Structure‐function relationships in the visual system in multiple sclerosis: an MEG and OCT study

Abstract

BackgroundWe conducted a multi‐modal optical coherence tomography (OCT) and magnetoencephalography (MEG) study to test whether there is a relationship between retinal layer integrity and electrophysiological activity and connectivity (FC) in the visual network influenced by optic neuritis (ON) in patients with multiple sclerosis (MS).MethodsOne hundred and two MS patients were included in this MEG/OCT study. Retinal OCT data were collected from the optic discs, macular region, and segmented. Neuronal activity and FC in the visual cortex was estimated from source‐reconstructed resting‐state MEG data by computing relative power and the phase lag index (PLI). Generalized estimating equations (GEE) were used to account for intereye within‐patient dependencies.ResultsThere was a significant relationship for both relative power and FC in the visual cortex with retinal layer thicknesses. The findings were influenced by the presence of MSON, particularly for connectivity in the alpha bands and the outer macular layers. In the absence of MSON, this relationship was dominated by the lower frequency bands (theta, delta) and inner and outer retinal layers.ConclusionThese results suggest that visual cortex FC more than activity alters in the presence of MSON, which may guide the understanding of FC plasticity effects following MSON.

Cortical topological network changes following optic neuritis

“…10 A MEG/ OCT study of the visual system in patients with MS has succeeded in differentiating between patients with and without ON based on a unique pattern of connectivity that specifically involves the visual system. 46 These studies mostly focus on the neurologic deficit as the driving force behind the effects observed in MS and NMOSD connectivity and are congruent with the general connectivity patterns presented in our current study.…”

The utility of Magnetoencephalography in multiple sclerosis – A systematic review

“…Therefore, networks are possibly shifted towards random networks; The MST of MS patients showed a lower leaf fraction (delta, theta, and alpha2) with a lower degree divergence (delta, theta, alpha1, alpha2). This is suggestive of a shift towards more path life trees (reduced large scale integration) MST leaf tree fraction was negatively correlated with BOLD thalamo-cortical functional connectivity and EDSS ( Tewarie et al, 2017 ) Amsterdam Patients: 102 Controls: 0 PPMS – MSON & MSNON RRMS – MSON & MSNON SPMS – MSON & MSNON 8 PLI Resting State Significant relationship between retinal layer thickness and average PLI in bilateral MSON cases, with outer retinal layer thickness being positively related to PLI in visual cortex of mainly alpha 2 and delta band ( Schoonhoven et al, 2019 ) Amsterdam Patients: 83 Controls: 34 PPMS, RRMS, SPMS 8 Peak Frequency; Relative Power measurements of cortical and subcortical regions; Correlation of whole brain measurements and specific cognitive domains Resting State The regional cortical power differences between groups showed Cognitively Impaired (CI) patients with MS had significantly increased cortical theta and alpha1 power compared to controls and Cognitively Preserved patients; CI had significantly higher DGMV theta and lower alpha2 than CP. Differences in alpha 2 and theta were seen between Cognitively Impaired patients and controls in all subcortical areas, pronounced in bilateral thalami.…”

“…This study was discussed between reviewers as it answered hypothesis 3 and was an important study in helping delineate whether MEG is a prognostic biomarker. Another study looked at a large sample of patients with MS characterised by whether or not there were different subgroups (Optic Neuritis) within the MS population ( Tewarie et al, 2017 ). Given the importance of visual symptoms in Multiple Sclerosis, we considered it important to include this in a review of MEG in MS and elected to include this study.…”

“…There was some evidence for different measures as shown by MS-subgroups for Periventricular Lesions ( Karhu et al, 1992 ), cognitive impairment ( Schoonhoven et al, 2019 ), neuropathic pain ( Kim et al, 2019 , Kim et al, 2020 ), benzodiazepines ( Van Schependom et al, 2019 ), optic neuritis ( Tewarie et al, 2017 ) (see Table 1 ). Taken together there is some evidence that different disease features may be associated with different MEG parameters.…”