Cortical thickness and surface area relate to specific symptoms in early relapsing–remitting multiple sclerosis

Nygaard, Gro Owren; Walhovd, Kristine B.; Sowa, Piotr; Chepkoech, Joy‐Loi; Bjørnerud, Atle; Due‐Tønnessen, Paulina; Landrø, Nils Inge; Damangir, Soheil; Spulber, Gabriela; Storsve, Andreas Berg; Beyer, Mona K.; Fjell, Anders M.; Celius, Elisabeth G; Harbo, Hanne F.

doi:10.1177/1352458514543811

Cited by 78 publications

(89 citation statements)

References 265 publications

(420 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…thalamus, caudate, and pallidum) (Cifelli et al 2002;Filippi and Agosta 2010;Vercellino et al 2009). Disability has been linked specifically to cortical thinning in the frontal (including anterior cingulate gyrus) and temporal lobes (for EDSS) (Charil et al 2007;Nygaard et al 2015), occipital region (for visual Functional System Scores) (Calabrese et al 2007) as well as grey matter loss in the striatum (for Fatigue Severity Status Scale) (Calabrese et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Combined structural and functional patterns discriminating upper limb motor disability in multiple sclerosis using multivariate approaches

Zhong

Chen

Nantes

et al. 2016

Brain Imaging and Behavior

View full text Add to dashboard Cite

A structural or functional pattern of neuroplasticity that could systematically discriminate between people with impaired and preserved motor performance could help us to understand the brain networks contributing to preservation or compensation of behavior in multiple sclerosis (MS). This study aimed to (1) investigate whether a machine learning-based technique could accurately classify MS participants into groups defined by upper extremity function (i.e. motor function preserved (MP) vs. motor function impaired (MI)) based on their regional grey matter measures (GMM, cortical thickness and deep grey matter volume) and inter-regional functional connection (FC), (2) investigate which features (GMM, FC, or GMM + FC) could classify groups more accurately, and (3) identify the multivariate patterns of GMM and FCs that are most discriminative between MP and MI participants, and between each of these groups and the healthy controls (HCs). With 26 MP, 25 MI, and 21 HCs (age and sex matched) underwent T1-weighted and resting-state functional MRI at 3 T, we applied support vector machine (SVM) based classification to learn discriminant functions indicating regions in which GMM or between which FCs were most discriminative between groups. This study demonstrates that there exist structural and FC patterns sufficient for correct classification of upper limb motor ability of people with MS. The classifier with GMM + FC features yielded the highest accuracy of 85.61 % (p < 0.001) to distinguish between the MS groups using leave-one-out cross-validation. It suggests that a machine-learning approach combining structural and functional features is useful for identifying the specific neural substrates that are necessary and sufficient to preserve motor function among people with MS.

show abstract

Section: Introductionmentioning

confidence: 99%

Combined structural and functional patterns discriminating upper limb motor disability in multiple sclerosis using multivariate approaches

Zhong

Chen

Nantes

et al. 2016

Brain Imaging and Behavior

View full text Add to dashboard Cite

show abstract

“…However, there is considerable evidence that both normal appearing white matter (Kutzelnigg et al 2005;Bodini et al 2009) and gray matter (De Stefano et al 2003;Sailer et al 2003;Ceccarelli et al 2008) may be affected in early RRMS patients, and associated with specific symptoms, like cognition and fatigue (Sepulcre et al 2009;Nygaard et al 2014). Cerebellar pathology is also related to eye movements disorders, as recently shown in a study of antisaccades and cognition in early MS patients (Kolbe et al 2014 …”

Section: Discussionmentioning

confidence: 94%

“…They also underwent a thorough neuropsychological assessment (Nygaard et al 2014). Results of the auditory 3 seconds' version of the Paced Auditory Serial Addition Test (PASAT) (Gronwall 1977) performed by the patients, and wSDMT (Smith Aron 1982) performed by all participants, are reported.…”

Section: Clinical Evaluationmentioning

confidence: 99%

“…White matter lesion load (WMLL) was estimated from FLAIR and MPRAGE sequences, using the Cascade software, previously applied to an overlapping MS sample (ki.se/en/nvs/cascade) (Damangir et al 2012;Nygaard et al 2014). A subset of the patients (n=32) were examined by a trained neuroradiologist (PS) and rated according to the presence of white matter lesions (WML) of the brainstem.…”

