IOP to < 21 mmHg without further surgery, with or without medications. RESULTS: A total of 74 eyes of 73 patients were identified with a diagnosis of MG. The median (interquartile range) age of the patients at the time of MG presentation was 70 years (19.5) and 49 (75.4%) patients were female. The most common prior diagnosis before MG was primary angle closure glaucoma (PACG) (34 eyes, 51.5%). The initiating event for 30 eyes (45.5%) was glaucoma surgery and for 21 eyes (31.8%) was cataract surgery. Most eyes were pseudophakic (57, 86.4%). Fifty-six eyes underwent medical treatment; MG resolved in 2 eyes with medical treatment alone. Nine eyes (7 eyes = treatment naïve; 2 eyes = failed medical treatment) underwent laser treatment and MG resolved in 5 eyes. Among the 55 eyes which had surgical treatment, 52 eyes failed medical treatment and 3 eyes were treatment naïve. The anatomical success rate with surgical treatment was 96.4% and the most commonly performed surgical procedure was combined pars plana antero-central vitrectomy, hyaloido-zonulectomy, and iridectomy. CONCLUSIONS: Female gender, PACG, and glaucoma surgery were predisposing factors for the development of MG. Medical treatment alone for MG was inadequate in the vast majority of cases. A surgical technique consisting of combined pars plana antero-central vitrectomy, hyaloido-zonulectomy and iridectomy consistently produced high long-term success. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Asunto(s)

Glaucoma , Presión Intraocular , Agudeza Visual , Humanos , Femenino , Masculino , Estudios Retrospectivos , Presión Intraocular/fisiología , Anciano , Persona de Mediana Edad , Estudios de Seguimiento , Glaucoma/fisiopatología , Glaucoma/diagnóstico , Glaucoma/cirugía , Resultado del Tratamiento , Factores de Tiempo , Anciano de 80 o más Años , Antihipertensivos/uso terapéutico , Adulto , Trabeculectomía/métodos

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Purpose: Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL). Methods: This study included 1121 OCT volume scans and 10-2 VFs from 289 eyes (257 patients). Macular scans were used to estimate 10-2 VF mean deviation (MD), threshold sensitivities (TS), and total deviation (TD) values at 68 locations. A three-dimensional (3D) convolutional neural network based on the 3D DenseNet121 architecture was used for prediction. We compared DL predictions to those from baseline linear models. We carried out 10-fold stratified cross-validation to optimize generalizability. The performance of the DL and baseline models was compared based on correlations between ground truth and predicted VF measures and mean absolute error (MAE; ground truth - predicted values). Results: Average (SD) MD was -9.3 (7.7) dB. Average (SD) correlations between predicted and ground truth MD and MD MAE were 0.74 (0.09) and 3.5 (0.4) dB, respectively. Estimation accuracy deteriorated with worsening MD. Average (SD) Pearson correlations between predicted and ground truth TS and MAEs for DL and baseline model were 0.71 (0.05) and 0.52 (0.05) (P < 0.001) and 6.5 (0.6) and 7.5 (0.5) dB (P < 0.001), respectively. For TD, correlation (SD) and MAE (SD) for DL and baseline models were 0.69 (0.02) and 0.48 (0.05) (P < 0.001) and 6.1 (0.5) and 7.8 (0.5) dB (P < 0.001), respectively. Conclusions: Macular OCT volume scans can be used to predict global central VF parameters with clinically relevant accuracy. Translational Relevance: Macular OCT imaging may be used to confirm and supplement central VF findings using deep learning.

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Aprendizaje Profundo , Tomografía de Coherencia Óptica , Humanos , Campos Visuales , Ojo , Redes Neurales de la Computación

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AIM: We tested the hypothesis that visual field (VF) progression can be predicted with a deep learning model based on longitudinal pairs of optic disc photographs (ODP) acquired at earlier time points during follow-up. METHODS: 3919 eyes (2259 patients) with ≥2 ODPs at least 2 years apart, and ≥5 24-2 VF exams spanning ≥3 years of follow-up were included. Serial VF mean deviation (MD) rates of change were estimated starting at the fifth visit and subsequently by adding visits until final visit. VF progression was defined as a statistically significant negative slope at two consecutive visits and final visit. We built a twin-neural network with ResNet50-backbone. A pair of ODPs acquired up to a year before the VF progression date or the last VF in non-progressing eyes were included as input. Primary outcome measures were area under the receiver operating characteristic curve (AUC) and model accuracy. RESULTS: The average (SD) follow-up time and baseline VF MD were 8.1 (4.8) years and -3.3 (4.9) dB, respectively. VF progression was identified in 761 eyes (19%). The median (IQR) time to progression in progressing eyes was 7.3 (4.5-11.1) years. The AUC and accuracy for predicting VF progression were 0.862 (0.812-0.913) and 80.0% (73.9%-84.6%). When only fast-progressing eyes were considered (MD rate < -1.0 dB/year), AUC increased to 0.926 (0.857-0.994). CONCLUSIONS: A deep learning model can predict subsequent glaucoma progression from longitudinal ODPs with clinically relevant accuracy. This model may be implemented, after validation, for predicting glaucoma progression in the clinical setting.

