Purpose: The advent of macular optical coherence tomography (OCT) segmentation has enabled the in vivo quantitative assessment of retinal axonal and neuronal subpopulations. Recent studies employing OCT in multiple sclerosis (MS) have utilized various manual macular segmentation approaches to quantify retinal layer thicknesses. We investigated whether measurements of retinal layers solely at the points of maximal macular thickness (point estimates) within the central macular B-scan are representative of the corresponding average layer thicknesses for the ganglion cell + inner plexiform (GCIP) layers, inner nuclear layer (INL), outer plexiform layer (OPL) and outer nuclear layer (ONL) in MS and healthy controls. Additionally, we examined the correlation of manual segmentation-derived measures of composite layers with average thickness measures derived from automated 3-D segmentation of the macular cube.
Materials and methods: Spectral-domain OCT central macular B-scans of 52 MS patients and 30 healthy controls (HCs) were manually segmented. Average layer thicknesses and layer thicknesses at the points of maximal macular thickness were calculated. Macular cube scans were also segmented utilizing a fully automated 3-D segmentation algorithm.
Results: GCIP, INL and OPL maximal thicknesses derived from point estimates correlated well with the average thicknesses of these layers within the central macular B-scan, whereas the ONL maximal thickness did not correlate as strongly. Manual segmentation-derived point estimates and average thickness measures of the GCIP correlated excellently with corresponding automated segmentation-derived measures. MS patients had significantly decreased GCIP maximal and average thicknesses relative to HCs. ONL average thickness was significantly decreased in MS compared to HCs, but this was not true of the ONL maximal thickness.
Conclusions: GCIP, INL and OPL maximal layer thicknesses may be used as surrogates to assess the gross structural integrity of these layers in MS, in a time-conservative fashion.