Next Article in Journal
Infants Investigated by the Child Welfare System: Exploring a Distinct Profile of Risks, Service Needs, and Referrals for Support in Ontario
Next Article in Special Issue
Melanocortins, Melanocortin Receptors and Multiple Sclerosis
Previous Article in Journal
Autonomic Dysfunction after Mild Traumatic Brain Injury
Previous Article in Special Issue
Multiple Sclerosis: Immunopathology and Treatment Update
Article Menu

Export Article

Open AccessArticle
Brain Sci. 2017, 7(8), 102; doi:10.3390/brainsci7080102

Structural and Neuronal Integrity Measures of Fatigue Severity in Multiple Sclerosis

Multiple Sclerosis Center, Department of Neurology, Detroit Medical Center, 4201 St Antoine, 8C-UHC Detroit 48201, MI, USA
The Sastry Foundation Advanced Imaging Laboratory, Wayne State School of Medicine, 4201 St Antoine, Detroit 48201, MI, USA
Department of Pediatric Neurology/PET Center, Children’s Hospital of Michigan, 4201 St Antoine, Detroit 48201, MI, USA
Author to whom correspondence should be addressed.
Received: 24 June 2017 / Revised: 4 August 2017 / Accepted: 7 August 2017 / Published: 12 August 2017
(This article belongs to the Special Issue Pathophysiology and Imaging Diagnosis of Demyelinating Disorders)
View Full-Text   |   Download PDF [750 KB, uploaded 12 August 2017]   |  


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

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Bernitsas, E.; Yarraguntla, K.; Bao, F.; Sood, R.; Santiago-Martinez, C.; Govindan, R.; Khan, O.; Seraji-Bozorgzad, N. Structural and Neuronal Integrity Measures of Fatigue Severity in Multiple Sclerosis. Brain Sci. 2017, 7, 102.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Brain Sci. EISSN 2076-3425 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top