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To explore the temporal profile of retinal proteomes specific to primary and secondary retinal ganglion cell (RGC) loss. Unilateral partial optic nerve transection (pONT) was performed on the temporal side of the rat optic nerve. Temporal and nasal retinal samples were collected at 1, 4 and 8 weeks after pONT (n = 4 each) for non-biased profiling with a high-resolution hybrid quadrupole time-of-flight mass spectrometry running on label-free SWATHTM acquisition (SCIEX). An information-dependent acquisition ion library was generated using ProteinPilot 5.0 and OneOmics cloud bioinformatics. Combined proteome analysis detected 2531 proteins with a false discovery rate of <1%. Compared to the nasal retina, 10, 25 and 61 significantly regulated proteins were found in the temporal retina at 1, 4, and 8 weeks, respectively (p < 0.05, FC ≥ 1.4 or ≤0.7). Eight proteins (ALDH1A1, TRY10, GFAP, HBB-B1, ALB, CDC42, SNCG, NEFL) were differentially expressed for at least two time points. The expressions of ALDH1A1 and SNCG at nerve fibers were decreased along with axonal loss. Increased ALDH1A1 localization in the inner nuclear layer suggested stress response. Increased GFAP expression demonstrated regional reactivity of astrocytes and Muller cells. Meta-analysis of gene ontology showed a pronounced difference in endopeptidase and peptidase inhibitor activity. Temporal proteomic profiling demonstrates established and novel protein targets associated with RGC damage.

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BACKGROUND: Which phenotypes are we able to recognize in the optic nerve of patients with primary open angle glaucoma? METHODS: Retrospective interventional case series. 885 eyes from 885 patients at an outpatient tertiary care centre who met specified criteria for POAG were included. Disc photographs were classified by three glaucoma specialists into the following phenotypes according to their predominant characteristics: (1) concentric rim thinning, (2) focal rim thinning, (3) acquired pit of the optic nerve (APON), (4) tilted, (5) extensive peripapillary atrophy (PPA), and (6) broad rim thinning. Demographic, medical, and ocular data were collected. Kruskal-Wallis was used as a non-parametric test and pairwise comparison was performed by using Wilcoxon rank sum test corrected. RESULTS: Phenotypic distribution was as follows: 398(45%) focal thinning, 153(18%) concentric thinning, 153(17%) broad thinning, 109(12%) tilted, 47(5%) extensive PPA and 25(3%) APON. Phenotypic traits of interest included a higher proportion of female patients with the focal thinning phenotype (p = 0.015); myopia (p = 0.000), Asian race (OR: 8.8, p = 0.000), and younger age (p = 0.000) were associated with the tilted phenotype; the concentric thinning patients had thicker RNFL (p = 0.000), higher MD (p = 0.008) and lower PSD (p = 0.043) than broad thinning, despite no difference in disc sizes (p = 0.849). The focal thinning group had a localized VF pattern with high PSD compared to concentric thinning (p = 0.005). CONCLUSION: We report six phenotypic classifications of POAG patients with demographic and ocular differences between phenotypes. Future refinement of phenotypes should allow enhanced identification of genetic associations and improved individualization of patient care.

