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(1) Objective: This study investigated the relationship between long-term particulate matter (PM2.5) exposure and optic disc parameters—vertical cup-to-disc ratio (vCDR), vertical optic disc diameter (vDD), and vertical optic cup diameter (vCD)—in patients with type 2 diabetes mellitus (T2DM). (2) Methods: A cross-sectional analysis was conducted using data from 65,750 T2DM patients in the 2017–2018 Shanghai Cohort Study of Diabetic Eye Disease (SCODE). Optic disc parameters were extracted from fundus images, and PM2.5 exposure was estimated using a random forest model incorporating satellite and meteorological data. Multivariate linear regression models were applied, adjusting for confounders including age, gender, body mass index, blood pressure, glucose, time of T2DM duration, smoking, drinking, and physical exercise. (3) Results: A 10 μg/m3 increase in PM2.5 exposure was associated with significant reductions in vCDR (−0.008), vDD (−42.547 μm), and vCD (−30.517 μm) (all p-values < 0.001). These associations persisted after sensitivity analyses and adjustments for other pollutants like O3 and NO2. (4) Conclusions: Long-term PM2.5 exposure is associated with detrimental changes in optic disc parameters in patients with T2DM, suggesting possible optic nerve atrophy. Considering the close relationship between the optic nerve and the central nervous system, these findings may also reflect broader neurodegenerative processes. [ABSTRACT FROM AUTHOR]

Background: Glaucoma is a progressive optic nerve disease that, despite its treatment, is associated with retinal ganglion cell damage. However, timely treatment hinders the progression of visual field damage and preserves visual function. Our study aimed to evaluate the treatment outcomes and adverse effects in glaucomatous patients of using a single anti-glaucomatous agent, 0.5% timolol maleate, or 0.005% latanoprost, for 24 months. Methods and Results: This prospective, single-arm, open-label study included 87 patients (47.13% men and 52.87% women) with open-angle glaucoma treated with a single hypotensive agent. The patients were divided into two groups. Group 1 patients (n=43) were treated with 0.5% timolol, and Group 2 patients (n=44) were treated with 0.005% latanoprost. We assessed the intraocular pressure (IOP) in 7 visits for 24 months, the cup-to-disc ratio (CDR), and the drug's side effects. At baseline (Visit 1), Group 1 showed an IOP(OD) of 26.46±1.99 mmHg and an IOP(OS) of 26.34±2.14 mmHg. Group 2 showed an IOP(OD) of 26.18±1.98 mmHg and an IOP(OS) of 26.18±2.03 mmHg. There were no significant differences between the two treatments at the initial stage. At the second follow-up visit, the mean IOP(OD) and IOP(OS) significantly decreased from baseline in both groups. There was no significant difference between the two treatments at this stage. By the third follow-up visit, IOP continued to decrease effectively in both groups, and no significant difference was observed between the two treatments at this stage. At Visits 4 and 5, in Group 1, the IOP remained without significant dynamics compared to Visit 3. At the same time, in Group 2, the IOP continued to decrease slightly. However, no significant difference was observed between the two treatments at these stages. Latanoprost appears to result in slightly lower IOP levels overall. By the sixth follow-up visit, IOP continued to decrease effectively in both groups. Although latanoprost provided lower IOP values, there was no significant difference between groups. By Visit 7, the difference between the two treatments becomes more noticeable. Group 1 has an IOP(OD) of 16.09±1.26 mmHg and IOP(OS) of 16.00±1.38 mmHg, while Group 2 continued to show lower IOP levels: IOP(OD) of 14.18±1.04 mmHg and IOP(OS) of 14.13±1.09 mmHg. The differences between the groups became significant (P=0.029), indicating that latanoprost was more effective in reducing IOP in the long term. Changes in the CDR used to assess the optic nerve were assessed before and after 24 months of treatment. In Group 1, CDR before treatment was 0.451±0.112 and slightly increased by the end of treatment to 0.484±0.123. In Group 2, CDR before treatment was 0.436±0.138 and slightly increased to 0.452±0.15. With timolol therapy, side effects were found in 11(25.58%) patients, and with latanoprost therapy only in 7(15.9%) patients. Although the differences were not statistically significant, latanoprost had a slightly more favorable safety profile than timolol. Conclusion: The consistently lower mean IOP values for latanoprost treatment suggest it may be more effective in reducing IOP than timolol. However, the lack of statistically significant differences indicates that while one may perform slightly better on average, both treatments are generally effective and may be chosen based on individual patient needs and tolerability.

