Longitudinal associations between brain structural changes and fatigue in early MS

The neural basis of fatigue in multiple sclerosis

“…32 Studies are inconsistent regarding the association between fatigue and total measures of lesion load and atrophy in MS. Two studies reported an association between fatigue and higher T1 and T2 lesion load 3,4 and in one of these studies the authors also found an association between lower white matter and gray matter fraction and fatigue in MS. 3 However, several other studies did not find any association between these fractions and fatigue, which is in line with our results. 6,9,11,13,32 Possible explanations for these discrepancies include differences in patients' clinical characteristics (disease duration, concomitant presence of depression and cognitive impairment); use of different fatigue scales and sample sizes; sensitivity of the technique applied to different substrates of MS pathology; and methods used for the analysis (e.g., global vs regional assessment). 11 Regarding the contribution of GM pathology to fatigue in MS, previous studies have suggested that the main contributor is multiregional damage rather than global brain damage.…”

“…2 Although the clinical aspects of fatigue are well-recognized, its pathophysiologic mechanisms remain incompletely understood. Neuroimaging studies have yielded divergent results regarding a correlation between fatigue severity and MRI lesion load, [3][4][5][6] number and volume of gadolinium-enhancing lesions, 7 brain atrophy measurements, 3,8,9 and diffuse damage to the normalappearing brain tissues. 10,11 Interestingly, several works have succeeded in establishing a link between fatigue and cortico-subcortical disconnection.…”

Fatigue in multiple sclerosis – Insights into evaluation and management

“…In the field of MS, some authors evaluated the role of gray and white matter abnormalities, such as lesion load and brain atrophy, in the development of fatigue. While some authors have established a positive correlation [126,220,224], the remaining majority failed to do so [7,13,35,74,120,149,153,233]. Such negative findings might be due to the fact that the symptom seems to arise from regional abnormalities rather than global brain pathology.…”

“…This has led to identifying specific pathologies within the frontal and parietal cortices [13,43,88,160,175,178], thalami and basal ganglia [13,89,145,149,225], among others. More interestingly, several MS fatigue networks have been described: the fronto-striatal network [157,179,209], the parieto-striatal network [37], the cortico-cortical network mainly involving fronto-frontal and fronto-parietal regions [13,157,169,202,221] and an interhemispheric network consisting of the corpus callosum and its radiating fibers [13,75,178,244,245].…”

The ANTs Longitudinal Cortical Thickness Pipeline

“…In [12,19], the authors motivated the design and implementation of the longitudinal FreeSurfer variant inspired by these earlier insights and the overarching general principle of "treat[ing] all time points exactly the same." It has since been augmented by integrated linear mixed effects modeling capabilities [20] and has been used in a variety of studies including pediatric cortical development [21], differential development in Alzheimer's disease and fronto-temporal dementia [22], and fatigue in the context of multiple sclerosis [23]. Although the FreeSurfer longitudinal processing stream is perhaps one of the most well-known, other important longitudinal-specific methodologies have been proposed for characterizing cortical morphological change.…”