To characterize the material properties of posterior and peripapillary sclera from human donors, and to investigate the macro- and micro-scale strains as potential control mechanisms governing mechanical homeostasis. Posterior scleral shells from 9 human donors aged 57–90 years were subjected to IOP elevations from 5 to 45 mmHg and the resulting full-field displacements were recorded using laser speckle interferometry. Eye-specific finite element models were generated based on experimentally measured scleral shell surface geometry and thickness. Inverse numerical analyses were performed to identify material parameters for each eye by matching experimental deformation measurements to model predictions using a microstructure-based constitutive formulation that incorporates the crimp response and anisotropic architecture of scleral collagen fibrils. The material property fitting produced models that fit both the overall and local deformation responses of posterior scleral shells very well. The nonlinear stiffening of the sclera with increasing IOP was well reproduced by the uncrimping of scleral collagen fibrils, and a circumferentially-aligned ring of collagen fibrils around the scleral canal was predicted in all eyes. Macroscopic in-plane strains were significantly higher in peripapillary region then in the mid-periphery. In contrast, the meso- and micro-scale strains at the collagen network and collagen fibril level were not significantly different between regions. The elastic response of the posterior human sclera can be characterized by the anisotropic architecture and crimp response of scleral collagen fibrils. The similar collagen fibril strains in the peripapillary and mid-peripheral regions support the notion that the scleral collagen architecture including the circumpapillary ring of collagen fibrils evolved to establish optimal load bearing conditions at the collagen fibril level.

To test the hypothesis that mechanical strain in the posterior human sclera is altered with age, twenty pairs of normal eyes from human donors aged 20 to 90 years old were inflation tested within 48 hours post mortem. The intact posterior scleral shells were pressurized from 5 to 45 mmHg while the full-field three-dimensional displacements of the scleral surface were measured using laser speckle interferometry. The full strain tensor of the outer scleral surface was calculated directly from the displacement field. Mean maximum principal (tensile) strain was computed for eight circumferential sectors (45° wide) within the peripapillary and mid-peripheral regions surrounding the optic nerve head (ONH). To estimate the age-related changes in scleral strain, results were fit using a functional mixed effects model that accounts for intra-donor variability and spatial autocorrelation. Mechanical tensile strain in the peripapillary sclera is significantly higher than the strain in the sclera farther away from the ONH. Overall, strains in the peripapillary sclera decrease significantly with age. Sectorially, peripapillary scleral tensile strains in the nasal sectors are significantly higher than the temporal sectors at younger ages, but the sectorial strain pattern reverses with age, and the temporal sectors exhibited the highest tensile strains in the elderly. Overall, peripapillary scleral structural stiffness increases significantly with age. The sectorial pattern of peripapillary scleral strain reverses with age, which may predispose adjacent regions of the lamina cribrosa to biomechanical insult. The pattern and age-related changes in sectorial peripapillary scleral strain closely match those seen in disk hemorrhages and neuroretinal rim area measurement change rates reported in previous studies of normal human subjects.

Purpose: To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT (SD OCT) optic nerve head images.Design: Evaluation of a diagnostic technology.Participants: A total of 9765 visual field (VF) SD OCT pairs collected from 1194 participants with and without GVFD (1909 eyes).Methods: Deep learning models were trained to use SD OCT retinal nerve fiber layer (RNFL) thickness maps, RNFL en face images, and confocal scanning laser ophthalmoscopy (CSLO) images to identify eyes with GVFD and predict quantitative VF mean deviation (MD), pattern standard deviation (PSD), and mean VF sectoral pattern deviation (PD) from SD OCT data.Main Outcome Measures: Deep learning models were compared with mean RNFL thickness for identifying GVFD using area under the curve (AUC), sensitivity, and specificity. For predicting MD, PSD, and mean sectoral PD, models were evaluated using R 2 and mean absolute error (MAE).Results: In the independent test dataset, the deep learning models based on RNFL en face images achieved an AUC of 0.88 for identifying eyes with GVFD and 0.82 for detecting mild GVFD significantly (P < 0.001) better than using mean RNFL thickness measurements (AUC ¼ 0.82 and 0.73, respectively). Deep learning models outperformed standard RNFL thickness measurements in predicting all quantitative VF metrics. In predicting MD, deep learning models based on RNFL en face images achieved an R 2 of 0.70 and MAE of 2.5 decibels (dB) compared with 0.45 and 3.7 dB for RNFL thickness measurements. In predicting mean VF sectoral PD, deep learning models achieved high accuracy in the inferior nasal (R 2 ¼ 0.60) and superior nasal (R 2 ¼ 0.67) sectors, moderate accuracy in inferior (R 2 ¼ 0.26) and superior (R 2 ¼ 0.35) sectors, and lower accuracy in the central (R 2 ¼ 0.15) and temporal (R 2 ¼ 0.12) sectors.Conclusions: Deep learning models had high accuracy in identifying eyes with GFVD and predicting the severity of functional loss from SD OCT images. Accurately predicting the severity of GFVD from SD OCT imaging can help clinicians more effectively individualize the frequency of VF testing to the individual patient.

The age- and race-related differences in scleral material properties result in a loss of scleral compliance due to a higher shear stiffness and a lower level of stretch at which the collagen fibrils uncrimp. The loss of compliance should lead to larger high frequency IOP fluctuations and changes in the optic nerve head (ONH) biomechanical response in the elderly and in persons of African ancestry, and may contribute to the higher susceptibility to glaucoma in these at-risk populations.

Human posterior sclera exhibits complex regional mechanical behavior in response to acute IOP elevations from 5 to 45 mm Hg. Results indicate 1) the peripapillary sclera is subjected to significantly higher tensile strain than the adjacent mid-peripheral sclera, and 2) strains are significantly higher in the temporal and inferior quadrants of the peripapillary sclera, which may contribute to the increased prevalence of glaucomatous damage associated with these regions of the ONH.