Abstract Background To investigate the relationship between changes in the optic disc size and color, cup-to-disc (C/D) ratio, and axial elongation in schoolchildren. Methods A prospective cohort study was performed in 75 right eyes of elementary school students for six years (from 8.5 to 14.5 years old). In the first and last year, all participants underwent optical axial length measurement and color fundus photography. The optic disc color was calculated by dividing the intensity of red by the sum of the intensity of red, green, and blue. The optic disc area was calculated by modifying the number of pixels according to Bennett’s formula. The C/D ratio was calculated by dividing the vertical cup diameter by vertical optic disc diameter. Wilcoxon signed rank test was used to compare these optic disc parameters and axial length in the first and last year. Results Mean axial length in the last year (24.82 mm) was significantly longer than that in the first year (23.34 mm). Likewise, the mean optic disc size was significantly smaller in the last year (41,946 pixels) than that in the first year (46,144 pixels). The mean optic disc color in the last year (0.49) was significantly more reddish than that in the first year (0.46), while the mean C/D ratio in last year (0.50) was significantly smaller than that in first year (0.52). Conclusions During the period from 8.5 years to 14.5 years of age, both the optic disc size and C/D ratio became smaller, while the color became more red.

Background: To investigate the relationship between changes in the optic disc size and color, cup-to-disc (C/D) ratio, and axial elongation in schoolchildren. Methods: A prospective cohort study was performed in 75 right eyes of elementary school students for six years (from 8.5 to 14.5 years old). In the first and last year, all participants underwent optical axial length measurement and color fundus photography. The optic disc color was calculated by dividing the intensity of red by the sum of the intensity of red, green, and blue. The optic disc area was calculated by modifying the number of pixels according to Bennett's formula. The C/D ratio was calculated by dividing the vertical cup diameter by vertical optic disc diameter. Wilcoxon signed rank test was used to compare these optic disc parameters and axial length in the first and last year. Results: Mean axial length in the last year (24.82 mm) was significantly longer than that in the first year (23.34 mm). Likewise, the mean optic disc size was significantly smaller in the last year (41,946 pixels) than that in the first year (46,144 pixels). The mean optic disc color in the last year (0.49) was significantly more reddish than that in the first year (0.46), while the mean C/D ratio in last year (0.50) was significantly smaller than that in first year (0.52). Conclusions: During the period from 8.5 years to 14.5 years of age, both the optic disc size and C/D ratio became smaller, while the color became more red. [ABSTRACT FROM AUTHOR]

In this work, we aim to introduce some modifications to the Anam-Net deep neural network (DNN) model for segmenting optic cup (OC) and optic disc (OD) in retinal fundus images to estimate the cup-to-disc ratio (CDR). The CDR is a reliable measure for the early diagnosis of Glaucoma. In this study, we developed a lightweight DNN model for OC and OD segmentation in retinal fundus images. Our DNN model is based on modifications to Anam-Net, incorporating an anamorphic depth embedding block. To reduce computational complexity, we employ a fixed filter size for all convolution layers in the encoder and decoder stages as the network deepens. This modification significantly reduces the number of trainable parameters, making the model lightweight and suitable for resource-constrained applications. We evaluate the performance of the developed model using two publicly available retinal image databases, namely RIM-ONE and Drishti-GS. The results demonstrate promising OC segmentation performance across most standard evaluation metrics while achieving analogous results for OD segmentation. We used two retinal fundus image databases named RIM-ONE and Drishti-GS that contained 159 images and 101 retinal images, respectively. For OD segmentation using the RIM-ONE we obtain an f1-score (F1), Jaccard coefficient (JC), and overlapping error (OE) of 0.950, 0.9219, and 0.0781, respectively. Similarly, for OC segmentation using the same databases, we achieve scores of 0.8481 (F1), 0.7428 (JC), and 0.2572 (OE). Based on these experimental results and the significantly lower number of trainable parameters, we conclude that the developed model is highly suitable for the early diagnosis of glaucoma by accurately estimating the CDR. [ABSTRACT FROM AUTHOR]

PurposeCompare cup-to-disc ratio (CDR) measured by clinical assessment and optical coherence tomography (OCT) in pediatric eyes being monitored as glaucoma suspects for suspicious optic disc appearance.DesignRetrospective cross-sectional study.MethodsAn institutional study following 221 eyes from 122 unique pediatric glaucoma suspects being monitored due to increased or asymmetric appearance of CDR. Ophthalmologic findings, including visual acuity, intraocular pressure, CDR measured by clinical assessment, average retinal nerve fiber layer thickness, and average CDR measured by OCT, were recorded for each participant’s initial and final examinations. CDRs measured clinically and by OCT were compared at both initial and final presentations.ResultsAverage age at presentation was 9.0 years old (95% CI: 8.0-9.9), and mean length of follow-up was 5.0 years (95% CI: 5.4-4.5). At initial presentation, 53 eyes had CDRs recorded by both clinical assessment and OCT, and at final presentation, 93 eyes had CDRs measured by both modalities. CDR measured by OCT was significantly larger than CDR measured clinically on initial and final presentation (p=0.002, p

