Stochastic Modeling to Identify the Normal Response of an Optic Nerve Head to Small Increases in Intraocular Pressure

Glaucoma is one of the leading causes of blindness worldwide. Although elevated intraocular pressure (IOP) is the main risk factor for the development of the disease, its role remains unclear. Several studies have explored the hypothesis that an IOP-induced altered biomechanical environment within the optic nerve head (ONH), and the lamina cribrosa in particular, may contribute to disruption of the retinal ganglion cell axons, and the subsequent loss of vision associated with glaucoma [1–3]. Identifying the normal ONH biomechanical environment, however, has proven challenging. This has been in part because of the difficulty in accessing the ONH directly for experimentation, but also because of the difficulty in reconstructing models of the relevant structures with which to estimate its biomechanics. Few models represent only a small subset of the possible variations in ONH characteristics in a population, with the consequent lack of statistical power in the predictions.