Posterior pole asymmetry analysis and retinal nerve fibre layer thickness measurements in primary angle-closure suspect patients

Abstract

PurposeTo measure peripapillary retinal nerve fiber layer (RNFL) thickness and posterior pole retinal thickness in primary angle-closure suspects (PACS) by Spectral domain optical coherence tomography (SD-OCT) and to be compared with normal subjects.MethodsThirty five primary angle-closure suspect patients and thirty normal subjects were enrolled in this study. Peripapillary RNFL and posterior pole retinal thickness by posterior pole asymmetry analysis (PPAA) in SD-OCT were measured.ResultsNo significant difference was found in both groups on age, sex distribution, refractive error, intraocular pressure (IOP) and axial length. The PACS group exhibited significantly thinner macular retinal thickness and larger asymmetry on posterior pole region compared with the control group. Yet no significant difference of peripapillary RNFL parameters was found between PACS group and normal control group. A negative correlation was observed between the total retinal thickness on posterior pole region and age when all the PACS participants were analyzed.ConclusionsPosterior pole retinal thickness measurements obtained by Heidelberg Spectralis SD-OCT using PPAA showed significant thinner change in PACS group than healthy controls. Only age seemed to be an indicator in the occurrence of glaucomatous damage in PACS patients.

Measures of disease activity in glaucoma

“…Lee et al produced similar results, suggesting that the PPAA was able to serve as a potential tool to estimate disease activity (Lee et al 2016a). Moreover, PPAA can accurately distinguish between normal people and PACG patients even without any specific symptoms such as vision loss or increased intraocular pressure (IOP), suggesting that PPAA could be an indicator of PACG (Zha et al 2019). The OCT parameters are all able to estimate the structural damage and monitor disease progression with good accuracy and reproducibility(Table 3).…”

“…AI is an artificial entity capable of performing certain human tasks such as decision making and recognition of the features of certain subjects (Zheng et al 2019). AI has flourished in recent times.…”

“…However, analysis of the results of these investigations poses a challenge and is dependent on the experience of doctors with differing opinions leading to disagreements in management (Wang et al 2019). AI has been shown to have a significant potential in assisting complex data and image analysis which allow AI to differentiate glaucomatous functional and/or structural changes form normal eyes (Zheng et al 2019).…”

Posterior Pole Asymmetry Analysis in the Children with Anisometropia

“…Optical coherence tomography (OCT) has been widely used for diagnosis and follow-up of optic nerve and retinal disorders in children. It allows objective measurements of the optic nerve head (ONH), retinal nerve fiber layer (RNFL), and macular thickness in a non-invasive manner ( 1 - 8 ). Certain tests may be difficult to perform in children and objective tests are required.…”

Impacto do ajuste da medida da rima neurorretiniana dada pelo tomógrafo de coerência óptica no diagnóstico de glaucoma

“…Isso se deve ao fato de, habitualmente, a doença afetar de forma assimétrica as células ganglionares e os axônios na retina superior em relação à inferior, e também de haver preferência de acometimento de um olho antes do outro. 59 Com a melhoria das imagens e softwares, se tornou possível visualizar, segmentar e analisar individualmente as camadas retinianas, ou seja, as camadas internas da retina (camada de fibras nervosas, de células ganglionares e plexiforme interna), de maior interesse para o diagnóstico e monitoramento de glaucoma. 45 Xu demonstrou, através de diversos índices, tais como o coeficiente de variação, que medidas da retina interna com TCO apresentavam excelente reprodutibilidade.…”