(1) Objective: This study investigated the relationship between long-term particulate matter (PM2.5) exposure and optic disc parameters—vertical cup-to-disc ratio (vCDR), vertical optic disc diameter (vDD), and vertical optic cup diameter (vCD)—in patients with type 2 diabetes mellitus (T2DM). (2) Methods: A cross-sectional analysis was conducted using data from 65,750 T2DM patients in the 2017–2018 Shanghai Cohort Study of Diabetic Eye Disease (SCODE). Optic disc parameters were extracted from fundus images, and PM2.5 exposure was estimated using a random forest model incorporating satellite and meteorological data. Multivariate linear regression models were applied, adjusting for confounders including age, gender, body mass index, blood pressure, glucose, time of T2DM duration, smoking, drinking, and physical exercise. (3) Results: A 10 μg/m3 increase in PM2.5 exposure was associated with significant reductions in vCDR (−0.008), vDD (−42.547 μm), and vCD (−30.517 μm) (all p-values < 0.001). These associations persisted after sensitivity analyses and adjustments for other pollutants like O3 and NO2. (4) Conclusions: Long-term PM2.5 exposure is associated with detrimental changes in optic disc parameters in patients with T2DM, suggesting possible optic nerve atrophy. Considering the close relationship between the optic nerve and the central nervous system, these findings may also reflect broader neurodegenerative processes.

Background/Aims: Primary open-angle glaucoma (POAG) disproportionately affects individuals of African ancestry. In these patients' eyes, a large cup-to-disc ratio (LCDR > 0.90) suggests greater retinal ganglion cell loss, though these patients often display varied visual ability. This study investigated the prevalence and risk factors associated with LCDR in African ancestry individuals with POAG and explored the differences between blind (>20/200) and not blind (≤20/200) LCDR eyes. Methods: A case–control methodology was used to investigate the demographic, optic disc, and genetic risk factors of subjects in the Primary Open-Angle African American Glaucoma Genetics Study. Risk factors were analyzed using univariable and multivariable logistic regression models with inter-eye correlation adjusted using generalized estimating equations. Results: Out of 5605 eyes with POAG, 1440 eyes (25.7%) had LCDR. In the multivariable analysis, LCDR was associated with previous glaucoma surgery (OR = 1.72), increased intraocular pressure (OR = 1.04), decreased mean deviation (OR = 1.08), increased pattern standard deviation (OR = 1.06), thinner retinal nerve fiber layer (OR = 1.05), nasalization of vessels (OR = 2.67), bayonetting of vessels (OR = 1.98), visible pores in the lamina cribrosa (OR = 1.68), and a bean-shaped cup (OR = 2.11). Of LCDR eyes, 30.1% were classified as blind (≤20/200). In the multivariable analysis, the statistically significant risk factors of blindness in LCDR eyes were previous glaucoma surgery (OR = 1.72), increased intraocular pressure (OR = 1.05), decreased mean deviation (OR = 1.04), and decreased pattern standard deviation (OR = 0.90). Conclusions: These findings underscore the importance of close monitoring of intraocular pressure and visual function in African ancestry POAG patients, particularly those with LCDR, to preserve visual function. [ABSTRACT FROM AUTHOR]

Purpose: To find the diagnostic accuracy of Disc Damage Likelihood Scale (DDLS) and cup-to-disc ratio (CDR) for diagnosis of glaucoma taking central corneal thickness (CCT) adjusted intraocular pressure (IOP) and characteristic visual filed defects with corresponding OCT-ONH changes as standard. Study Design: Comparative, cross-sectional. Place and Duration of Study: Department of Ophthalmology, Mayo Hospital, Lahore, from August 2020 to February 2021. Methods: Three hundred and nine patients were enrolled after taking informed consent. Demographic data was obtained and patients underwent complete ocular exam including DDLS and CDR, Slit-lamp biomicroscopy, gonioscopy and IOP. CCT, visual fields and OCT ONH was done. The patient was said to have glaucoma if his CCT adjusted IOP was greater than 21 mmHg, visual field defects and OCT changes. It was compared with CDR and DDLS, which was taken as suggestive of glaucoma with scores greater than 5. Results: Mean age of patients was 54.82 ± 9.29 years, 108 (34.95%) were males. The sensitivity, specificity and diagnostic accuracy of DDLS for detection of glaucoma was 78.57%, 84.97% and 80.91% and the sensitivity, specificity and diagnostic accuracy of CDR for detection of glaucoma was 82.14%, 49.56% & 70.23% taking CCT adjusted IOP and characteristic visual field defects with corresponding OCT changes as standard. Conclusion: DDLS is useful, cost effective and has higher accuracy to detect glaucomatous damage as compared to CDR for diagnosis of glaucoma taking CCT adjusted IOP and characteristic visual field defects with corresponding OCT changes as standard. [ABSTRACT FROM AUTHOR]

