Literature DB >> 33467457

Ocular Phantom-Based Feasibility Study of an Early Diagnosis Device for Glaucoma.

Marie-Valérie Moreno1, Cloé Houriet2, Pierre-Alain Grounauer2.   

Abstract

Glaucoma causes total or partial loss of vision in 10% of people over the age of 70, increasing their fragility and isolation. It is characterised by the destruction of the optic nerve fibres, which may result from excessively high intraocular pressure as well as other phenomena. Diagnosis is currently reached through a combination of several checks, mainly of the eyes' fundus, tonometry and gonioscopy. Prior to validation for human subjects, the objective of this study is to validate whether ocular phantom-based models could be used to diagnose glaucoma using an onboard system, which could, even at home, prevent the early-stage development of the pathology. Eight phantoms modelling healthy eyes and eight phantoms modelling eyes with glaucoma due to excessive intraocular pressure were measured using an onboard system, including lens and electrophysiology electronics. We measured the actual average Zr (real part of impedance) impedance of 160.9 ± 24.3 ohms (glaucoma ocular phantom models) versus 211.9 ± 36.9 ohms (healthy ocular phantom models), and an average total water volume (Vt) of 3.02 ± 0.35 mL (glaucoma ocular phantom models) versus 2.45 ± 0.28 mL (healthy ocular Phantoms). On average, we obtained 51 ohms (-24.1%) less and 0.57 mL (22.9%) of total water volume more, respectively. Normality tests (Shapiro-Wilk) for Vt and Zr indicate p < 0.001 and p < 0.01, respectively. Since these variables do not respect normal laws, unmatched Mann-Whitney tests were performed indicating a significant difference between Vt and Zr in the healthy ocular phantom models and those modelling glaucoma. To conclude, this preliminary study indicates the possibility of discriminating between healthy eyes with those with glaucoma. However, further large-scale studies involving healthy eyes and those suffering from glaucoma are necessary to generate viable models.

Entities:  

Keywords:  eye impedance; glaucoma; ocular phantom

Year:  2021        PMID: 33467457     DOI: 10.3390/s21020579

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  An Efficient Deep Learning Approach to Automatic Glaucoma Detection Using Optic Disc and Optic Cup Localization.

Authors:  Marriam Nawaz; Tahira Nazir; Ali Javed; Usman Tariq; Hwan-Seung Yong; Muhammad Attique Khan; Jaehyuk Cha
Journal:  Sensors (Basel)       Date:  2022-01-07       Impact factor: 3.576

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.