BACKGROUND: Fatigue is one of the most frequent symptoms suffered by patients affected by multiple sclerosis. The patho-physiological basis of multiple sclerosis-related fatigue remains to be elucidated. OBJECTIVE: Our aim was to investigate whether a particular pattern of deep and/or cortical grey matter atrophy is associated with fatigue in patients with multiple sclerosis. METHODS: A total of 152 patients with relapsing-remitting multiple sclerosis were evaluated with the Expanded Disability Status Scale, the Fatigue Severity Status Scale (FSS), the Modified Fatigue Impact Scale and the Beck Depression Inventory. The thalamic and basal ganglia volume and the regional cortical thickness were analysed by means of FreeSurfer. RESULTS: Based on Fatigue Severity Status Scale score, patients were divided into fatigued (FSS ≥ 4, 71 patients, 46.6%) and non-fatigued (FSS < 4, 81 patients, 53.4%). A significant atrophy of striatum, thalamus, superior frontal gyrus and inferior parietal gyrus was observed in fatigued patients compared with non-fatigued patients. The cognitive domain of Modified Fatigue Impact Scale significantly correlated with the volume of the striatum and with the cortical thickness of the posterior parietal cortex and middle frontal gyrus (R = 0.51-0.61), while the physical domain of Modified Fatigue Impact Scale significantly correlated with striatum volume and superior frontal gyrus cortical thickness (R = 0.50-0.54). CONCLUSIONS: The regional analysis of deep and cortical grey matter atrophy suggests an association between the neurodegenerative process taking place in the striatum-thalamus-frontal cortex pathway and the development of fatigue in relapsing-remitting multiple sclerosis. The inclusion of the posterior parietal cortex as one of the best predictors of the Modified Fatigue Impact Scale cognitive domain suggests the major role of the posterior attentional system in determining cognitive fatigue in relapsing-remitting multiple sclerosis.
BACKGROUND:Fatigue is one of the most frequent symptoms suffered by patients affected by multiple sclerosis. The patho-physiological basis of multiple sclerosis-related fatigue remains to be elucidated. OBJECTIVE: Our aim was to investigate whether a particular pattern of deep and/or cortical grey matter atrophy is associated with fatigue in patients with multiple sclerosis. METHODS: A total of 152 patients with relapsing-remitting multiple sclerosis were evaluated with the Expanded Disability Status Scale, the Fatigue Severity Status Scale (FSS), the Modified Fatigue Impact Scale and the Beck Depression Inventory. The thalamic and basal ganglia volume and the regional cortical thickness were analysed by means of FreeSurfer. RESULTS: Based on Fatigue Severity Status Scale score, patients were divided into fatigued (FSS ≥ 4, 71 patients, 46.6%) and non-fatigued (FSS < 4, 81 patients, 53.4%). A significant atrophy of striatum, thalamus, superior frontal gyrus and inferior parietal gyrus was observed in fatigued patients compared with non-fatigued patients. The cognitive domain of Modified Fatigue Impact Scale significantly correlated with the volume of the striatum and with the cortical thickness of the posterior parietal cortex and middle frontal gyrus (R = 0.51-0.61), while the physical domain of Modified Fatigue Impact Scale significantly correlated with striatum volume and superior frontal gyrus cortical thickness (R = 0.50-0.54). CONCLUSIONS: The regional analysis of deep and cortical grey matter atrophy suggests an association between the neurodegenerative process taking place in the striatum-thalamus-frontal cortex pathway and the development of fatigue in relapsing-remitting multiple sclerosis. The inclusion of the posterior parietal cortex as one of the best predictors of the Modified Fatigue Impact Scale cognitive domain suggests the major role of the posterior attentional system in determining cognitive fatigue in relapsing-remitting multiple sclerosis.
Authors: I Specogna; F Casagrande; A Lorusso; M Catalan; A Gorian; L Zugna; R Longo; M Zorzon; M Naccarato; G Pizzolato; M Ukmar; M A Cova Journal: Radiol Med Date: 2012-06-22 Impact factor: 3.469
Authors: A Vidal-Jordana; D Pareto; J Sastre-Garriga; C Auger; E Ciampi; X Montalban; A Rovira Journal: AJNR Am J Neuroradiol Date: 2016-11-24 Impact factor: 3.825