Glaucoma, a chronic eye disease with irreversible blindness, is difficult to diagnose early. The cup-to-disc ratio is an important diagnostic index in glaucoma screening. Segmenting the optic disc and the optic cup is critical for glaucoma screening. Artificial glaucoma screening is time-consuming and laborious, so computer-aided function is important to save more human resources. In this paper, a biregional contour evolution model based on machine learning is proposed to segment the optic disc and the optic cup. To segment probability information in a more complete OD-OC, feature space is integrated into the edge indicator function by a machine learning method, and the intensity, edge, and region features of the OD-OC are obtained. In addition, the cup-to-disc ratio is calculated to diagnose glaucoma because it is currently practiced and can effectively assist doctors in clinical diagnosis. To evaluate the reliability and effectiveness of the proposed model, qualitative and quantitative results are obtained in the Dhristi-GS, DRIVE, and REFUGE datasets. [ABSTRACT FROM AUTHOR]

Abstract Background Digital optic disc photographs are integral to remote telehealth ophthalmology, yet no quality control standards exist for the brightness setting of the images. This study evaluated the relationship between brightness setting and cup/disc ratio (c/d) grading among glaucoma specialists. Methods Optic disc photographs obtained during routine examinations under anesthesia were collected to construct an image library. For each optic disc, photographs were obtained at 3 light intensity settings: dark, medium, and bright. From the image library, photograph triads (dark, medium and bright) of 50 eyes (50 patients) were used to construct the study set. Nine glaucoma specialists evaluated the c/d of the study set photographs in randomized order. The relationships between the brightness levels and the c/d grading as well as graders’ years in practice and variability were evaluated. Results The c/d were graded as significantly larger in bright photographs when compared to photographs taken at the medium light intensity (0.53 vs 0.48, P

Kelvin KW Cheng, Andrew J Tatham Princess Alexandra Eye Pavilion, Edinburgh, UKCorrespondence: Andrew J TathamPrincess Alexandra Eye Pavilion, Edinburgh, UKTel +44 131 536 3753Email andrewjtatham@gmail.comAbstract: The disc damage likelihood scale (DDLS) is a tool for classifying glaucomatous structural changes to the optic disc based on the radial width of the neuroretinal rim at its thinnest location, or if no rim is present, the extent of absence of the rim. Unlike cup disc ratio (CDR), the DDLS also considers disc size. Twenty years after its first description, the aim of this review was to critically appraise evidence for the DDLS and evaluate its role in current practice. A literature search by two independent authors identified 33 relevant articles for inclusion. Five studies evaluated reproducibility, 5 diagnostic performance, and 2 studies examined ability to detect progression. Eleven studies evaluated correlation between DDLS and other markers of glaucoma. Despite the widespread availability of imaging devices such as optical coherence tomography (OCT), clinical examination of the optic disc remains an essential component of glaucoma diagnosis and monitoring. The DDLS provides a reliable method for semi-quantitative clinical grading of the optic disc in glaucoma, with higher reproducibility than methods such as CDR.Keywords: glaucoma, cup-to-disc ratio, rim-to-disc ratio, disc damage likelihood scale

Glaucoma is a silent disease that shows symptoms when severe, leading to partial vision loss or irreversible blindness. Early screening permits treating patients in time. For glaucoma screening, retinal images are very important since they enable the observation of initial glaucoma lesions, which typically begins with the cupping formation in the optic disc (OD). In clinical settings, practical indicators such as Cup-to-Disc Ratio (CDR) are frequently used to evaluate the presence and stage of glaucoma. The ratio between the cup and the optic disc can be measured using the vertical or horizontal diameter, or the area of the two. Mass screening programs are limited by the high costs of specialised teams and equipment. Current deep learning (DL) methods can assist the glaucoma mass screening, lower the cost and allow it to be extended to larger populations. With DL methods in the OD and optic cup (OC) segmentation, is possible to evaluate the presence of glaucoma in the patient more quickly based on cupping formation in the OD, using CDR. In this work, is assessed the contribution of Multi-Class and Single-Class segmentation methods for glaucoma screening using the 3 types of CDR. U-Net architecture is trained using transfer learning models (Inception V3 and Inception ResNet V2) to segment the OD and OC and then evaluate glaucoma prediction based on different types of CDRs indicators. The models were trained and evaluated on main public known databases (REFUGE, RIM-ONE r3 and DRISHTI-GS). The segmentation of both OD and OC reach Dice over 0.8 and IoU above 0.7. The CDRs were computed to glaucoma assessment where was reach sensitivity above 0.8, specificity of 0.7, F1-Score around 0.7 and AUC above 0.85. Finally, conclusions of segmentation methods showing adequate performance to be used in practical glaucoma screening. [ABSTRACT FROM AUTHOR]

