Cognitive Fatigue in Multiple Sclerosis Associated with Brain Iron Concentration
Poster No:
250
Submission Type:
Abstract Submission
Authors:
Bing Yao1, Mateusz Kowalczyk1, Hannah Ovadia1, Sarah Wood1
Institutions:
1Kessler Foundation, West Orange, NJ
First Author:
Co-Author(s):
Introduction:
Fatigue, defined as an overwhelming feeling of lack of both mental and physical energy, has been reported in over 90% of individuals with multiple sclerosis (MS) [1]. Studies have shown basal ganglia structures play a central role in fatigue [2]. Meanwhile, abnormal iron deposition has been observed in the deep gray matter structures including basal ganglia in MS [3]. In this study, we aimed to examine the correlation between brain iron concentration indicated by susceptibility contrast imaging and the severity of fatigue in MS.
Methods:
Data from ten clinically definite MS patients (F/M = 8/2, age = 56.0±8.3 y/o) and ten healthy controls (F/M = 5/4, age = 37.5±12.5 y/o) were reported in this study. MRI: A 3D multi-echo gradient-echo acquisition was performed on a 3T Siemens Skyra scanner with a standard 20-ch head/neck coil. The parameters were as following: TE = 8.49/16.86/25.23/33.60/41.97 ms, TR = 49 ms, resolution = 0.9×0.9×2 mm2, flip angle= 20°, bandwidth= ±38.4 kHz. A total of 52 axial slices were acquired to cover the whole brain. A GRAPPA of 2 was used to shorten the scan time down to 5 minutes. Quantitative R2* maps were derived from exponential fitting over the 5 echo data. The Laplacian algorithm was used to unwrap the raw phase and remove the phase background. The susceptibility maps were then calculated using the LSQR algorithm based on the unwrapped phase maps and averaged over three echo data (25.23, 33.60 and 41.97 ms) [4]. Six regions of interest (ROIs) including substantia nigra (SN), red nucleus (RN), globus pallidus (GP), putamen (PU), caudate nucleus (CN), and thalamus (TH) were mapped on the magnitude images. A registered MP-RAGE image was used as an additional reference for the ROI drawing. Each ROI was drawn on multiple successive images to almost entirely cover each structure. R2*, and susceptibility values were averaged in each ROI, respectively, and then averaged across all the subjects in the group. Fatigue measures: Each individual was administrated a Fatigue Severity Scale (FSS) test and a Modified Fatigue Impact Scale (MFIS) test to measure their fatigue levels. The FSS scores and total MFIS scores with its subcategories (Physical, Cognitive, Psychosocial) subscales from each individual were correlated with R2*, Frequency shift and QSM values in all ROIs.
Results:
Two representative axial slices of the MR images containing the ROI regions from one MS patient are shown in Fig. 1. The SN, RN, GP, PU, and CN are readily identifiable in the magnitude, and R2*, frequency and QSM maps. Comparing to the magnitude and R2* maps, these iron-rich structures are clearly visible and distinguishable with clear boundaries in the QSM. Fig. 2 shows A comparison of the R2* and susceptibility values between MS patients (MS) and healthy controls (HC) in different brain regions. Significant positive correlations between Frequency and FSS Total, MFIS Total, MFIS Physical subscale and MFIS Psychosocial subscale are found in CN. QSM also correlates with MFIS Total and MFIS Physical subscales significantly. Based on the data from ten subjects, no significant consistent positive correlations in the other ROIs are found. No significant correlations between R2* and all fatigue measures are observed.
Conclusions:
Our findings on the correlation between iron deposition measured by MR susceptibility contrast imaging and severity of fatigue is of particular interesting to understanding the fatigue mechanisms, which may lead to an effective treatment on reducing clinical symptoms in MS patients.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
Image Registration and Computational Anatomy 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures
Novel Imaging Acquisition Methods:
Anatomical MRI
Keywords:
Basal Ganglia
Cognition
Degenerative Disease
Demyelinating
Sub-Cortical
Thalamus
1|2Indicates the priority used for review
Provide references using author date format
2. Chaudhuri A. (2000), ‘Fatigue and basal ganglia’. Journal of the Neurological Sciences. Vol 179(1-2):34–42.
3. Yao, B. (2015), ‘Detecting Iron Deposition In Multiple Sclerosis Using Susceptibility Contrast Imaging’. Proceeding of the International Society for Magnetic Resonance in Medicine vol 23.
4. Li W. (2011), ‘Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition’, NeuroImage. vol 15;55:1645.
5. Dobryakova E. (2013), ‘Neural correlates of cognitive fatigue: cortico-striatal circuitry and effort-reward imbalance’. Journal of the International Neuropsychological Society. Vol 19(8):849–53.