Structural and Neuronal Integrity Measures of Fatigue Severity in Multiple Sclerosis

Brain Sci. 2017 Aug 12;7(8):102. doi: 10.3390/brainsci7080102.

Abstract

Fatigue is a common and disabling symptom in Multiple Sclerosis (MS). However, consistent neuroimaging correlates of its severity are not fully elucidated. In this article, we study the neuronal correlates of fatigue severity in MS. Forty-three Relapsing Remitting MS (RRMS) patients with MS-related fatigue (Fatigue Severity Scale (FSS) range: 1-7) and Expanded Disability Status Scale (EDSS) ≤ 4, were divided into high fatigue (HF, FSS ≥ 5.1) and low fatigue groups (LF, FSS ≤ 3). We measured T2 lesion load using a semi-automated technique. Cortical thickness, volume of sub-cortical nuclei, and brainstem structures were measured using Freesurfer. Cortical Diffusion Tensor Imaging (DTI) parameters were extracted using a cross modality technique. A correlation analysis was performed between FSS, volumetric, and DTI indices across all patients. HF patients showed significantly lower volume of thalamus, (p = 0.02), pallidum (p = 0.01), and superior cerebellar peduncle ((SCP), p = 0.002). The inverse correlation between the FSS score and the above volumes was significant in the total study population. In the right temporal cortex (RTC), the Radial Diffusivity ((RD), p = 0.01) and Fractional Anisotropy ((FA), p = 0.01) was significantly higher and lower, respectively, in the HF group. After Bonferroni correction, thalamic volume, FA-RTC, and RD-RTC remained statistically significant. Multivariate regression analysis identified FA-RTC as the best predictor of fatigue severity. Our data suggest an association between fatigue severity and volumetric changes of thalamus, pallidum, and SCP. Early neuronal injury in the RTC is implicated in the pathogenesis of MS-related fatigue.

Keywords: cortical thickness; deep gray matter nuclei volume; diffuse tensor imaging; fatigue; fatigue severity scale; multiple sclerosis.