Background: Digital optic disc photographs are integral to remote telehealth ophthalmology, yet no quality control standards exist for the brightness setting of the images. This study evaluated the relationship between brightness setting and cup/disc ratio (c/d) grading among glaucoma specialists.Methods: Optic disc photographs obtained during routine examinations under anesthesia were collected to construct an image library. For each optic disc, photographs were obtained at 3 light intensity settings: dark, medium, and bright. From the image library, photograph triads (dark, medium and bright) of 50 eyes (50 patients) were used to construct the study set. Nine glaucoma specialists evaluated the c/d of the study set photographs in randomized order. The relationships between the brightness levels and the c/d grading as well as graders' years in practice and variability were evaluated.Results: The c/d were graded as significantly larger in bright photographs when compared to photographs taken at the medium light intensity (0.53 vs 0.48, P < 0.001) as well as those taken at the dark setting (0.47, P < 0.001). In addition, no relationship was found between ophthalmologists' years in practice and the variability of their c/d grading (P = 0.76).Conclusion: Image brightness affects c/d grading of nonstereoscopic disc photographs. The brighter intensity is associated with larger c/d grading. Photograph brightness may be an important factor to consider when evaluating digital disc photographs. [ABSTRACT FROM AUTHOR]

Background: Enlarged optic disc cupping and interocular cup-to-disc ratio (CDR) asymmetry are often important indicators of glaucoma. Clinically, we occasionally encounter children with large CDR and interocular CDR asymmetry during vision screening. This study aimed to report longitudinal change of ocular parameters in children with large cup-to-disc ratio (CDR) and interocular CDR asymmetry. Methods: This was a retrospective, observational case series of 160 eyes of 160 children with large CDR who visited a tertiary eye center from January 2010 to June 2016. Average CDR ≥ 0.6 were considered large CDR values, and CDR asymmetry was defined as an interocular difference ratio value greater than 0.2. All included patients showed interocular pressure (IOP) < 21 mmHg at least three ophthalmic examinations conducted at total intervals of at least 30 months. Results: The mean age of children included in the study was 7.14 ± 2.42 years, with a follow-up period of 54.46 ± 19.82 months. Changes in refractive error and axial length were significantly different between initial and final examination (p < 0.001). However, optic nerve head (ONH) analysis and retinal nerve fiber layer (RNFL) and macular ganglion cell-inner plexiform layer (mGCIPL) thicknesses were not significantly different between initial and final examination. In interocular comparisons of patients with CDR asymmetry, changes of refractive error, axial length, ONH analysis, and RNFL and mGCIPL thickness were not significantly different between the two eyes. Conclusions: There were no significant differences in the changes of ONH analysis, and RNFL and mGCIPL thicknesses in children with large CDR, or those with interocular CDR asymmetry over the study period. Our results provide helpful information for the establishment of guidelines for managing children with large CDR and interocular CDR asymmetry. [ABSTRACT FROM AUTHOR]

Glaucoma is one of the severe visual diseases that lead to damage the eyes irreversibly by affecting the optic nerve fibers and astrocytes. Consequently, the early detection of glaucoma plays a virtual role in the medical field. The literature presents various techniques for the early detection of glaucoma. Among the various techniques, retinal image-based detection plays a major role as it comes under noninvasive methods of detection. While detecting glaucoma disorder using retinal images, various medical features of the eyes, such as retinal nerve fiber layer, cup-to-disc ratio, apex point, optic disc, and optic nerve head, and image features, such as Haralick texture, higher-order spectra, and wavelet energy, are used. In this paper, a review and study were conducted for the different techniques of glaucoma detection using retinal fundus images. Accordingly, 45 research papers were reviewed and the analysis was provided based on the extracted features, classification accuracy, and the usage of different data sets, such as DIARETDB1 data set, MESSIDOR data set, IPN data set, ZEISS data set, local data set, and real data set. Finally, we present the various research issues and solutions that can be useful for the researchers to accomplish further research on glaucoma detection.

