The retinal ganglion cell layer predicts normal-appearing white matter tract integrity in multiple sclerosis: A combined diffusion tensor imaging and optical coherence tomography approach

Abstract

We investigated the relationship between retinal layers and normal-appearing white matter (WM) integrity in the brain of patients with relapsing-remitting multiple sclerosis (MS), using a combined diffusion tensor imaging and high resolution optical coherence tomography approach. Fifty patients and 62 controls were recruited. The patients were divided into two groups according to presence (n = 18) or absence (n = 32) of optic neuritis. Diffusion tensor data were analyzed with a voxel-wise whole brain analysis of diffusion metrics in WM with tract-based spatial statistics. Thickness measurements were obtained for each individual retinal layer. Partial correlation and multivariate regression analyses were performed, assessing the association between individual retinal layers and diffusion metrics across all groups. Region-based analysis was performed, by focusing on tracts associated with the visual system. Receiver operating characteristic (ROC) curves were computed to compare the biomarker potential for the diagnosis of MS, using the thickness of each retinal layer and diffusion metrics. In patients without optic neuritis, both ganglion cell layer (GCL) and inner plexiform layer thickness correlated with the diffusion metrics within and outside the visual system. GCL thickness was a significant predictor of diffusion metrics in the whole WM skeleton, unlike other layers. No association was observed for either controls or patients with a history of optic neuritis. ROC analysis showed that the biomarker potential for the diagnosis of MS based on the GCL was high when compared to other layers. We conclude that GCL integrity is a predictor of whole-brain WM disruption in MS patients without optic neuritis.

Keywords: diffusion tensor imaging; ganglion cell layer; multiple sclerosis; optic neuritis; optical coherence tomography; retinal segmentation; white matter pathology.

Figure 1

Macular image segmentation results, identifying the layers considered for this study. RNFL, retinal nerve fiber layer; GCL, ganglion cell layer; IPL, inner plexiform layer; INL, inner nuclear layer; OPL, outer plexiform layer; ONL, outer nuclear layer [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

Axial images of TBSS results for the correlation analysis between both FA and MD and thickness of retinal layers in the MSNON group. The results shown are for statistical testing of a positive correlation between FA and retinal layers thickness measurements (top), and negative correlation for MD (bottom). Regions with significant correlation (with cluster‐based thresholding corrected for multiple comparisons as well as Bonferroni correction for the number of retinal layers analyzed) are displayed in red to yellow (positive) and blue to light‐blue (negative). Results are overlaid on the mean WM skeleton (green) and mean FA image (gray). Both the OR and SCC are highlighted, in pink and light‐brown colors, respectively. White matter voxels with lesions were excluded from the analysis. Thus, only NAWM was considered. The significant portion of the tracts was dilated by using the “tbss_fill” command in FSL to enhance visualization. FA, fractional anisotropy; MD, mean diffusivity; OR, optic radiation; SCC, splenium of the corpus callosum; NAWM, normal‐appearing white matter; RNFL, retinal nerve fiber layer; GCL, ganglion cell layer; IPL, inner plexiform layer; INL, inner nuclear layer; OPL, outer plexiform layer; ONL, outer nuclear layer [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Scatterplot demonstrating the relationship between GCL thickness (main retinal predictor) and whole‐brain FA (left) and MD (right). GCL, ganglion cell layer; FA, fractional anisotropy; MD, mean diffusivity

Figure 4

ROC curves for whole skeleton FA, whole skeleton MD and GCL. The reference line represents the random event. All of these areas under the ROC curve were significantly greater than chance (p < .001). GCL, ganglion cell layer; FA, fractional anisotropy; MD, mean diffusivity