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Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Alterations in Retinal Layer Thickness and Reflectance at Different Stages of Diabetic Retinopathy by En Face Optical Coherence Tomography.
Investigative Ophthalmology & Visual Science 2016 July 2
PURPOSE: This article reports a method for en face optical coherence tomography (OCT) imaging and quantitative assessment of alterations in both thickness and reflectance of individual retinal layers at different stages of diabetic retinopathy (DR).
METHODS: High-density OCT raster volume scans were acquired in 29 diabetic subjects divided into no DR (NDR) or non-proliferative DR (NPDR) groups and 22 control subjects (CNTL). A customized image segmentation method identified eight retinal layer interfaces and generated en face thickness maps and reflectance images for nerve fiber layer (NFL), ganglion cell and inner plexiform layers (GCLIPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), photoreceptor outer segment layer (OSL), and retinal pigment epithelium (RPE). Mean thickness and intensity values were calculated in nine macular subfields for each retinal layer.
RESULTS: En face thickness maps and reflectance images of retinal layers in CNTL subjects corresponded to normal retinal anatomy. Total retinal thickness correlated negatively with age in nasal subfields (R ≤-0.31; P ≤ 0.03, N = 51). In NDR subjects, NFL and OPL thickness were decreased (P = 0.05), and ONL thickness was increased (P = 0.04) compared to CNTL. In NPDR subjects, GCLIPL thickness was increased in perifoveal subfields (P< 0.05) and INL intensity was higher in all macular subfields (P = 0.04) compared to CNTL.
CONCLUSIONS: Depth and spatially resolved retinal thickness and reflectance measurements are potential biomarkers for assessment and monitoring of DR.
METHODS: High-density OCT raster volume scans were acquired in 29 diabetic subjects divided into no DR (NDR) or non-proliferative DR (NPDR) groups and 22 control subjects (CNTL). A customized image segmentation method identified eight retinal layer interfaces and generated en face thickness maps and reflectance images for nerve fiber layer (NFL), ganglion cell and inner plexiform layers (GCLIPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), photoreceptor outer segment layer (OSL), and retinal pigment epithelium (RPE). Mean thickness and intensity values were calculated in nine macular subfields for each retinal layer.
RESULTS: En face thickness maps and reflectance images of retinal layers in CNTL subjects corresponded to normal retinal anatomy. Total retinal thickness correlated negatively with age in nasal subfields (R ≤-0.31; P ≤ 0.03, N = 51). In NDR subjects, NFL and OPL thickness were decreased (P = 0.05), and ONL thickness was increased (P = 0.04) compared to CNTL. In NPDR subjects, GCLIPL thickness was increased in perifoveal subfields (P< 0.05) and INL intensity was higher in all macular subfields (P = 0.04) compared to CNTL.
CONCLUSIONS: Depth and spatially resolved retinal thickness and reflectance measurements are potential biomarkers for assessment and monitoring of DR.
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