This paper proposes a deep image analysis–based model for glaucoma diagnosis that uses several features to detect the formation of glaucoma in retinal fundus. These features are combined with most extracted parameters like inferior, superior, nasal, and temporal region area, and cup-to-disc ratio that overall forms a deep image analysis. This proposed model is exercised to investigate the various aspects related to the prediction of glaucoma in retinal fundus images that help the ophthalmologist in making better decisions for the human eye. The proposed model is presented with the combination of four machine learning algorithms that provide the classification accuracy of 98.60% while other existing models like support vector machine (SVM), K-nearest neighbors (KNN), and Naïve Bayes provide individually with accuracies of 97.61%, 90.47%, and 95.23% respectively. These results clearly demonstrate that this proposed model offers the best methodology to an early diagnosis of glaucoma in retinal fundus. [ABSTRACT FROM AUTHOR]

Primary angle closure glaucoma (PACG) is one of the major causes of blindness worldwide. The underlying genetic aetiology is complex in nature and molecular mechanism remains elusive. Here, we identify genomic alterations using haplotype-based genome-wide association study in 148 PACG and 92 anatomically predisposed non-glaucomatous individuals. Logistic regression was performed on each common haplotype (within blocks of 3–8 SNPs) across the genotype and a total of 59 SNPs were found below genome wide suggestive threshold (p<1e−05). We found majority of these SNPs (n = 13) are located in CNTNAP5 genic region. The prioritized rs780010 of CNTNAP5 is also significantly associated with Cup to Disc ratio, which is a clinical parameter directly correlated with glaucomatous neurodegeneration. We further validated rs780010, present in all the significant haplotype blocks with p-value = 2.131e−06 (discovery phase), in a separate replication cohort (PACG, n = 50; control, n = 39) and observed significant association (p = 0.012, per G allele OR = 2.3079; 95% CI: 1.23–4.33). Bioinformatics analyses also suggested neuronal expression of CNTNAP5 with active chromatin structure. KEGG pathway analysis indicates towards pathways related to apoptosis and neurodegeneration. Overall, these results not only indicate a strong genetic association of CNTNAP5 locus with PACG but also suggest its potential involvement in glaucomatous neurodegeneration. [ABSTRACT FROM AUTHOR]

Glaucoma is one of the most complicated disorder in human eye that causes permanent vision loss gradually if not detect in early stage. It can damage the optic nerve without any symptoms and warnings. Different automated glaucoma detection systems were developed for analyzing glaucoma at early stage but lacked good accuracy of detection. This paper proposes a novel automated glaucoma detection system which effectively process with digital colour fundus images using hybrid classifiers. The proposed system concentrates on both Cup-to Disk Ratio (CDR) and different features to improve the accuracy of glaucoma. Morphological Hough Transform Algorithm (MHTA) is designed for optic disc segmentation. Intensity based elliptic curve method is used for separation of optic cup effectively. Further feature extraction and CDR value can be estimated. Finally, classification is performed with combination of Naive Bayes Classifier and K Nearest Neighbour (KNN). The proposed system is evaluated by using High Resolution Fundus (HRF) database which outperforms the earlier methods in literature in various performance metrics.

Importance Evidence‐based guidelines are essential for glaucoma screening to work effectively. Background: To derive a vertical cup‐to‐disc ratio (VCDR) cut‐off for glaucoma screening in a multi‐ethnic Asian population. Design The Singapore Epidemiology of Eye Diseases (SEED) study is a population‐based study conducted from 2004 to 2011 in a single tertiary care research institute. Participants: SEED comprised of 10 033 Chinese, Malay and Indian adults aged ≥40 (response rate 75.6%). After excluding participants with a history of glaucoma medication or surgery, 9673 participants were included for analysis. Methods: A systematic eye examination, which included applanation tonometry, visual field testing, gonioscopy and dilated fundus examination was conducted. Main Outcome Measure: Diagnosis of glaucoma. Results: The distribution of VCDR and VCDR asymmetry were relatively homogenous in this multi‐ethnic Asian population, with a 97.5th percentile value of 0.67 and 0.17, respectively. In the absence of more definite signs of glaucoma, VCDR ≥0.60 and VCDR asymmetry ≥0.20 provided the best balance between sensitivity (95.1%) and specificity (90.9%) in detecting glaucoma. For larger optic disc (≥2.0 mm), VCDR ≥0.65 with VCDR asymmetry ≥0.20 provided the best balance between sensitivity (84.8%) and specificity (93.2%). Conclusion and relevance: Overall, VCDR ≥0.60 with VCDR ≥0.20 asymmetry provides a good balance between sensitivity and specificity in detecting glaucoma. For larger optic disc, VCDR ≥0.65 should be considered instead to mitigate against false‐referrals due to larger physiological disc cupping. Our findings may act as a reference to populations with similar VCDR distribution. [ABSTRACT FROM AUTHOR]

