Automated segmentation of the lamina cribrosa using Frangi's filter: a novel approach for rapid identification of tissue volume fraction and beam orientation in a trabeculated structure in the eye

Abstract

The lamina cribrosa (LC) is a tissue in the posterior eye with a complex trabecular microstructure. This tissue is of great research interest, as it is likely the initial site of retinal ganglion cell axonal damage in glaucoma. Unfortunately, the LC is difficult to access experimentally, and thus imaging techniques in tandem with image processing have emerged as powerful tools to study the microstructure and biomechanics of this tissue. Here, we present a staining approach to enhance the contrast of the microstructure in micro-computed tomography (micro-CT) imaging as well as a comparison between tissues imaged with micro-CT and second harmonic generation (SHG) microscopy. We then apply a modified version of Frangi's vesselness filter to automatically segment the connective tissue beams of the LC and determine the orientation of each beam. This approach successfully segmented the beams of a porcine optic nerve head from micro-CT in three dimensions and SHG microscopy in two dimensions. As an application of this filter, we present finite-element modelling of the posterior eye that suggests that connective tissue volume fraction is the major driving factor of LC biomechanics. We conclude that segmentation with Frangi's filter is a powerful tool for future image-driven studies of LC biomechanics.

Whole-globe biomechanics using high-field MRI

“…Recently, Micro-CT methods have been developed which offer improved resolution, however these methods require the use of alcohol based contrast agents which alter the hydration status of the eye and a fine beam radiation source such as a synchrotron (Campbell et al, 2015; Coudrillier et al, 2016; Hann et al, 2011). …”

“…Recently, the so-called whole-eye OCT devices have permitted simultaneous imaging of both anterior (cornea) and posterior segments (macula or ONH), but do not provide data elsewhere (Dai et al, 2012; Fan et al, 2015b). CT can produce very high resolution images, capturing structures of the LC, but due to limited soft tissue contrast, additional contrast agents, which may affect tissue mechanics, or very high energy systems are required (Campbell et al, 2015; Coudrillier et al, 2016). Further, those high energy systems cannot be used in-vivo due to radiation exposure and are not widely available.…”

Effects of collagen microstructure and material properties on the deformation of the neural tissues of the lamina cribrosa

“…First we modeled the ONH at a mesoscale level (mean element edge length of 112 µm), using serial histological sections of the ONH and peripapilary sclera, similar to previous approaches [13, 14]. These models were then used as boundary conditions for high resolution, microscale models of LC regions (mean element edge length of 7–10 µm) which included distinct material properties for LC neural tissues and beams.…”

“…Much work has gone into modeling the complex structures of the optic nerve head (ONH), the region of the eye including the LC where the RGC axons converge to form the optic nerve, in an attempt to understand how the LC and other tissues of the ONH deform under elevated IOP [8–14]. Over the last ten years, efforts have primarily focused on developing models that include the effects of collagen fiber alignment and material non-linearity [13–15], both improvements upon earlier isotropic linear models [9, 10, 16].…”

“…Not surprisingly, the models have been unable to reproduce the strain fields observed experimentally. Recent models predict tensile strains within the LC to be less than 5% under elevated levels of IOP [10, 13, 14, 16, 17], whereas experimental studies by us [18, 19] and others [20] have measured IOP-induced strains exceeding 10 and even 20% in some regions. Further, these experiments revealed highly heterogeneous deformation fields, with levels of stretch varying greatly from one LC pore to another.…”