Purpose
To report normal baseline thickness maps for 6 retinal layers generated by segmentation of spectral-domain optical coherence tomography (SD-OCT) images in normal subjects. Intersubject thickness variability and thickness variations in 9 macular sectors were established.
Design
Prospective cross-sectional study.
Materials and Methods
SD-OCT imaging was performed in 15 normal subjects. Nineteen SD-OCT images were acquired, encompassing a 6 × 5-mm retinal area, centered on the fovea. Each image was analyzed using an automated segmentation algorithm to derive thickness profiles of 6 retinal layers. Thickness data obtained from all scans were combined to generate thickness maps of 6 retinal layers: nerve fiber layer, ganglion cell layer + inner plexiform layer, inner nuclear layer, outer plexiform layer, outer nuclear layer + photoreceptor inner segments, and photoreceptor outer segments. Mean and standard deviation of thickness measurements were calculated in 9 macular sectors and 6 retinal layers. Intersubject and intrasector thickness variations were established based on standard deviation of measurements.
Results
Minimum and maximum thickness of the nerve fiber layer were observed in the foveal and nasal perifoveal areas, respectively. The largest thickness variation among subjects and intrasector variability were observed in perifoveal areas. Thickness of the ganglion cell layer + inner plexiform layer and intersubject thickness variability were largest in parafoveal areas. The inner nuclear layer thickness was relatively constant in parafoveal and perifoveal areas and intrasector thickness variations were largest in the foveal area. The outer plexiform layer thickness was relatively constant in foveal and parafoveal areas and higher than in perifoveal areas. Intersubject thickness variability in inner nuclear layer and outer plexiform layer was relatively uniform in all macular sectors. The outer nuclear layer + photoreceptor inner segments thickness map displayed maximum thickness in the foveal area and intersubject thickness variability was largest superior to the fovea. Thickness of the photoreceptor outer segments layer, thickness variations among subjects, and intrasector thickness variability were relatively constant. There was a significant correlation between total retinal thickness derived by thickness mapping and SD-OCT commercial software.
Conclusion
Normal thickness maps for 6 retinal layers were generated and thickness variations among subjects and macular areas were assessed. This technique is promising for investigating thickness changes attributable to disease in specific retinal layers and macular areas.
Optical coherence tomography (OCT) is an optical imaging technique that provides objective and quantitative measurements of retinal thickness alterations associated with retinal diseases. OCT images have been analyzed to provide maps of normal macular thickness. Furthermore, segmentation of OCT images has provided information about thickness of specific retinal layers. Time-domain (TD) OCT images have been segmented to provide thickness maps of the nerve fiber layer, ganglion cell layer, inner plexiform layer, and inner nuclear layer in normal subjects and glaucoma patients. Additionally, thickness maps of the outer nuclear layer have been generated in normal subjects and in children with Leber’s congenital amaurosis. Furthermore, ultra-high-resolution OCT imaging has been applied to measure thickness of the photoreceptor layer in normal subjects and patients with macular degeneration.
With the availability of spectral-domain OCT (SD-OCT), it is now possible to obtain multiple scans over a retinal area and generate quantitative maps of retinal thickness with high spatial resolution. Several studies have reported comparisons of total retinal thickness measurements obtained by TD- and SD-OCT instruments. Additionally, SD-OCT imaging technology has been used to measure macular thickness in normal subjects and to generate macular thickness maps of a 3-layer complex consisting of the nerve fiber layer, ganglion cell layer, and inner plexiform layer in patients with various nonglaucomatous optic neuropathies. In the current study, our previously reported SD-OCT image segmentation technique was applied to SD-OCT images. Normal thickness maps of 6 retinal layers were generated and intersubject thickness variations were assessed. For each retinal layer, thickness measurements and variations in 9 macular sectors were established. Generating normal thickness maps of retinal layers and assessing thickness variations among subjects is needed to identify thickness changes that occur because of disease.
Materials and Methods
SD-OCT imaging was performed in 1 eye of 15 normal subjects, 8 female and 7 male, 8 right and 7 left eyes. The subjects’ ages ranged between 40 and 59 years, with an average age of 52 ± 6 years (mean ± standard deviation).
SD-OCT imaging was performed using a commercially available OCT instrument (Spectralis, Heidelberg Engineering, Heidelberg, Germany). Nineteen horizontal SD-OCT B-scans were acquired in each eye, encompassing a 6 × 5-mm retinal area, centered on the fovea. Each SD-OCT image was 1024 pixels (6 mm) in length and 496 pixels (2 mm) in depth. The grayscale SD-OCT images were exported in tagged image file format for segmentation analysis.