Purpose: Recent guidelines recommend disc damage likelihood scale (DDLS) is recorded for all referrals of suspected glaucoma from community optometrists to hospital eye services (HES) in Scotland. This study aimed to determine whether lower DDLS grades were associated with higher rates of discharge at the first visit to HES. Methods: A retrospective analysis of 618 consecutive new referrals from community optometrists to a university hospital glaucoma service. 65 (10.5%) included DDLS graded by the community optometrist. A comprehensive eye examination and optical coherence tomography (OCT) was performed in the hospital glaucoma clinic and first visit discharge rate (FVDR) for different grades of DDLS compared. The relationship between DDLS and retinal nerve fibre layer (RNFL) thickness on OCT was also examined. Results: The FVDR for patients with DDLS recorded in the referral was 27.7% (18 of 65) compared to 25% (138 of 553) in those without DDLS (p = 0.631). The FVDR was 50% for those with a DDLS of 3 in the worse eye, decreasing to 32% and 21% for DDLS grades of 4 and 5 respectively. No patient with a DDLS ≥ 6 was discharged at the first visit and none with a DDLS < 4 (the cut off for consideration of referral in Scottish guidelines) were found to have glaucoma. There was a significant but weak inverse relationship between DDLS and RNFL thickness. The strongest relationship was with average RNFL thickness (r = −0.378, p < 0.01) followed by superotemporal (r = −0.359, p < 0.01) and inferotemporal (r = −0.353, p < 0.01) RNFL thickness. Conclusions: In patients referred to HES with DDLS information included, lower DDLS grading was associated with higher odds of being discharged at the first visit. DDLS grading by community optometrists had a poor correlation with RNFL thickness measured using OCT. [ABSTRACT FROM AUTHOR]

Exposure to selective serotonin reuptake inhibitors causes pupillary dilator muscle stimulation, active mydriasis, rapid rise in the level of the intraocular pressure (IOP), damage to the optic nerve at the back of the eye, and ultimately leads to acute angle closure glaucoma. The aim of this study was to assess the effects of sertraline on the levels of IOP and cup-to-disc ratio (CDR) in patients with anxiety disorders or mixed anxiety and depressive disorder or major depressive under daily treatment with sertraline and without underlying eye disease for three months. In this study,30 eligible patients in the sertraline group and 30 healthy volunteers in the control group include the study and were referred to an ophthalmologist. Ophthalmologic examinations were assessed at the baseline and on the first and third months of the study. The average daily dose of sertraline was 95±2.5 mg.During the study, the IOP changes in the sertraline and control groups were 0.26±0.43 and 0.00±0.00 mmHg (p

Glaucoma is a sight-threading disease which can lead to irreversible blindness. Currently, extracting the vertical cup-to-disc ratio (CDR) from 2D retinal fundus images is promising for automatic glaucoma diagnosis. In this paper, we present a novel sparse coding approach for glaucoma diagnosis called adaptive weighted locality-constrained sparse coding (AWLCSC). Different from the existing reconstruction-based glaucoma diagnosis approaches, the weighted matrix in AWLCSC is constructed by adaptively fusing multiple distance measurement information between the reference images and the testing image, making our approach more robust and effective to glaucoma diagnosis. In our approach, the disc image is firstly extracted and reconstructed according to the proposed AWLCSC technique. Then, with the usage of the obtained reconstruction coefficients and a series of reference disc images with known CDRs, the CDR of the testing disc image can be automated estimation for glaucoma diagnosis. The performance of the proposed AWLCSC is evaluated on two publicly available DRISHTI-GS1 and RIM-ONE r2 databases. The experimental results indicate that the proposed approach outperforms the state-of-the-art approaches. Graphical abstract The flowchart of the proposed approach for glaucoma diagnosis. [ABSTRACT FROM AUTHOR]

Automatic evaluation of the retinal fundus image is regarded as one of the most important future tools for early detection and treatment of progressive eye diseases like glaucoma. Glaucoma leads to progressive degeneration of vision which is characterized by shape deformation of the optic cup associated with focal notching, wherein the degeneration of the blood vessels results in the formation of a notch along the neuroretinal rim. In this study, we have developed a methodology for automated prediction of glaucoma based on feature analysis of the focal notching along the neuroretinal rim and cup to disc ratio values. This procedure has three phases: the first phase segments the optic disc and cup by suppressing the blood vessels with dynamic thresholding; the second phase computes the neuroretinal rim width to detect the presence and direction of notching by the conventional ISNT rule apart from calculating the cup-to-disc ratio from the color fundus image (CFI); the third phase uses linear support vector based machine learning algorithm by integrating extracted parameters as features for classification of CFIs into glaucomatous or normal. The algorithm outputs have been evaluated on a freely available database of 101 images, each marked with decision of five glaucoma expert ophthalmologists, thereby returning an accuracy rate of 87.128%. [ABSTRACT FROM AUTHOR]

