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Assessment of myelination is a core issue in paediatric neuroimaging and can be challenging, particularly in settings without dedicated paediatric neuroradiologists. Deep learning models have recently been shown to be able to estimate myelination age in children with normal MRI, but currently lack validation for patients with myelination delay and implementation including pre-processing suitable for local imaging is not trivial. Standardized myelination scores, which have been successfully used as biomarkers for myelination in hypomyelinating diseases, rely on visual, semiquantitative scoring of myelination on routine clinical MRI and may offer an easy-to-use alternative for assessment of myelination. Myelination was scored in 13 anatomic sites (items) on conventional T2w and T1w images in controls (n = 253, 0–2 years). Items for the score were selected based on inter-rater variability, practicability of scoring, and importance for correctly identifying validation scans. The resulting myelination score consisting of 7 T2- and 5 T1-items delineated myelination from term-equivalent to advanced, incomplete myelination which 50 % and 99 % of controls had reached by 19.1 and 32.7 months, respectively. It correctly identified 20/20 new control MRIs and 40/43 with myelination delay, missing one patient with borderline myelination delay at 8.6 months and 2 patients with incomplete T2-myelination of subcortical temporopolar white matter at 28 and 34 months. The proposed myelination score provides an easy to use, standardized, and versatile tool to delineate myelination normally occurring during the first 1.5 years of life. • Assessment of myelination as a core issue in paediatric neuroimaging, potentially challenging and observer-dependent. • Deep learning can estimate myelination age in normal MRI, but not yet validated for myelination delay, not trivial to implement. • Myelination scores: visual, semiquantitative scoring of myelination on routine MRIs, established for hypomyelination research. • Proposed myelination score: standardized, ready-to-go, easy-to-use for MRIs from different scanners and field strengths. [ABSTRACT FROM AUTHOR]

Voxel-based morphometry (VBM) has been used repeatedly in single-center studies to investigate regional gray matter (GM) atrophy in multiple sclerosis (MS). In multi-center trials, across-scanner variations might interfere with the detection of disease-specific structural abnormalities, thereby potentially limiting the use of VBM. Here we evaluated longitudinally inter-site differences and inter-site comparability of regional GM in MS using VBM. Baseline and follow up 3D T1-weighted magnetic resonance imaging (MRI) data of 248 relapsing-remitting (RR) MS patients, recruited in two clinical centers, (center1/2: n = 129/119; mean age 42.6 ± 10.7/43.3 ± 9.3; male:female 33:96/44:75; median disease duration 150 [72-222]/116 [60-156]) were acquired on two different 1.5T MR scanners. GM volume changes between baseline and year 2 while controlling for age, gender, disease duration, and global GM volume were analyzed. The main effect of time on regional GM volume was larger in data of center two as compared to center one in most of the brain regions. Differential effects of GM volume reductions occured in a number of GM regions of both hemispheres, in particular in the fronto-temporal and limbic cortex (cluster P corrected <0.05). Overall disease-related effects were found bilaterally in the cerebellum, uncus, inferior orbital gyrus, paracentral lobule, precuneus, inferior parietal lobule, and medial frontal gyrus (cluster P corrected <0.05). The differential effects were smaller as compared to the overall effects in these regions. These results suggest that the effects of different scanners on longitudinal GM volume differences were rather small and thus allow pooling of MR data and subsequent combined image analysis. Hum Brain Mapp, 2011. © 2011 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Background: Gender effects are strong in multiple sclerosis (MS), with male patients showing a worse clinical outcome than female patients. Functional reorganization of neural activity may contribute to limit disability, and possible gender differences in this process may have important clinical implications.Objectives: The aim of this study was to explore gender-related changes in functional connectivity and network efficiency in MS patients. Additionally, we explored the association of functional changes with cognitive function.Methods: Sixty subjects were included in the study, matched for age, education level and intelligence quotient (IQ). Male and female patients were matched for disability, disease duration and white matter lesion load. Two cognitive domains often impaired in MS, i.e. visuospatial memory and information processing speed, were evaluated in all subjects. Functional connectivity between brain regions and network efficiency was explored using resting-state functional magnetic resonance imaging and graph analysis. Differences in cognitive and functional characteristics between groups, and correlations with cognitive performance, were examined.Results: Male patients showed worse performance on cognitive tests than female and male controls, while female patients were cognitively normal. Decreases in functional connectivity and network efficiency, observed in male patients, correlated with reduced visuospatial memory (r = −0.6 and r = −0.5, respectively). In the control group, no cognitive differences were found between genders, despite differences in functional connectivity between healthy men and women.Conclusions: Functional connectivity differences were found in male patients only and were related to impaired visuospatial memory. These results underline the importance of gender in MS and require further investigation in larger and longitudinal studies. [ABSTRACT FROM AUTHOR]

Classical Galactosemia (CG) is an inherited disorder of galactose metabolism caused by a deficiency of the galactose-1-phosphate uridylyltransferase (GALT) enzyme resulting in neurocognitive complications. As in many Inborn Errors of Metabolism, the metabolic pathway of CG is well-defined, but the pathophysiology and high variability in clinical outcome are poorly understood. The aim of this study was to investigate structural changes of the brain of CG patients on MRI and their association with clinical outcome. In this prospective cohort study an MRI protocol was developed to evaluate gray matter (GM) and white matter (WM) volume of the cerebrum and cerebellum, WM hyperintensity volume, WM microstructure and myelin content with the use of conventional MRI techniques, diffusion tensor imaging (DTI) and quantitative T1 mapping. The association between several neuroimaging parameters and both neurological and intellectual outcome was investigated. Twenty-one patients with CG (median age 22 years, range 8–47) and 24 controls (median age 30, range 16–52) were included. Compared to controls, the WM of CG patients was lower in volume and the microstructure of WM was impaired both in the whole brain and corticospinal tract (CST) and the lower R1 values of WM, GM and the CST were indicative of less myelin. The volume of WM lesions were comparable between patients and controls. The 9/16 patients with a poor neurological outcome (defined as the presence of a tremor and/or dystonia), demonstrated a lower WM volume, an impaired WM microstructure and lower R1 values of the WM indicative of less myelin content compared to 7/16 patients without movement disorders. In 15/21 patients with a poor intellectual outcome (defined as an IQ < 85) both GM and WM were affected with a lower cerebral and cerebellar WM and GM volume compared to 6/21 patients with an IQ ≥ 85. Both the severity of the tremor (as indicated by the Tremor Rating Scale) and IQ (as continuous measure) were associated with several neuroimaging parameters such as GM volume, WM volume, CSF volume, WM microstructure parameters and R1 values of GM and WM. In this explorative study performed in patients with Classical Galactosemia, not only WM but also GM pathology was found, with more severe brain abnormalities on MRI in patients with a poor neurological and intellectual outcome. The finding that structural changes of the brain were associated with the severity of long-term complications indicates that quantitative MRI techniques could be of use to explain neurological and cognitive dysfunction as part of the disease spectrum. Based on the clinical outcome of patients, the absence of widespread WM lesions and the finding that both GM and WM are affected, CG could be primarily a GM disease with secondary damage to the WM as a result of neuronal degeneration. To investigate this further the course of GM and WM should be evaluated in longitudinal research, which could also clarify if CG is a neurodegenerative disease. [ABSTRACT FROM AUTHOR]