Research Center, RunSys, 53 Avenue Carnot, 69250 Neuville-sur-Saône, France.
Research Center, Fabrinal, Rue de la Tuilerie 42, 2300 La Chaux-de-Fonds, Switzerland.
Sensors (Basel). 2021 Jan 15;21(2):579. doi: 10.3390/s21020579.
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 < 0.001 and < 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.
青光眼会导致 10%的 70 岁以上人群完全或部分失明，增加他们的脆弱性和孤立感。它的特征是视神经纤维的破坏，这可能是由于眼内压过高以及其他现象引起的。目前的诊断是通过几种检查的结合来实现的，主要是眼底、眼压和房角镜检查。在进行人体验证之前，本研究的目的是验证基于眼部模型的模型是否可以用于通过车载系统诊断青光眼，即使在家中，也可以预防该病理学的早期发展。使用车载系统测量了 8 个模拟健康眼睛的模型和 8 个因眼内压过高而导致青光眼的模型，其中包括镜片和电生理电子设备。我们测量了实际平均 Zr（阻抗的实部）阻抗为 160.9 ± 24.3 欧姆（青光眼眼部模型）与 211.9 ± 36.9 欧姆（健康眼部模型），平均总水体积（Vt）为 3.02 ± 0.35 mL（青光眼眼部模型）与 2.45 ± 0.28 mL（健康眼部模型）。平均而言，我们分别获得了 51 欧姆（-24.1%）和 0.57 毫升（22.9%）的总水体积。Vt 和 Zr 的正态性检验（Shapiro-Wilk）分别为 < 0.001 和 < 0.01。由于这些变量不遵守正态规律，因此进行了不匹配的曼-惠特尼检验，表明健康眼部模型和青光眼模型之间的 Vt 和 Zr 存在显著差异。总之，这项初步研究表明了区分健康眼睛和青光眼的可能性。然而，需要进一步进行涉及健康眼睛和青光眼患者的大规模研究，以生成可行的模型。
