Association of associative, limbic and sensorimotor subcortical structures with fatigue in multiple sclerosis

Context

Fatigue is a disabling symptom in 65-97% of patients with multiple sclerosis (MS). Fatigue is the presenting symptom in one third of MS patients and 15-40% describe fatigue as their most severe symptom. Despite its clinical significance, the pathophysiology of fatigue is not well understood. Neural, immune, endocrine and metabolic mechanisms have all been proposed. Previous studies have associated damage to several cortical and subcortical structures with fatigue in MS. However, structural integrity of associative, limbic and sensorimotor subdivisions of subcortical brain structures have not been investigated in fatigued MS patients. In the proposed project, we will develop an automated algorithm which will parcellate the subcortical brain structures (striatum, thalamus, hippocampus and amygdala) into associative, limbic and sensorimotor subdivisions based on their axonal connections with associative, limbic and sensorimotor cortical areas in the hope that this method may provide a more robust investigation of subcortical pathology in MS patients with fatigue.

 

Objective

To define a Diffusion Tensor (DT) Tractography-based subcortical (striatal, thalamic, hippocampal and amygdalar) parcelation method in MS patients with fatigue.

 

Methodology

1. Define a method for parcellation of subcortical structures (striatum, thalamus, hippocampus and amygdala) into associative, limbic and sensorimotor divisions based on their axonal connections with associative, limbic and sensorimotor cortical areas using DT tractography.

2. Correlate volume and DT metrics (such as fractional anisotropy) of associative, limbic and sensorimotor subdivisions of striatum, thalamus, hippocampus and amygdala with fatigue in MS patients

 

Profile

  What skills do you need?

  • Programming skills in C++, Matlab, and python (javascript is a plus)
  • Image processing background. Knowledge of ITK, VTK is a plus.

 

  What skills you will acquire?

  • Improve presentation skills.
    • You will attend monthly, sometimes weekly, presentations from researchers of groups collaborating with us.
    • You will have to present to the group at least three times (first: project and objectives, fourth: advances, and last month: preparation for defense)
  • Team working
    • Expose your ideas within a multidisciplinary team
  • Data management
    • You will be exposed to different types of data, typically images (MRI mostly) and clinical data. You will learn the best practices to handle this information.
  • Networking
    • Being in a multidisciplinary team and linked to research groups all around the world you will enhance your networking skills.

 

  What you will learn?

  • Neuroscience
    • You will learn about brain morphology and physiology
  • Neuroimaging
    • You will understand the basics of MRI and how to interpret them, with emphasis on the grey matter and the white matter of the human brain.
    • You will handle structural MRIs, including T1-weighted, T2-weighted and Diffusion Tensor Images (DTI) and will understand the basic physics underneath these types of acquisitions.

 

Contact

  

Address

  • 1249 Boylston St, Boston 02215, Massachusetts, USA

 

References

1. Induruwa, I., C.S. Constantinescu, and B. Gran, Fatigue in multiple sclerosis - a brief review. J Neurol Sci, 2012. 323(1-2): p. 9-15.

2. Dobryakova, E., et al., Neural correlates of cognitive fatigue: cortico-striatal circuitry and effort-reward imbalance. J Int Neuropsychol Soc, 2013. 19(8): p. 849-53.

3. Gobbi, C., et al., Forceps minor damage and co-occurrence of depression and fatigue in multiple sclerosis. Mult Scler, 2014.

4. Rocca, M.A., et al., Regional but not global brain damage contributes to fatigue in multiple sclerosis. Radiology, 2014. 273(2): p. 511-20.

5. Feinstein, A., et al., The link between multiple sclerosis and depression. Nat Rev Neurol, 2014. 10(9): p. 507-17.

6. Marrie, R.A., et al., Differences in the burden of psychiatric comorbidity in MS vs the general population. Neurology, 2015. 85(22): p. 1972-9.

7. Marrie, R.A., et al., The incidence and prevalence of psychiatric disorders in multiple sclerosis: a systematic review. Mult Scler, 2015. 21(3): p. 305-17.

8. Wood, B., et al., Prevalence and concurrence of anxiety, depression and fatigue over time in multiple sclerosis. Mult Scler, 2013. 19(2): p. 217-24.

See also: Project