Spatial distribution of posterior pole choroidal thickness by spectral domain optical coherence tomography.

摘要: The choroid, a vascular meshwork between the retina and sclera, plays major role in providing oxygen nutrition to outer layers of retina.1 In recent years, increased awareness its ocular development known association with many diseases posterior pole have stimulated renewed focus on understanding choroidal anatomy physiology.2 A number methods, including histology3 ultrasonography,4 previously been used quantify thickness (CT); however, overall precision these approaches is still lacking. Fortunately, introduction spectral domain optical coherence tomography (SD-OCT) description “enhanced depth imaging” scanning protocols afforded new opportunity improve accuracy quantitative assessment. As result, changes CT now studied using different OCT technologies over wide range pathologies (e.g., glaucoma,5 inherited retinal diseases,6 high myopia,7 central serous chorioretinopathy,8 polypoidal vasculopathy,9 neovascular age-related macular degeneration [AMD],9 Vogt Koyanagi Harada disease10). Although use has provided insights into morphology, date there exists notable disparity measurements obtained studies. For example, several studies cross-sectional variation “normal” subjects shown be greatest at fovea, decreasing more nasally than temporally.9,11,12 Other results suggest that foveal thinner choroid superior fovea.13 These discrepancies may arise due image acquisition methodologies, generally limited field view for scanning, inconsistencies choosing exact locations repeated measurement. Regardless, spatial distribution region human eyes remains unclear. In addition, most OCT-derived focused assessment alone, examining correlation disease expression. However, unlike neurosensory retina, complex highly organized neural structure fovea as unmistaken center, layer potentially very topography. Determination thus difficult, inaccurate, context alone. this report, we aim address issues by obtaining larger, two-dimensional (2D) maps identifying specific patterns healthy volunteers SD-OCT.