Structural Grading of Foveal Hypoplasia Using Spectral-Domain ...

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Figure 4. Algorithm used for grading foveal hypoplasia based on optical coherence tomography findings. The hallmark of foveal hypoplasia is incursion of the inner retinal layers. Based on disruption of the inner segment/outer segment (IS/OS) junction of the photoreceptor, the foveal hypoplasia is classified into either typical or atypical foveal hypoplasia. The grade of foveal hypoplasia can be determined based on whether the following features are present or absent: outer segment (OS) lengthening, foveal pit, and outer nuclear layer (ONL) widening. lengthening) were encountered, suggesting that pit formation may be dependent partly on OS lengthening. Successful centripetal migration of cone photoreceptors is represented by ONL widening (seen in grades 1, 2, and 3). However, in grade 4 foveal hypoplasia, this developmental process is completely arrested and has failed to occur. This grading system provides a prognostic visual function indicator by showing that the grade of foveal hypoplasia is significantly related to VA. It can be used easily in a clinical setting and does not require thickness measurements to predict and provide a likely visual prognosis for the patient with foveal hypoplasia. The grading system proposed accounts for the retinal structural basis for the decreased VA, but not for additional causes reducing VA, such as nystagmus, amblyopia, anterior segment disorder, or refractive error. Hence, morphologic grading of foveal hypoplasia can help in deciding whether further investigation or treatment are necessary to improve the patient’s VA. For instance, if a patient has grade 1 foveal hypoplasia and a VA of 0.7 logMAR, factors other than the foveal hypoplasia are likely to be contributing to the poor VA. Similarly, if a patient has a VA of 0.6 logMAR and has a grade 3 foveal hypoplasia, one would not expect the vision to improve past 0.5 logMAR because the structural development of the fovea is the limiting factor. An algorithm was also developed that is easy to follow and that can be used to derive the structural grade for foveal hypoplasia. Although 4 representative disorders associated with foveal hypoplasia were included, the grading system was not applied in patients with other forms of foveal hypoplasia, such as nanophthalmos 19 and retinopathy of prematurity. 20 In this study 1658 Ophthalmology Volume 118, Number 8, August 2011 population, VA correlated well with the grade of foveal hypoplasia; however, validation of the grading scheme in larger cohorts is necessary. The previous study by Seo et al 11 used OCT signs in albinism, which are dependent on reflectivity of structures in the tomogram such as foveal hyporeflectivity, choroidal transillumination, and tram tract sign. Presence or absence of foveal depression also was used to grade the foveal hypoplasia. Determining reflectivity features can be subjective, especially when using spectral-domain OCT, because they are associated with a sensitivity roll off, that is, the decrease in reflectivity values as the image moves away from the zero delay line. Hence, foveal hyporeflectivity may be difficult to interpret between an image that is close to the 0 delay line (which would be associated with higher reflectivity) and one that is further away (which would be less reflective). 21 This study avoided using reflectivity values because of the inherent difficulty in standardizing these values with spectral-domain OCT and because these signs may be specific for albinism. This study also showed that atypical foveal hypoplasia (seen in achromatopsia) is associated with worse visual prognosis in comparison with the typical disorders associated with foveal hypoplasia; this is because of the photoreceptor degeneration, visualized on OCT as IS/OS disruption. 22,23 Interestingly, in achromatopsia there is also a reduction in RT, whereas in typical foveal hypoplasia, there is an increase in RT compared with controls. This paradoxical reduction in RT in achromats is because of the ONL thinning resulting from photoreceptor degeneration. 22 However in achromatopsia, there is still a significantly shallower foveal pit compared with that in
controls and incursion of the inner retinal layers. This suggests that the centrifugal displacement of the inner retinal layers is not complete in some patients with achromatopsia. In summary, a structural grading system for foveal hypoplasia that relates to developmental stages and visual prognosis and that can be applied to most disorders associated with foveal hypoplasia was developed. Atypical forms of Thomas et al Structural Grading of Foveal Hypoplasia Figure 5. A, Bar graph showing the number of patients within each grade of foveal hypoplasia; the proportion of different disorders within each grade are shown with different shades. B, Box plots of visual acuity (VA) for each grade of foveal hypoplasia. The results of multiple comparisons of how grade of foveal hypoplasia affects VA are shown with the respective P values and median difference (d) in VA measured in logarithm of the minimum angle of resolution (logMAR) units. C, Box plot showing that similarly, there was a significant difference in visual acuity between the typical forms of foveal hypoplasia and atypical foveal hypoplasia. The other features that were significantly different between the controls and typical and atypical forms of foveal hypoplasia were: (D) retinal thickness at the fovea, (E) outer nuclear layer thickness, and (F) foveal depth. For all box plots, the whiskers represents the maximum and minimum range of observations, whereas the box represents the interquartile range and the line dividing the box represents the median. All multiple comparisons are shown with the box plots with the significance values and median differences (d), units for which are logMAR (for B and C) or micrometers (for D, E, and F). foveal hypoplasia seen with achromatopsia that are associated with worse visual prognosis resulting from photoreceptor degeneration also were investigated. This grading is especially suitable for clinical use because it is qualitative and fast, does not need measurements or specialized analytical software, and hence can be used just by visualizing the OCT. 1659
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