Each SD-OCT image was analyzed using an image segmentation algorithm and thickness profiles of 6 retinal layers were automatically generated, as previously described. A representative SD-OCT image obtained in 1 subject is shown in Figure 1 . Six retinal layers were identified by the automatic segmentation algorithm: nerve fiber layer (layer 1), ganglion cell layer + inner plexiform layer (layer 2), inner nuclear layer (layer 3), outer plexiform layer (layer 4), outer nuclear layer + photoreceptor inner segments (layer 5), and photoreceptor outer segments (layer 6). The image segmentation algorithm was applied to all 19 SD-OCT images. From each image, a thickness profile for each of the 6 retinal layers was generated by averaging thickness over contiguous 240-μm segments, along the 6-mm scan length. Layer 1 thickness profiles derived from all images were combined to generate a thickness map of layer 1. This procedure was repeated for each of the 6 retinal layers. Thickness maps of the 6 retinal layers were displayed in pseudo-color. Total retinal thickness was also calculated by summing thickness measurements in the 6 layers.
From the retinal layer thickness map, data were grouped in 9 macular sectors within 3 concentric circles as defined by the Early Treatment Diabetic Retinopathy Study. The retinal areas encompassed by the 9 macular sectors are displayed in Figure 2 . In each subject, the location of the center of fovea was first identified based on the minimum thickness on the map of layer 2 (ganglion cell layer + inner plexiform layer). This location defined the center of the concentric circles. Since the thickness data were stored in a 2-dimensional rectangular array, the horizontal dimension was used to define the diameter of the circles for grouping of data points. The central circle (sector 1) had a diameter of 1.2 mm and represented the central foveal area. The second circle had a diameter of 3.1 mm and was subdivided into superior (sector 2), nasal (sector 3), inferior (sector 4), and temporal (sector 5) parafoveal retinal areas. The third circle had a diameter of 6 mm and was subdivided into superior (sector 6), nasal (sector 7), inferior (sector 8), and temporal (sector 9) perifoveal retinal areas. Macular sectors 1, 2 to 5, and 6 to 9 contained 15, 38, and 74 data points, respectively.
From thickness maps generated in each subject, a mean and standard deviation (SD) of measurements was calculated in each of the 9 macular sectors and 6 retinal layers. Intrasector variability was defined by a mean SD of thickness measurements, averaged over all subjects. From thickness maps generated in all subjects, a mean normal thickness was established in each of the 9 macular sectors and in each of the 6 layers, by averaging thickness measurements over all subjects. Intersubject variability was defined as the SD of thickness measurements in all subjects. Thickness measurements among sectors were compared in each layer using analysis of variance statistics. Total retinal thickness in each sector was calculated by summing thickness measurements in all 6 layers. In the same subjects, an average total retinal thickness in each macular sector was obtained from the Spectralis SD-OCT software. Total retinal thickness measurements, averaged over all macular sectors, obtained by automated mapping and Spectralis SD-OCT software were compared, using linear regression analysis.
Results
By automated segmentation of 19 SD-OCT images, thickness maps were generated in 6 retinal layers: nerve fiber layer (layer 1), ganglion cell layer + inner plexiform layer (layer 2), inner nuclear layer (layer 3), outer plexiform layer (layer 4), outer nuclear layer + photoreceptor inner segments (layer 5), and photoreceptor outer segments (layer 6). Examples of thickness maps generated from the right eye of 1 subject are shown in Figure 3 . The thickness map of layer 1 (nerve fiber layer) displayed minimum thickness in the central foveal area and maximum thickness nasal to the fovea. The thickness map of layer 2 (ganglion cell layer + inner plexiform layer) also displayed a minimum thickness in the central foveal area, but the maximum thickness was observed in a circular pattern in the parafoveal retinal area. The thickness map of layer 3 (inner nuclear layer) showed a relatively constant thickness, with the lowest thickness in the central foveal area. In the foveal and parafoveal retinal areas, thickness of layer 4 (outer plexiform layer) was highest and relatively constant, while in the perifoveal retinal area, thickness was lower and also relatively constant. Thickness of layer 5 (outer nuclear layer + photoreceptor inner segments) was highest in the central foveal area and relatively constant in the parafoveal and perifoveal retinal areas. The thickness map of layer 6 (photoreceptor outer segments) displayed a uniform thickness in all retinal areas.
Mean macular sector thickness for each of the 6 retinal layers and the corresponding SD (intersubject thickness variability) is shown in Figure 4 (displayed for a right eye). Nerve fiber layer thickness superior and inferior to the fovea was similar. A minimum thickness of the nerve fiber layer was observed in the central foveal area and a maximum thickness in the perifoveal retinal area, nasal to the fovea and closest to the optic nerve head. Thickness of the ganglion cell layer + inner plexiform layer was highest in parafoveal retinal areas, particularly nasal to the fovea. The inner nuclear layer thickness was relatively constant in all macular sectors, with a minimum thickness observed in the central foveal area. The outer plexiform layer thickness was also relatively constant in foveal and parafoveal retinal areas and higher than the uniform thickness measured in perifoveal retinal areas. The outer nuclear layer + photoreceptor inner segments thickness map displayed a maximum thickness in the central foveal area and a relatively constant thickness in the perifoveal retinal areas. Thickness of the photoreceptor outer segments layer was slightly higher in the central foveal area, but overall was relatively constant in all macular sectors.
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