Section: Clinical Evaluationmentioning

confidence: 99%

See 1 more Smart Citation

Eye and hand motor interactions with the Symbol Digit Modalities Test in early multiple sclerosis

Nygaard

Benavent

Harbo

et al. 2015

Multiple Sclerosis and Related Disorders

Self Cite

View full text Add to dashboard Cite

show abstract

“…Structural imaging studies focusing on the quantification of atrophy have reported an association of fatigue severity with atrophy in the thalamus and a number of different cortical gray matter regions (superior frontal and inferior parietal gyrus, parietal lobe) in patients with relapsing-remitting MS [90, 91]. Yaldizli et al found an association between callosal atrophy and fatigue and cognitive performance in a large cohort of MS patients with various disease courses [92], and Nygaard et al reported a relation between regionally smaller cortical surface areas and volumes and higher depression and fatigue scores in relapsing-remitting MS patients [93]. Although Gobbi et al did not find an association between white matter atrophy and lesion distribution [94], a previous study by Sepulcre et al suggested a correlation between T2 lesion load and fatigue severity and between fatigue scores and gray matter atrophy in frontal regions [95].…”

Section: Clinical Correlates and Biological Mechanismsmentioning

confidence: 99%

The Berlin Treatment Algorithm: recommendations for tailored innovative therapeutic strategies for multiple sclerosis-related fatigue

et al. 2016

View full text Add to dashboard Cite

More than 80% of multiple sclerosis (MS) patients suffer from fatigue. Despite this, there are few therapeutic options and evidence-based pharmacological treatments are lacking. The associated societal burden is substantial (MS fatigue is a major reason for part-time employment or early retirement), and at least one out of four MS patients view fatigue as the most burdensome symptom of their disease. The mechanisms underlying MS-related fatigue are poorly understood, and objective criteria for distinguishing and evaluating levels of fatigue and tiredness have not yet been developed. A further complication is that both symptoms may also be unspecific indicators of many other diseases (including depression, sleep disorders, anemia, renal failure, liver diseases, chronic obstructive pulmonary disease, drug side effects, recent MS relapses, infections, nocturia, cancer, thyroid hypofunction, lack of physical exercise). This paper reviews current treatment options of MS-related fatigue in order to establish an individualized therapeutic strategy that factors in existing comorbid disorders. To ensure that such a strategy can also be easily and widely implemented, a comprehensive approach is needed, which ideally takes into account all other possible causes and which is moreover cost efficient. Using a diagnostic interview, depressive disorders, sleep disorders and side effects of the medication should be identified and addressed. All MS patients suffering from fatigue should fill out the Modified Fatigue Impact Scale, Epworth Sleepiness Scale, the Beck Depression Inventory (or a similar depression scale), and the Pittsburgh Sleep Quality Index (or the Insomnia Severity Index). In some patients, polygraphic or polysomnographic investigations should be performed. The treatment of underlying sleep disorders, drug therapy with alfacalcidol or fampridine, exercise therapy, and cognitive behavioral therapy-based interventions may be effective against MS-related fatigue. The objectives of this article are to identify the reasons for fatigue in patients suffering from multiple sclerosis and to introduce individually tailored treatment approaches. Moreover, this paper focuses on current knowledge about MS-related fatigue in relation to brain atrophy and lesions, cognition, disease course, and other findings in an attempt to identify future research directions.

show abstract

Cortical thickness and surface area relate to specific symptoms in early relapsing–remitting multiple sclerosis

Abstract: We found that cortical thickness, but not cortical surface area, is affected in early RRMS. We identified specific structural correlates to the main clinical symptoms in early RRMS.

Cited by 78 publications

References 265 publications

Combined structural and functional patterns discriminating upper limb motor disability in multiple sclerosis using multivariate approaches

Combined structural and functional patterns discriminating upper limb motor disability in multiple sclerosis using multivariate approaches

Eye and hand motor interactions with the Symbol Digit Modalities Test in early multiple sclerosis

The Berlin Treatment Algorithm: recommendations for tailored innovative therapeutic strategies for multiple sclerosis-related fatigue

Contact Info

Product

Resources

About