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We investigated the association of retinal nerve fibre layer thickness (RNFL) with white matter damage assessed by diffusion tensor imaging (DTI). Forty-four MS patients and 30 healthy subjects underwent optical coherence tomography. DTI was analysed with a voxel-based whole brain and region-based analysis of optic radiation, corpus callosum and further white matter. Correlations between RNFL, fractional anisotropy (FA) and other DTI-based parameters were assessed in patients and controls. RNFL correlated with optic radiation FA, but also with corpus callosum and remaining white matter FA. Our findings demonstrate that RNFL changes indicate white matter damage exceeding the visual pathway. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment and visual deterioration are two key clinical symptoms in MS and affect 50 to 80% of patients. Little is known about the influence of cognitive impairment on visual tests recommended for MS such as low contrast sensitivity testing. Our objective was to investigate whether low contrast sensitivity testing is influenced by cognitive impairment in multiple sclerosis (MS) patients. Methods: Cross-sectional study including 89 patients with relapsing-remitting MS. All patients received cognitive evaluation using Rao’s Brief Repeatable Battery of Neuropsychological Testing (BRB-N). Visual assessments included low contrast sensitivity (CS) by functional acuity contrast testing and high contrast visual acuity (VA) using ETDRS charts. Retinal morphology as visual impairment correlate was measured using retinal nerve fiber layer (RNFL) thickness by optical coherence tomography. Results: In combined analyses using generalized estimating equation models, Paced Auditory Serial Addition Test (PASAT) and RNFL as well as and the Symbol Digit Modalities Test (SDMT) and RNFL predicted CS. To further control for a potential influence of the anterior visual system we performed partial correlation analyses between visual function and cognitive function test results but controlling for RNFL. Even when controlling for RNFL, CS was associated with PASAT performance and SDMT performance. Conclusion: Our data show that: a) cognitive impairment and performance in visual function tests such as low contrast sensitivity testing are associated; b) the main cognitive domains correlating with visual test performance are information processing speed and, to a lesser degree, memory; This preliminary data needs to be substantiated in further studies investigating patients with a higher cognitive burden, healthy controls and in longitudinal settings. [ABSTRACT FROM AUTHOR]

Fatigue is one of the most frequent and disabling symptoms in multiple sclerosis (MS). Its pathophysiology remains poorly understood and objective measures to quantify fatigue are unavailable to date. To investigate whether analysis of ocular motor movements can provide diagnostic information in MS patients with fatigue, 37 MS patients (21 female, age 44 ± 9 years) and 20 age- and gender-matched healthy controls were prospectively recruited. Fatigue was assessed with the fatigue severity scale (FSS). Twenty-five MS patients were fatigued (defined as FSS ≥4) and 12 MS patients were not. Subjects performed a saccadic fatigue task that required execution of uniform saccades over a period of 10 min. Saccadic amplitude, latency and peak velocities during the task were analysed and selected parameters were tested in a receiver operating characteristic (ROC) analysis. Fatigued patients showed a significantly larger decrease of saccadic peak velocity and amplitude when compared to patients without fatigue and healthy controls. Furthermore, fatigued patients showed significantly longer latencies compared to non-fatigued patients and healthy controls. Peak velocity change over time and latencies correlated with FSS scores. The best parameter to discriminate between fatigued and non-fatigued patients was peak velocity change over time (ROC; area under the curve = 0.857). Assessment of peak velocity, amplitude and latency in a saccade fatigue task is a promising approach for quantifying fatigue in MS patients. [ABSTRACT FROM AUTHOR]