Glaucoma is one of the most complicated disorder in human eye that causes permanent vision loss gradually if not detect in early stage. It can damage the optic nerve without any symptoms and warnings. Different automated glaucoma detection systems were developed for analyzing glaucoma at early stage but lacked good accuracy of detection. This paper proposes a novel automated glaucoma detection system which effectively process with digital colour fundus images using hybrid classifiers. The proposed system concentrates on both Cup-to Disk Ratio (CDR) and different features to improve the accuracy of glaucoma. Morphological Hough Transform Algorithm (MHTA) is designed for optic disc segmentation. Intensity based elliptic curve method is used for separation of optic cup effectively. Further feature extraction and CDR value can be estimated. Finally, classification is performed with combination of Naive Bayes Classifier and K Nearest Neighbour (KNN). The proposed system is evaluated by using High Resolution Fundus (HRF) database which outperforms the earlier methods in literature in various performance metrics. [ABSTRACT FROM AUTHOR]

• Glaucoma is one of the leading causes of blindness worldwide. The optic nerve is the most affected site where glaucomatous changes are seen. Therefore, early detection and treatment of glaucoma can be sight-saving. Advancing optical coherence tomography technology helps detect changes in glaucomatous eyes. To determine the diagnostic value of optic nerve head (ONH) topographic parameters measured by swept-source optical coherence tomography (SS-OCT) in differentiating between early glaucoma cases, glaucoma suspects (GSs), and healthy eyes. The files of GSs, those with an early primary open angle glaucoma (POAG) diagnosis, and healthy eyes were retrospectively screened. Demographic characteristics, retinal nerve fibre measurements, visual field examinations, and ONH topographic parameters, including rim area, disc area, vertical and horizontal cup-to-disc ratios (CDRs), and cup volume, were compared between the groups. A receiver operating characteristic (ROC) curve analysis was performed on the ONH parameters. A total of 170 eyes from 85 GSs, 114 eyes from 57 patients with a diagnosis of early POAG, and 70 healthy eyes from 48 subjects were included in the study. The median age was 52.1 ± 0.9 years for the POAG group, 60.2 ± 1.1 years for the GS group, and 60.5 ± 1.6 for the controls. In the comparison of the ONH parameters between the groups, only rim area statistically significantly differed between the POAG and GS groups. However, all ONH parameters statistically significantly differed between the GS and control groups (p< 0.05). The mean rim areas of the GS, POAG, and control groups were 1.278 ± 0.055 mm2, 1.073 ± 0.065 mm2, and 1.446 ± 0.055 mm2, respectively, being statistically significantly higher in the controls and lower in the POAG group (p < 0.001). The highest area under the curve (AUC) value belonged to vertical CDR for the discrimination of the eyes with POAG from healthy eyes [0.806 (0.728–0.869, p < 0.001] and rim area for the discrimination of POAG cases and GSs [0.728 (0.650–0.797, p < 0.001]. There are significant differences in all ONH parameters between the eyes of GSs and healthy eyes. For the discrimination of early POAG and GS cases, topographic disc parameters may have value. In this study, rim area significantly differed between the GS and POAG groups, and it had the highest AUC value amongst the evaluated ONH parameters in the discrimination of early POAG cases S GSs. [ABSTRACT FROM AUTHOR]

Glaucoma is a chronic progressive eye condition leading to permanent visual loss. An automatic screening system is necessary to detect primary open-angle glaucoma because it is an insidious disease appearing without symptoms or early warning signs. This work introduces an automatic screening technique to diagnose glaucoma using a support vector machine (SVM). Two case studies are investigated: binary-stage and multi-stage classification of glaucoma. First, there is a comparison of the performance of the hard threshold-based approach to the supervised learning approach using an SVM. Image segmentation techniques are performed to detect important features: the actual sizes of the optic cup and optic disc in vertical and horizontal directions. SVMs with a linear kernel function are used to generate the classifier model, and the results show that using threshold-based classification is inadequate to screen glaucoma. In a second case study, an SVM is applied to develop the classification algorithm focused more on the detection of the glaucoma suspect stage, which is an intermediate stage between the healthy and glaucoma stages. A polynomial kernel function is used to implement the classification model. The unbalanced decision tree (UDT) and one-versus-the-rest (OVR) techniques are combined in the models in order to overcome the limitations of an SVM. Finally, the combination of an SVM with both UDT and OVR techniques yields a reliable result with respect to belonging classes at 99.4%. [ABSTRACT FROM AUTHOR]