Dataset Information

Automated macular segmentation can distinguish glaucomatous from compressive optic neuropathy.

ABSTRACT:

Purpose

To compare macular damage in glaucomatous optic neuropathy (GON) and compressive optic neuropathy (CON) and assess its diagnostic accuracy in distinguishing between diseases.

Methods

Observational, cross-sectional, single-center study. Patients with GON, CON, and healthy controls were included according to the eligibility criteria. An automated spectral-domain optical coherence tomography (SD-OCT) algorithm was used to segment the circumpapilary retinal nerve fiber layer (cpRNFL) and macula. The layer thickness was measured in each sector according to the Early Treatment Diabetic Retinopathy Study and the 6-sector Garway-Heath-based grids. Data was compared across all study groups, and the significance level was set at 0.05.

Results

Seventy-five eyes of 75 participants, 25 with GON, 25 with CON, and 25 healthy controls (CG), were included. Macular thickness was diminished in the ganglion cell complex of GON and CON patients compared to CG (p<0.05). The best Garway-Heath-based grid parameters for distinguishing GON and CON were the nasal-inferior (NI) and nasal-superior sectors and the NI/temporal inferior (TI) damage ratios in the macular ganglion cell (mGCL) and inner plexiform (IPL) layers. Moreover, the combination of the NI sector and NI/TI damage ratios in both layers had higher discriminative power (AUC 0.909; 95% CI 0.830-0.988; p<0.001) than combining parameters in each layer separately.

Conclusion

Our findings suggest that the evaluation of macular segmented layers damage by SD-OCT may be a helpful add-on tool in the differential diagnosis between GON and CON.

SUBMITTER: Soares RM

PROVIDER: S-EPMC10198839 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Publications

Automated macular segmentation can distinguish glaucomatous from compressive optic neuropathy.

Soares Ricardo Machado RM Braga Joana Figueiredo JF da Silva Fernandes Joana J Ferreira Catarina Cunha CC Ribeiro Lígia L Alves Hélio H Meira Dália D

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie 20230110 6

<h4>Purpose</h4>To compare macular damage in glaucomatous optic neuropathy (GON) and compressive optic neuropathy (CON) and assess its diagnostic accuracy in distinguishing between diseases.<h4>Methods</h4>Observational, cross-sectional, single-center study. Patients with GON, CON, and healthy controls were included according to the eligibility criteria. An automated spectral-domain optical coherence tomography (SD-OCT) algorithm was used to segment the circumpapilary retinal nerve fiber layer ( ...[more]

PMID: 36625929

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Project description:PurposeTo quantify the morphological features of the optic nerve head using radial polynomials, to use these morphometric models as the basis for classification of glaucomatous optic neuropathy via an automated decision tree induction algorithm, and to compare these classification results with established procedures.MethodsA cohort of patients with high-risk ocular hypertension or early glaucoma (n=179) and a second cohort of normal subjects (n=96) were evaluated for glaucomatous optic neuropathy using stereographic disc photography and confocal scanning laser tomography. Morphological features of the optic nerve head region were modeled from the tomography data using pseudo-Zernike radial polynomials and features derived from these models were used as the basis for classification by a decision tree induction algorithm. Decision tree classification performance was compared with expert classification of stereographic disc photographs and analysis of neural retinal rim thickness by Moorfields Regression Analysis (MRA).ResultsRoot mean squared error of the morphometric models decreased asymptotically with additional polynomial coefficients, from 62±0.5 (32 coefficients) to 32±5.7 μm (256 coefficients). Optimal morphometric classification was derived from a subset of 64 total features and had low sensitivity (69%), high specificity (88%), very good accuracy (80%), and area under the receiver operating characteristic curve (AUROC) was 88% (95% confidence interval, 78%-98%). In comparison, MRA classification of the same records had a comparatively poorer sensitivity (55%), but had higher specificity (95%), with similar overall accuracy (78%) and AUROC curve, 83% (95% CI, 70%-96%).ConclusionsPseudo-Zernike radial polynomials provide a mathematically compact and faithful morphological representation of the structural features of the optic nerve head. This morphometric method of glaucomatous optic neuropathy classification has greater sensitivity, and similar overall classification performance (AUROC) when compared with classification by neural retinal rim thickness by MRA in patients with high-risk ocular hypertension and early glaucoma.

Project description:PurposeTo determine whether an association exists between sleep apnea and open-angle glaucoma, normal-tension glaucoma, nonarteritic ischemic optic neuropathy (NAION), papilledema, or idiopathic intracranial hypertension (IIH) and whether treatment with continuous positive airway pressure affects the development of these conditions.DesignRetrospective, longitudinal cohort study.MethodsBilling records for beneficiaries 40 years of age and older enrolled in a large United States managed care network from 2001 through 2007 were reviewed. Incidence of open-angle glaucoma, normal-tension glaucoma, NAION, papilledema, and IIH were determined for the beneficiaries and were stratified by sleep apnea status. Cox regression analyses determined the hazard of each of these conditions developing among individuals with and without sleep apnea, with adjustment for sociodemographic, ocular, and medical conditions.ResultsAmong the 2 259 061 individuals in the study, 156 336 (6.9%) had 1 or more sleep apnea diagnoses. The hazard of open-angle glaucoma was no different among persons with sleep apnea either treated (adjusted hazard ratio [HR], 0.99; 95% confidence interval [CI], 0.82 to 1.18) or untreated with continuous positive airway pressure (HR, 1.01; 95% CI, 0.98 to 1.05) and individuals without sleep apnea. Similar findings were observed when assessing the hazard of normal-tension glaucoma developing (P > .05 for both comparisons). A significantly increased hazard of NAION developing (HR, 1.16; 95% CI, 1.01 to 1.33) and IIH (HR, 2.03; 95% CI, 1.65 to 2.49) was observed among individuals with sleep apnea who were not receiving continuous positive airway pressure therapy as compared with individuals without sleep apnea, although similar increased risks could not be demonstrated among continuous positive airway pressure-treated sleep apnea patients for these conditions (P > .05 for both comparisons).ConclusionsPatients with untreated sleep apnea are at increased risk for IIH and NAION. Clinicians should consider appropriate screening for these conditions in sleep apnea patients.

Dataset Information

Automated macular segmentation can distinguish glaucomatous from compressive optic neuropathy.

Purpose

Methods

Results

Conclusion

Publications

Automated macular segmentation can distinguish glaucomatous from compressive optic neuropathy.

Similar Datasets

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