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Glaucoma de Ángulo Abierto , Disco Óptico , Humanos , Femenino , Glaucoma de Ángulo Abierto/diagnóstico , Glaucoma de Ángulo Abierto/complicaciones , Estudios Retrospectivos , Campos Visuales , Presión Intraocular , Tomografía de Coherencia Óptica

RESUMEN

PURPOSE: To compare rates of change (RoC) of peripapillary retinal nerve fiber layer (RNFL) and Bruch membrane opening-based minimum rim width (BMO-MRW) thickness in moderate-to-advanced glaucoma. DESIGN: Prospective cohort study. METHODS: Longitudinal optical coherence tomography (OCT) optic nerve head volume scans of 113 eyes of 113 glaucoma patients with moderate-to-advanced or central damage were exported. This study estimated and compared global and sectoral RoC with linear mixed effects models and simple linear regression (SLR) of RNFL and BMO-MRW thickness. Permutation analyses were used to test significance of RoC in the SLR model. It also compared longitudinal signal-to-noise ratios (LSNR) defined as RoC divided by residual standard deviation (SD) between the two groups. RESULTS: Mean (SD) follow-up and median (IQR) OCT scan sessions were 5.2 (1.3) years and 10 (8-11), respectively. Baseline average (SD) visual field mean deviation was -9.2 (5.8) dB. Based on SLR, a higher proportion of significant negative RNFL RoC was observed compared to BMO-MRW in the inferotemporal (35% vs 20%; P = .015) and inferonasal (42% vs 17%; P < .001) sectors. Permutation analyses also demonstrated a higher proportion of worsening RNFL RoC than BMO-MRW in the inferotemporal (P = .026) and inferonasal (P < .001) sectors along with overall lower positive RoC. Longitudinal signal-to-noise ratios for RNFL were significantly more negative than for BMO-MRW globally, and in the inferotemporal, inferonasal, and superonasal sectors (P ≤ .01). CONCLUSIONS: Longitudinal RNFL OCT measurements are more likely to detect structural change and demonstrate better LSNR compared with BMO-MRW in eyes with central or moderate-to-advanced glaucoma damage at baseline.

Asunto(s)

Lámina Basal de la Coroides , Glaucoma , Retina , Fibras Nerviosas/patología , Nervio Óptico , Humanos , Tomografía de Coherencia Óptica , Estudios Prospectivos , Estudios de Cohortes , Masculino , Femenino , Persona de Mediana Edad , Anciano , Anciano de 80 o más Años

RESUMEN

PURPOSE: To measure visual field (VF) rates of change after Ahmed Glaucoma Valve (AGV) implantation and to investigate risk factors for progression. DESIGN: Retrospective, clinical cohort study. METHODS: Patients who underwent AGV implantation with at least 4 eligible postoperative VFs and 2 years of follow-up were included. Baseline, intraoperative, and postoperative data were collected. VF progression was explored with 3 methods: mean deviation (MD) rate; glaucoma rate index (GRI); and pointwise linear regression (PLR). For a subset of eyes with sufficient preoperative and postoperative VFs, rates were compared between the 2 periods. RESULTS: A total of 173 eyes were included. The intraocular pressure (IOP) and number of glaucoma medications were significantly reduced from a median (interquartile range [IQR]) of 23.5 (12.1) mm Hg at baseline to 12.8 (4.0) mm Hg at final follow-up, and from (mean ± SD) 3.3 ± 1.2 to 2.2 ± 1.4, respectively. A total of 38 eyes (22%) showed VF progression, and 101 eyes (58%) were stable as assessed by all 3 methods, which accounted for 80% of all eyes. The rate of VF decline by MD and GRI was a median (IQR) of -0.30 (0.8) dB/y and -2.30 (10.6) (of -100), respectively. When comparing progression before and after surgery, the reduction was not statistically significant with any of the methods. The peak IOP (after 3 postoperative months) was associated with VF deterioration, with a 7% increase in risk per each additional millimeter of mercury (mm Hg). CONCLUSIONS: To our knowledge, this is the largest published series reporting long-term VF outcomes after glaucoma drainage device implantation. There is a continued, significant rate of VF decline after AGV surgery.

Asunto(s)

Implantes de Drenaje de Glaucoma , Glaucoma , Humanos , Campos Visuales , Estudios Retrospectivos , Estudios de Cohortes , Estudios de Seguimiento , Trastornos de la Visión/cirugía , Glaucoma/cirugía , Presión Intraocular , Resultado del Tratamiento , Implantación de Prótesis

