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The article examines functional network integrity in multiple sclerosis (MS) and relate this to cognitive dysfunction and physical disability in MS patients. It is said that the quality of life is hugely influenced by cognitive dysfunction in MS. The study included 128 MS patients and 50 controls on whom resting state fMRI scans were done.

Background and objectives: Disability and cognitive impairment are known to be related to brain atrophy in multiple sclerosis (MS), but 3D-T1 imaging required for brain volumetrics is often unavailable in clinical protocols, unlike 3D-FLAIR. Here our aim was to investigate whether brain volumes derived from 3D-FLAIR images result in similar associations with disability and cognition in MS as do those derived from 3D-T1 images. Methods: 3T-MRI scans of 329 MS patients and 76 healthy controls were included in this cross-sectional study. Brain volumes were derived using FreeSurfer on 3D-T1 and compared with brain volumes derived with SynthSeg and SAMSEG on 3D-FLAIR. Relative agreement was evaluated by calculating the intraclass correlation coefficient (ICC) of the 3D-T1 and 3D-FLAIR volumes. Consistency of relations with disability and average cognition was assessed using linear regression, while correcting for age and sex. The findings were corroborated in an independent validation cohort of 125 MS patients. Results: The ICC between volume measured with FreeSurfer and those measured on 3D-FLAIR for brain, ventricle, cortex, total deep gray matter and thalamus was above 0.74 for SAMSEG and above 0.91 for SynthSeg. Worse disability and lower average cognition were similarly associated with brain (adj. R2 = 0.24–0.27, p < 0.01; adj. R2 = 0.26–0.29, p < 0.001) ventricle (adj. R2 = 0.27–0.28, p < 0.001; adj. R2 = 0.19–0.20, p < 0.001) and deep gray matter volumes (adj. R2 = 0.24–0.28, p < 0.001; adj. R2 = 0.27–0.28, p < 0.001) determined with all methods, except for cortical volumes derived from 3D-FLAIR. Discussion: In this cross-sectional study, brain volumes derived from 3D-FLAIR and 3D-T1 show similar relationships to disability and cognitive dysfunction in MS, highlighting the potential of these techniques in clinical datasets. [ABSTRACT FROM AUTHOR]

The aim of the current study was to assess the structural centrality and microstructural integrity of the cortical hubs of the salience network, the anterior insular cortex (AIC) subregions and anterior cingulate cortex (ACC), and their relationship to cognitive and affective impairment in PD. MRI of 53 PD patients and 15 age-matched controls included 3D-T1 for anatomical registration, and diffusion tensor imaging for probabilistic tractography. Network topological measures of eigenvector and betweenness centrality were calculated for ventral (vAI) and dorsal (dAI) AIC. Microstructural tract integrity between vAI, dAI and the ACC was quantified with fractional anisotrophy (FA) and mean diffusivity (MD). Structural integrity and connectivity were related to cognitive and affective scores. The dAI had significantly higher eigenvector centrality in PD than controls (p < 0.01), associated with higher depression scores (left dAI only, rs = 0.28, p < 0.05). Tracts between dAI and ACC showed lower FA and higher MD in PD (p < 0.05), and associated with lower semantic fluency, working memory and executive functioning, and higher anxiety scores (range 0.002 < p < 0.05). This study provides evidence for clinically relevant structural damage to the cortical hubs of the salience network in PD, possibly due to extensive local neuropathology and loss of interconnecting AIC-ACC tracts. [ABSTRACT FROM AUTHOR]

Background and purpose: To predict disability and cognition in multiple sclerosis (MS) after 6 and 12 years, using early clinical and imaging measures. Methods: A total of 115 patients with MS were selected and followed up after 2 and 6 years, with 79 patients also being followed up after 12 years. Disability was measured using the Expanded Disability Status Scale (EDSS); cognition was measured only at follow‐up using neuropsychological testing. Predictors of interest included EDSS score, baseline brain and lesion volumes and their changes over 2 years, baseline age, clinical phenotype, sex and educational level. Results: Higher 6‐year EDSS score was predicted by early EDSS score and whole‐brain volume changes and baseline diagnosis of primary progressive MS (adjusted R2 = 0.56). Predictors for 12‐year EDSS score included larger EDSS score changes and higher T1‐hypointense lesion volumes (adjusted R2 = 0.38). Year 6 cognition was predicted by primary progressive MS phenotype, lower educational level, male sex and early whole‐brain atrophy (adjusted R2 = 0.26); year 12 predictors included male sex, lower educational level and higher baseline T1‐hypointense lesion volumes (adjusted R2 = 0.14). Conclusions: Patients with early signs of neurodegeneration and a progressive disease onset were more prone to develop both disability progression and cognitive dysfunction. Male sex and lower educational level only affected cognitive dysfunction, which remains difficult to predict and probably needs more advanced imaging measures. [ABSTRACT FROM AUTHOR]