Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.
Research Department, Heel of Scene Ltd., Tokyo, Japan; Basir Eye Health Research Center, Tehran, Iran.
J Mech Behav Biomed Mater. 2021 Jan;113:104155. doi: 10.1016/j.jmbbm.2020.104155. Epub 2020 Oct 26.
Understanding of the corneal biomechanical properties is of high interest due to its potential application in the early diagnosis of keratoconus (KC). KC by itself is a non-inflammatory eye disorder causes corneal structural and/or compositional anomalies. The biomechanically weakened cornea is no longer able to preserve the normal shape of the cornea against the intraocular pressure (IOP) and gradually starts to bulge outward, invoking a conical shape and subsequent distorted vision. The most popular way to measure the in vivo corneal biomechanical properties is the CorVis-ST, which enables to analyze the dynamic response of the cornea under a temporary air puff pressure. However, the complications, such as the lack of knowledge on the accurate air-puff pressure distribution on the cornea's surface as a function of the distance from the apex of the cornea as well as the time, hinder us to have a reliable estimation of the cornea's mechanical parameters. This study aims to establish patient-specific geometries of the healthy and KC corneas and calculate the pressure distribution on the cornea's surface as a function of both the distance from the apex of the cornea and time, and thereafter, the viscoelastic mechanical properties of both the healthy and KC corneas using a coupled finite element (FE)-optimization algorithm. To do that, the dynamic deformation response of six healthy and six KC corneas were measured via CorVis-ST. The videos of the in vivo deformation of the corneas under the applied air puff pressure were segmented using our segmentation algorithm to determine the anterior and posterior curvatures of the corneas during the dynamic movement of the cornea. The FE model of the corneas were established using the segmented data and subjected to a negative (pre-stress), positive IOP, and air puff pressure while the floating boundary conditions were applied to the two ends of the corneas' FE models. The simulation results were imported into a loop of FE-optimization algorithm and analyzed until the deformation amplitude at the apex of the cornea reaches to its minimum difference compared to the clinical data by CorVis-ST. The results revealed that the pressure distributions found in the literature as a function of the distance from the apex of the cornea and time unable to provide satisfactory results. Therefore, the pressure distributions both as a function of the distance and time were optimized using our coupled FE-optimization algorithm and employed to estimate the viscoelastic properties of the healthy and KC corneas. The mean percentage error (MPE) of 8.45% and 10.79% were found for the healthy and KC corneas compared to the clinical data of CorVis-ST, respectively. The results also revealed a significantly higher short-time shear modulus for the KC (62.33 MPa) compared to the healthy (37.45 MPa) corneas while the long-time shear modulus of both the healthy and KC corneas were almost the same (4.01 vs. 3.91 MPa). The proposed algorithm is a noninvasive technique capable of accurately estimating the viscoelastic mechanical properties of the cornea, which can contribute to understand the mechanism of KC development and improve diagnosis and intervention in KC.
了解角膜生物力学特性具有重要意义,因为它有可能应用于圆锥角膜(KC)的早期诊断。KC 本身是一种非炎症性眼病,导致角膜结构和/或成分异常。生物力学减弱的角膜不再能够抵抗眼内压(IOP)而保持角膜的正常形状,并逐渐开始向外突出,形成圆锥形,从而导致视力扭曲。测量活体角膜生物力学特性的最流行方法是 CorVis-ST,它能够分析角膜在短暂空气脉冲压力下的动态响应。然而,由于缺乏关于空气脉冲压力在角膜表面上的准确分布的知识,以及关于距离角膜顶点的时间的知识,这些并发症阻碍了我们对角膜机械参数的可靠估计。本研究旨在建立健康和 KC 角膜的患者特定几何形状,并计算角膜表面上的压力分布,该压力分布既取决于距离角膜顶点的距离,又取决于时间,然后使用耦合有限元(FE)优化算法计算健康和 KC 角膜的粘弹性机械特性。为此,通过 CorVis-ST 测量了六只健康角膜和六只 KC 角膜的动态变形响应。使用我们的分割算法对角膜在应用空气脉冲压力下的活体变形视频进行分割,以确定角膜在动态运动过程中的前曲率和后曲率。使用分割数据建立角膜的 FE 模型,并在角膜 FE 模型的两端施加负(预压)、正 IOP 和空气脉冲压力,同时施加浮动边界条件。将模拟结果导入 FE-优化算法的循环中,并进行分析,直到角膜顶点的变形幅度达到与 CorVis-ST 的临床数据相比最小差异。结果表明,文献中作为距离角膜顶点的函数和时间的压力分布无法提供令人满意的结果。因此,使用我们的耦合 FE-优化算法优化了作为距离和时间函数的压力分布,并用于估计健康和 KC 角膜的粘弹性特性。与 CorVis-ST 的临床数据相比,健康角膜和 KC 角膜的平均百分比误差(MPE)分别为 8.45%和 10.79%。结果还表明,KC(62.33 MPa)的短期剪切模量明显高于健康(37.45 MPa)角膜,而健康和 KC 角膜的长期剪切模量几乎相同(4.01 与 3.91 MPa)。所提出的算法是一种非侵入性技术,能够准确估计角膜的粘弹性力学特性,有助于了解 KC 发展的机制,并改善 KC 的诊断和干预。