RESUMEN

PRCIS: This study examined the association between dietary niacin intake and glaucoma in the 2005-2008 National Health and Nutrition Examination Survey (NHANES). Increased niacin intake was associated with lower odds of glaucoma overall and among women. PURPOSE: To examine the association between dietary niacin intake and glaucoma in the 2005-2008 NHANES. MATERIALS AND METHODS: This cross-sectional study included adult participants of the 2005-2008 NHANES. The exposure was dietary niacin intake, which was examined as a continuous and categorical variable. The outcome was glaucoma as defined by regraded disc images. Covariates included age, sex, race/ethnicity, education level, income, body mass index, smoking status, alcohol use, cardiovascular disease, diabetes mellitus, daily energy intake, vitamin B2 and B6 consumption, and macular degeneration. Adjusting for all covariates, logistic regression was performed to examine the association between niacin intake and glaucoma in the overall population and stratified by sex. RESULTS: The weighted population included 5371 individuals (109,734,124 weighted), of whom 55 (1.0%) had glaucoma. Each 1 mg increase in niacin intake was associated with a 6% decreased odds of glaucoma odds [adjusted odds ratio (aOR) = 0.94, 95% CI = 0.90, 0.98]. Among women, increased niacin intake was associated with decreased odds of glaucoma both with niacin as a continuous (aOR = 0.89, 95% CI = 0.80, 0.99 per 1 mg increase in niacin intake) and binary variable (aOR = 0.35, 95% CI = 0.14, 0.90 for higher vs lower niacin intake). CONCLUSIONS: In the 2005-2008 NHANES population, higher levels of niacin intake were associated with decreased odds of glaucoma overall and in women. Further studies are needed to examine the potential protective effects of niacin on glaucoma risk.

Asunto(s)

Glaucoma , Niacina , Adulto , Humanos , Femenino , Encuestas Nutricionales , Estudios Transversales , Presión Intraocular , Glaucoma/diagnóstico , Glaucoma/epidemiología , Glaucoma/prevención & control

RESUMEN

PRCIS: We report the survival of surgical revision to glaucoma drainage devices for several indications in a large cohort of patients, with an overall success rate of 45% at 36 months. PURPOSE: To evaluate the outcomes of surgical revision for complications of glaucoma drainage devices. METHODS: Three hundred thirty-five eyes of 318 patients who underwent tube revision or removal at University of California Los Angeles (UCLA) Jules Stein Eye Institute between 1997 and 2019 were included. The pre-defined primary outcome measure was surgical success of the initial revision, defined as resolution of the condition with no additional revisions required, no functionally significant change in vision, and no instances of intraocular pressure > 21 mmHg at 2 consecutive visits postoperatively. Kaplan-Meier survival analysis was applied to evaluate survival at 36 months based on these criteria. The Wilcoxon paired test was used to compare mean preoperative and postoperative intraocular pressure, medication usage, and visual acuity. RESULTS: Overall, survival of revised tubes at 36 months was 45%. The 4 most common indications for revision were exposure of the implant (42% of all revisions), occlusion (14%), corneal failure or threat of failure (12%), and hypotony (11%). Survival at 36 months for each of these indications was 44%, 45%, 52%, and 37%, respectively. CONCLUSIONS: These results suggest that eyes with glaucomatous damage with long-term glaucoma drainage device complications can still have a reasonably successful outcome when a revision is performed. However, with substantial rates of vision loss and a frequent need for additional revisions to manage complications, managing patient expectations for success and making them aware of the likelihood of additional surgeries or failure is important.

Asunto(s)

Implantes de Drenaje de Glaucoma , Presión Intraocular , Humanos , Resultado del Tratamiento , Estudios de Seguimiento , Complicaciones Posoperatorias/cirugía , Estudios Retrospectivos , Córnea

RESUMEN

This study describes the development of a convolutional neural network (CNN) for automated assessment of optic disc photograph quality. Using a code-free deep learning platform, a total of 2377 optic disc photographs were used to develop a deep CNN capable of determining optic disc photograph quality. Of these, 1002 were good-quality images, 609 were acceptable-quality, and 766 were poor-quality images. The dataset was split 80/10/10 into training, validation, and test sets and balanced for quality. A ternary classification model (good, acceptable, and poor quality) and a binary model (usable, unusable) were developed. In the ternary classification system, the model had an overall accuracy of 91% and an AUC of 0.98. The model had higher predictive accuracy for images of good (93%) and poor quality (96%) than for images of acceptable quality (91%). The binary model performed with an overall accuracy of 98% and an AUC of 0.99. When validated on 292 images not included in the original training/validation/test dataset, the model's accuracy was 85% on the three-class classification task and 97% on the binary classification task. The proposed system for automated image-quality assessment for optic disc photographs achieves high accuracy in both ternary and binary classification systems, and highlights the success achievable with a code-free platform. There is wide clinical and research potential for such a model, with potential applications ranging from integration into fundus camera software to provide immediate feedback to ophthalmic photographers, to prescreening large databases before their use in research.