Glaucoma Mimickers: A major review of causes, diagnostic evaluation, and recommendations

Senthil, Sirisha; Nakka, Mamata; Sachdeva, Virender; Goyal, Shaveta; Sahoo, Naresh Kumar; Choudhari, Nikhil S.

doi:10.1080/08820538.2021.1897855

Cited by 13 publications

(16 citation statements)

References 70 publications

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“…In line with this, the significance of the examination of OD parameters in the differential diagnosis of glaucoma is presented in [4]. A most recent review [5] in this context brings out the risks of undiagnosis and overdiagnosis of glaucoma due to overlapping symptoms between glaucomatous and nonglaucomatous optic neuropathy in the OD region. Further, a recent case study also shows that constrictive ODs manifest in pediatric patients with central retinal vein occlusion (CRVO) [6], one of the important causes of glaucoma.…”

Section: Introductionmentioning

confidence: 91%

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A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection

Ganesh

Kannayeram

Karthick

et al. 2021

Computational and Mathematical Methods in Medicine

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Glaucoma is a chronic ocular disease characterized by damage to the optic nerve resulting in progressive and irreversible visual loss. Early detection and timely clinical interventions are critical in improving glaucoma-related outcomes. As a typical and complicated ocular disease, glaucoma detection presents a unique challenge due to its insidious onset and high intra- and interpatient variabilities. Recent studies have demonstrated that robust glaucoma detection systems can be realized with deep learning approaches. The optic disc (OD) is the most commonly studied retinal structure for screening and diagnosing glaucoma. This paper proposes a novel context aware deep learning framework called GD-YNet, for OD segmentation and glaucoma detection. It leverages the potential of aggregated transformations and the simplicity of the YNet architecture in context aware OD segmentation and binary classification for glaucoma detection. Trained with the RIGA and RIMOne-V2 datasets, this model achieves glaucoma detection accuracies of 99.72%, 98.02%, 99.50%, and 99.41% with the ACRIMA, Drishti-gs, REFUGE, and RIMOne-V1 datasets. Further, the proposed model can be extended to a multiclass segmentation and classification model for glaucoma staging and severity assessment.

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Section: Introductionmentioning

confidence: 91%

“…In this formulation, N is the training set size, and y i is the label of the segmentation mask for the sample i . The segmentation loss can be formulated as in (5).…”

Section: Proposed Systemmentioning

confidence: 99%

A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection

Ganesh

Kannayeram

Karthick

et al. 2021

Computational and Mathematical Methods in Medicine

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“… 93 Compared to normal eyes, myopic eyes typically have an optic disc that is: larger, more shallow, oval-shaped, obliquely oriented, and presence of neuroretinal rim thinning and peripapillary atrophy. 94 , 95 …”

Section: Congenital Causesmentioning

confidence: 99%

Neuro-Ophthalmological Optic Nerve Cupping: An Overview

Waisberg¹,

Micieli²

2021

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Optic nerve cupping or enlargement of the cup-to-disc ratio is widely recognized as a feature of glaucoma, however it may also occur in non-glaucomatous optic neuropathies. The most well-recognized non-glaucomatous optic neuropathies that cause cupping include compressive optic neuropathies, arteritic anterior ischemic optic neuropathies, hereditary optic neuropathies, and optic neuritis. Cupping is thought to consist of two main components: prelaminar and laminar thinning. The former is a shallow form of cupping and related to loss of retinal ganglion cells, whereas the latter involves damage to the lamina cribrosa and peripapillary scleral connective tissue. Differentiating glaucomatous and non-glaucomatous optic nerve cupping remains challenging even for experienced observers. Classically, the optic nerve in non-glaucomatous causes has pallor of the neuroretinal rim, but the optic nerve should not be examined in isolation. The patient’s medical history, history of presenting illness, visual function (visual acuity, color vision and visual field testing) and ocular examination also need to be considered. Ancillary testing such as optical coherence tomography of the retinal nerve fiber layer and ganglion cell layer-inner plexiform layer may also be helpful in localizing the disease. In this review, we review the non-glaucomatous causes of cupping and provide an approach to evaluating a patient that presents with an enlarged cup-to-disc ratio.

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“…However, unlike in manifest glaucoma with typical VF defect, assessing glaucoma risk in early suspected cases is clinically challenging. The optic disc has various morphologies among individuals, and the patterns of glaucomatous damage have many variations, making it difficult to make definitive decisions to start treatment 8 , 9 .…”

Section: Introductionmentioning

confidence: 99%

Screening fundus photography predicts and reveals risk factors for glaucoma conversion in eyes with large optic disc cupping

Kim

Yun

Choi

2023

Sci Rep

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This study aimed to investigate the risk factors for glaucoma conversion and progression in eyes with large optic disc cupping without retinal nerve fiber layer defect (RNFLD). Five hundred forty-two eyes of 271 subjects who had a vertical cup-to-disc ratio (CDR) ≥ 0.6 without RNFLD were enrolled. Characteristics for optic disc configuration (including CDR, vertical cupping, ISNT rule, disc ovality, peripapillary atrophy [PPA]-to-disc area [DA] ratio, and lamina cribrosa pore visibility) and blood vessels (including central retinal vessel trunk [CRVT] nasalization, bayoneting of vessels, baring of circumlinear vessels, history of disc hemorrhage [DH] and vessel narrowing/sclerotic change) were evaluated. From a median follow-up of 11.3 years, 26.6% of eyes (n = 144) developed RNFLD within a median of 5.1 years. Baseline factors, including vertical CDR ≥ 0.7 (hazard ratio [HR] = 2.12), vertical cupping (HR = 1.93), ISNT rule violation (HR = 2.84), disc ovality ≥ 1.2 (HR = 1.61), PPA-to-DA ratio ≥ 0.4 (HR = 1.77), CRVT nasalization ≥ 60% (HR = 1.77), vessel narrowing/sclerotic change (HR = 2.13), DH history (HR = 5.60), and baseline intraocular pressure ≥ 14 mmHg (HR = 1.70) were significantly associated with glaucoma conversion (all Ps < 0.05). An HR-matched scoring system based on initial fundus photography predicted glaucoma conversion with specificity of 90.4%. Careful examination of the optic nerve head and vascular structures can help to predict the risk of glaucoma conversion in eyes with large optic disc cupping.

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Glaucoma Mimickers: A major review of causes, diagnostic evaluation, and recommendations

Cited by 13 publications

References 70 publications

A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection

A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection

Neuro-Ophthalmological Optic Nerve Cupping: An Overview

Screening fundus photography predicts and reveals risk factors for glaucoma conversion in eyes with large optic disc cupping

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