The glaucomas are a group of relatively common optic neuropathies, in which the pathological loss of retinal ganglion cells causes a progressive loss of sight and associated alterations in the retinal nerve fiber layer and optic nerve head. The diagnosis and management of glaucoma are often dependent on methods of clinical testing that either, 1) identify and quantify patterns of functional visual abnormality, or 2) quantify structural abnormality in the retinal nerve fiber layer, both of which are caused by loss of retinal ganglion cells. Although it is evident that the abnormalities in structure and function should be correlated, propositions to link losses in structure and function in glaucoma have been formulated only recently. The present report describes an attempt to build a model of these linking propositions using data from investigations of the relationships between losses of visual sensitivity and thinning of retinal nerve fiber layer over progressive stages of glaucoma severity. A foundation for the model was laid through the pointwise relationships between visual sensitivities (behavioral perimetry in monkeys with experimental glaucoma) and histological analyses of retinal ganglion cell densities in corresponding retinal locations. The subsequent blocks of the model were constructed from clinical studies of aging in normal human subjects and of clinical glaucoma in patients to provide a direct comparison of the results from standard clinical perimetry and optical coherence tomography. The final formulation is a nonlinear structure-function model that was evaluated by the accuracy and precision of translating visual sensitivities in a region of the visual field to produce a predicted thickness of the retinal nerve fiber layer in the peripapillary sector that corresponded to the region of reduced visual sensitivity. The model was tested on two independent patient populations, with results that confirmed the predictive relationship between the retinal nerve fiber layer thickness and visual sensitivities from clinical perimetry. Thus, the proposed model for linking structure and function in glaucoma has provided information that is important in understanding the results of standard clinical testing and the neuronal losses caused by glaucoma, which may have clinical application for inter-test comparisons of the stage of disease.

The results suggest that the proportion of RNFL that is composed of RGC axons is not constant with age; rather, the proportion of the total thickness from non-neuronal tissue increases with age. If a similar compensation occurs in the RNFL thickness with axon loss from glaucoma, then a stage-dependent correction to translate OCT measurements to neuronal components is needed, in addition to the age-dependent correction.

In nonhuman primates, with appropriate transverse scaling and ONH shape analysis, the cross-sectional area of the RNFL is independent of scan distance, up to 600 μm from the rim margin, indicating that the axonal composition changes little over this range. The results suggest that, with incorporation of transverse scaling, the RNFL cross-sectional area, rather than RNFL thickness, provides an accurate assessment of the retinal ganglion cell axonal content within the eye.

The analysis of normative data suggests a model of age-related thinning of RNFL in which the relationship between RNFL thickness and the density of RGC axons varies with the number of neurons that are lost through normal aging. This model posits that the OCT measurement of total RNFL thickness of a normal retina represents two components: 1) an age-dependent population of RNFL axons, and 2) a non-neural component that partially compensates for the age-related decrease in axons in the nerve fiber layer.

Purpose An assessment of the retinal nerve fiber layer (RNFL) provides important information on the health of the optic nerve. There are several non-invasive technologies, including spectral domain optical coherence tomography (SD-OCT), that can be used for in vivo imaging and quantification of the RNFL, but often there is disagreement in RNFL thickness between clinical instruments. The purpose of this study was to investigate the influence of scan centration, ocular magnification and segmentation on the degree of agreement of RNFL thickness measures by two SD-OCT instruments. Methods RNFL scans were acquired from forty-five normal eyes using two commercially available SD-OCT systems. Agreement between RNFL thickness measures was determined using each instrument's algorithm for segmentation and a custom algorithm for segmentation. The custom algorithm included ocular biometry measures to compute the transverse scaling for each eye. Major retinal vessels were identified and removed from RNFL measures in 1:1 scaled images. Transverse scaling was also used to compute the RNFL area for each scan. Results Instrument derived global RNFL thickness measured from the two instruments correlated well (R2 = 0.70, p<0.01), but with significant differences between instruments (mean of 6.7 µm; 95% limits of agreement of 16.0 µm to −2.5 µm, ICC = 0.62). For recentered scans with custom RNFL segmentation, the mean difference was reduced to 0.1 µm (95% limits of agreement 6.1 µm to −5.8 µm, ICC = 0.92). Global RNFL thickness was related to axial length (R2 = 0.24, p<0.01), while global RNFL area measures were not (R2 = 0.004, p = 0.66). Major retinal vasculature accounted for 11.3±1.6% (Cirrus) or 11.8±1.4% (Spectralis) of the RNFL thickness/area measures. Conclusions Sources of disagreement in RNFL measures between SD-OCT instruments can be attributed to the location of the scan path and differences in their retinal layer segmentation algorithms. In normal eyes, the major retinal vasculature accounts for a significant percentage of the RNFL and is similar between instruments. With incorporation of an individual's ocular biometry, RNFL area measures are independent of axial length, with either instrument.