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Clinically, there are many systems of visual field imaging systems. The agreement between glaucoma function and appearance is still uncertain. This study was conducted to compare visual field staging classifications (as function staging) with Disc Damage Likelihood Scale (DDLS as appearance staging) in Primary Open Angle Glaucoma (POAG). A cross-section study was performed using 55 patients (90 eyes) examined and treated by the Vietnam National Institute of Ophthalmology from 9/2016 - 9/2017. The MD (Mean Deviation), PSD (Pattern Standard Deviation), and VFI (Visual Field Index) indexes were recorded and were used to classify glaucoma staging according to categories of eGSS (enhanced Glaucoma Severity Staging), mGSS (modified Glaucoma Severity Staging), HPA (Hodapp- Parrish-Aderson), AGIS (Advanced Glaucoma Intervention Study), and DDLS. Using SPSS 16.0 software, statistical significance was tested with proper tests of Chi-square test, Fisher exact test, Kappa (to assess the agreement-disagreement), and Spearman Rank (to assess the level of correlation). Mean VFI were -11.49 dB (MD), 5.85 dB (PSD), and 74.2 % (VFI). Compared to DDLS, all systems had slight agreement (K < 0.2). The disagreement percentage was highest in eGSS (70 %), followed by mGSS (50 %) and HPA (48.9 %). In terms of definitive diagnosis, HPA and mGSS showed a substantial agreement (K > 0.6) with AGIS, which was higher than that between eGSS and AGIS (0.773 and 0.75 vs 0.399), with p < 0.001. In terms of staging detection, the agreement between HPA, mGSS, and AGIS was substantial (K > 0.6), while that between eGSS and AGIS was fair (K < 0.4). In conclusion, mGSS and HPA tended to show stronger agreement with standard classifications than eGSS. mGSS should be used in clinical practice and research. [ABSTRACT FROM AUTHOR]

Glaucoma is a retinal disease caused due to increased intraocular pressure in the eyes. It is the second most dominant cause of irreversible blindness after cataract, and if this remains undiagnosed, it may become the first common cause. Ophthalmologists use different comprehensive retinal examinations such as ophthalmoscopy, tonometry, perimetry, gonioscopy and pachymetry to diagnose glaucoma. But all these approaches are manual and time-consuming. Thus, a computer-aided diagnosis system may aid as an assistive measure for the initial screening of glaucoma for diagnosis purposes, thereby reducing the computational complexity. This paper presents a deep learning-based disc cup segmentation glaucoma network (DC-Gnet) for the extraction of structural features namely cup-to-disc ratio, disc damage likelihood scale and inferior superior nasal temporal regions for diagnosis of glaucoma. The proposed approach of segmentation has been tested on RIM-One and Drishti-GS dataset. Further, based on experimental analysis, the DC-Gnet is found to outperform U-net, Gnet and Deep-lab architectures. [ABSTRACT FROM AUTHOR]

Purpose: To assess the correlation between the disc damage likelihood scale (DDLS) objectively measured by a non-mydriatic fundus camera, Heidelberg Retina Tomograph 3, and optic coherence tomography in preperimetric glaucoma. Methods: One-hundred-twenty-five patients with preperimetric primary open-angle glaucoma (POAG) and pseudoexfoliation glaucoma (n=30) were included (mean age 58.9±15.9 years). All three devices graded the optic disc topography: Diagnosis 1 was defined as "outside normal limits", while Diagnosis 2 as "borderline or outside normal limits". Results: For Diagnosis 1, a significant correlation was shown between DDLS and Moorfields regression analysis (P=0.022), and for Diagnosis 2 with glaucoma probability score analysis (P=0.024), in POAG. In pseudoexfoliation glaucoma, DDLS did not correlate significantly with Heidelberg Retina Tomograph 3 and optic coherence tomography. Regarding the area under the curve the highest predictive power was demonstrated by the objective DDLS (0.513--0.824) compared to Burk (0.239--0.343) and Mikelberg (0.093--0.270) coefficients. Conclusions: The DDLS showed a significant correlation to the Moorfields regression analysis in preperimetric POAG. The objective DDLS showed the highest predictive power and thus is an additive tool in diagnosing preperimetric glaucoma. [ABSTRACT FROM AUTHOR]

Abstract: The goal of the treatment of patients with glaucoma is to prevent disability or, if disability already exists, to repair the disability or at the least to prevent further disability from developing. To achieve these goals requires knowing what will happen if there is no treatment and what will happen if there is treatment. That is, one must know the possible benefits from the therapy in comparison to the damage caused by the therapy. As we will demonstrate, the classic risk factors do not provide accurate estimates of the development of disability and do not answer these two questions. The most helpful clues are provided by what the patient says, by whether the disc is damaged and by whether the disc is deteriorating. The severity of disease is best estimated by the nature of the optic disc and how it changes. This report is primarily focused on increasing the skill of the physician in being able to estimate the nature of the optic disc and how that changes. This does not, however, lessen the tremendous importance of careful history-taking and of gonioscopy. In this report, however, we focus on the evaluation of the disc. Currently disc evaluation is often not adequate because of poor examination techniques, reliance on cup/disc ratios, and reliance on the results of image analyzers. We will present here the Disc Damage Likelihood Scale, which is a user-friendly method which correlates accurately with visual field changes. [Copyright &y& Elsevier]