Abstract
Purpose: :
Fast scanning high resolution optical coherence tomography (HR-OCT) enables quantitative analysis of histological retinal layers. Aim of the present study was to measure maximum macular thickness of retinal ganglion cell plus inner plexiform layers (RGIPL) in healthy subjects and glaucoma patients in order to assess the diagnostic value.
Methods: :
Macular HR-OCT scans (Cirrus, Carl Zeiss Meditec) were obtained in 68 subjects (44 healthy subjects and 24 glaucoma patients) using raster scanning of a 20x20 field at a resolution of 512x128x1024 voxels. The scans were analysed using a software algorithm for automated segmentation and quantification in retinal layers. The macular area scans were dissected into one central area and 4 concentric rings with an incremental radius of 500 µm and further subdivided into 16 sectors each. For each of the 16 axis orientations in respect to the fovea the concentric ring segment with the maximum thickness of the RGIPL (RGIPLmax) has been determined. For each axis orientation RGIPLmax has been compared between age-matched healthy subjects (mean 54.1 ± 13.1 years) and glaucoma patients (60.5 ± 13.0 years) using ANOVA and ROC.
Results: :
The MD was 0.0 ± 1.3 in healthy subjects and -7.1 ± 6.6 for glaucoma patients. For all 16 sectors around the fovea the RGIPLmax was statistically significantly thinner in glaucoma patients compared to healthy volunteers. (p < 0.001). Furthermore we calculated the ROC-Area and could show that the separation effect had its peak temporal of the fovea, at sector 1 and 16, which are above and below the temporal raphe of the retinal nerve fiber layer. ROC area was 0.902 for mRGIPL, 0.900 for the sector 1 and 0.964 for sector 16. The ROC areas for the other sectors around the fovea indicated also fair to good diagnostic separation but in a slightly less distinctive manner (minimum ROC 0.778).
Conclusions: :
We were able to demonstrate significant differences between glaucoma patients and healthy volunteers for the RGIPLmax of the macula. More importantly, we present high ROC values for these parameters indicating a good diagnostic separation. This type of analysis is a promising approach for the use of RGIPL thickness data provided by automatic segmentation of the macular retinal layers and might offer an additional tool for diagnosis of glaucoma.
Keywords: imaging/image analysis: clinical