# Finite Element Analysis of the Epiretinal Membrane Contraction
## 1 Introduction  
The development of an Epiretinal Membrane (ERM) is a relatively common disorder of the vitreomacular interface that can cause visual impairment [1]. The ERM is a pathologic fibrocellular membrane that lies immediately superjacent to the inner surface of the retina, the Internal Limiting Membrane (ILM), and varies in thickness from a single layer of collagen with interspersed cells to a thicker, multilayered fibrocellular proliferation, which often results in coarse folds on the retinal surface [2].  
This pathology can be classified into two types: idiopathic and secondary ERM. An ERM may develop without any antecedent ocular conditions or surgical procedures, termed idiopathic or primary ERM. Oppositely, secondary ERM is associated with a variety of ocular diseases, such as ocular inflammatory diseases, retinal vascular disease, retinal detachments, trauma, or surgery [1, 3]. The prevalence of this disease ranges from 4.0 to 6.2% and increases with age [1] with peak prevalence being observed in those between 70 and 79 years (11.6\(\sim\)35.7%) [2].  
In the earlier stages, ERMs do not cause visual symptoms. However, as it progresses, it contract and create superficial retinal folds leading to distortion of the retinal anatomy that can result in visual symptoms such as loss of visual acuity and metamorphosis [2, 3].  
Current imaging techniques, such as Spectral-Domain Optical Coherence Tomography (SD-OCT) with three-dimensional reconstruction can allow evaluation of the macula in cross-section and three-dimensionally [4, 5]. SD-OCT is a harmless, noninvasive medical imaging technique used to produce high-resolution cross-sectional images of biologicaltissues [5; 6]. Another relevant feature of SD-OCT is that due to its scanning speed, cross-sectional nature and image quality, it can be used for 3D reconstruction of the retina and ERM, enabling detailed analysis [7].  
Currently, the treatment options for ERM are limited, consisting of either observation or surgical intervention. Surgical intervention corresponds to pars plana vircctomy with ERM removal with or without ILM removal [4; 8]. At this stage, it is not possible to know in advance, in the pre-operative stage, which patients will benefit visually from the surgery. We hypothesize a link between the displacements of the retinal surface and the capacity of recovering visual acuity from the surgery. To test the hypothesis, it is necessary to pre-operatively quantify the displacements that the ERM can cause on the retina. Numerical simulation can be a powerful tool for a variety of purposes, and it will be used in this study as a way to compute displacements on the retinal surface, by simulating the EMR contraction.  
Although numerical simulation studies can be found on the literature related to the eye, ranging from the study of the eye temperature to the study of specific eye components [9; 10; 11; 12; 13; 14; 15], to the authors' knowledge no study exists concerning the numerical simulations of the ERM contraction. In the existing literature related to numerical studies of the eye [16; 17; 18; 19; 20; 21], the most used method in these types of works is the Finite Element Method (FEM), being the method chosen in the present study.  
No consensus exists on the most adequate type of materials to simulate the behaviour of the retina membrane, with several sources using different material models. However, a correct understanding of previous studies found in the literature allows the selection of two preferential constitutive models, the hyperelastic and linear elastic constitutive models [12; 20; 22; 23]. Considering the work performed by both [PERSON] et al. [24], where the author concluded that most biological tissues can be described by hyperelastic materials, and by [PERSON] et al. [21], where it is reported that the results obtained with hyperelastic models to simulate the retina behaviour are similar to the experimental results, it becomes reasonable to take these constitutive models as the baseline for the following work.