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Abstract Filtering efficiency (FE) has been suggested as a task-related process of working memory (WM) in older adults, but the interaction of distractors with WM when implemented as a training to improve WM capacity is unclear. To investigate the effect of manipulations of WM and/or FE load in a multicomponent model-based WM training in improving WM capacity. 205 healthy older adults (129 women; aged 64.0 ± 8.3 years) were randomised into three WM training groups with manipulations of WM and FE load (high WM; low FE load, high WM; high FE load and low WM; high FE load). All groups underwent three online cognitive testing sessions and twelve 40-min training sessions over three weeks using the SmartBrain smartphone application. WM capacity was measured with complex span tasks and FE using the Change Detection Task. Linear mixed-effect models adjusted for age, sex, education and pre-baseline performance showed increased WM capacity post-training, but no difference between groups. While both distractors and WM are needed to improve WM in the absence of distraction, manipulations of the FE and WM load do not influence improvements following training.

Traditional Diffusion Tensor Imaging (DTI) metrics are affected by crossing fibers and lesions. Most of the previous tractometry works use the single diffusion tensor, which leads to limited sensitivity and challenging interpretation of the results in crossing fiber regions. In this work, we propose a tractometry pipeline that combines white matter tractography with multi-tensor fixel-based metrics. These multi-tensors are estimated using the stable, accurate and robust to noise Multi-Resolution Discrete Search method (MRDS). The spatial coherence of the multi-tensor field estimated with MRDS, which includes up to three anisotropic and one isotropic tensors, is tractography-regularized using the Track Orientation Density Imaging method. Our end-to-end tractometry pipeline goes from raw data to track-specific multi-tensor-metrics tract profiles that are robust to noise and crossing fibers. A comprehensive evaluation conducted in a phantom simulating healthy and damaged tissue with the standard model, as well as in a healthy cohort of 20 individuals scanned along 5 time points, demonstrates the advantages of using multi-tensor metrics over traditional single-tensor metrics in tractometry. Qualitative assessment in a cohort of patients with relapsing-remitting multiple sclerosis reveals that the pipeline effectively detects white matter anomalies in the presence of crossing fibers and lesions.

Abstract Pathological data showed focal inflammation and regions of diffuse neuronal loss in the cortex of people with multiple sclerosis (MS). In this work, we applied a novel model (“soma and neurite density imaging (SANDI)”) to multishell diffusion-weighted MRI data acquired in healthy subjects and people with multiple sclerosis (pwMS), in order to investigate inflammation and degeneration-related changes in the cortical tissue of pwMS. We aimed to (i) establish whether SANDI is applicable in vivo clinical data; (ii) investigate inflammatory and degenerative changes using SANDI soma fraction (f soma )—a marker of cellularity—in both cortical lesions and in the normal-appearing-cortex and (iii) correlate SANDI f soma with clinical and biological measures in pwMS. We applied a simplified version of SANDI to a clinical scanners. We then provided evidence that pwMS exhibited an overall decrease in cortical SANDI f soma compared to healthy subjects, suggesting global degenerative processes compatible with neuronal loss. On the other hand, we have found that progressive pwMS showed a higher SANDI f soma in the outer part of the cortex compared to relapsing–remitting pwMS, possibly supporting current pathological knowledge of increased innate inflammatory cells in these regions. A similar finding was obtained in subpial lesions in relapsing–remitting patients, reflecting existing pathological data in these lesion types. A significant correlation was found between SANDI f soma and serum neurofilament light chain—a biomarker of inflammatory axonal damage—suggesting a relationship between SANDI soma fraction and inflammatory processes in pwMS again. Overall, our data show that SANDI f soma is a promising biomarker to monitor changes in cellularity compatible with neurodegeneration and neuroinflammation in the cortex of MS patients.

IntroductionMulti-shell diffusion Magnetic Resonance Imaging (dMRI) data has been widely used to characterise white matter microstructure in several neurodegenerative diseases. The lack of standardised dMRI protocols often implies the acquisition of redundant measurements, resulting in prolonged acquisition times. In this study, we investigate the impact of the number of gradient directions on Diffusion Tensor Imaging (DTI) and on Neurite Orientation Dispersion and Density Imaging (NODDI) metrics.MethodsData from 124 healthy controls collected in three different longitudinal studies were included. Using an in-house algorithm, we reduced the number of gradient directions in each data shell. We estimated DTI and NODDI measures on six white matter bundles clinically relevant for neurodegenerative diseases.ResultsFractional Anisotropy (FA) measures on bundles where data were sampled at the 30% rate, showed a median L1 distance of up to 3.92% and a 95% CI of (1.74, 8.97)% when compared to those obtained at reference sampling. Mean Diffusivity (MD) reached up to 4.31% and a 95% CI of (1.60, 16.98)% on the same premises. At a sampling rate of 50%, we obtained a median of 3.90% and a 95% CI of (1.99, 16.65)% in FA, and 5.49% with a 95% CI of (2.14, 21.68)% in MD. The Intra-Cellular volume fraction (ICvf) median L1 distance was up to 2.83% with a 95% CI of (1.98, 4.82)% at a 30% sampling rate and 3.95% with a 95% CI of (2.39, 7.81)% at a 50% sampling rate. The volume difference of the reconstructed white matter at reference and 50% sampling reached a maximum of (2.09 ± 0.81)%.DiscussionIn conclusion, DTI and NODDI measures reported at reference sampling were comparable to those obtained when the number of dMRI volumes was reduced by up to 30%. Close to reference DTI and NODDI metrics were estimated with a significant reduction in acquisition time using three shells, respectively with: 4 directions at a b value of 700 s/mm2, 14 at 1000 s/mm2, and 32 at 2000 s/mm2. The study revealed aspects that can be important for large-scale clinical studies on bundle-specific diffusion MRI.

White matter bundle segmentation is a cornerstone of modern tractography to study the brain’s structural connectivity in domains such as neurological disorders, neurosurgery, and aging. In this study, we present FIESTA (FIbEr Segmentation in Tractography using Autoencoders), a reliable and robust, fully automated, and easily semi-automatically calibrated pipeline based on deep autoencoders that can dissect and fully populate white matter bundles. This pipeline is built upon previous works that demonstrated how autoencoders can be used successfully for streamline filtering, bundle segmentation, and streamline generation in tractography. Our proposed method improves bundle segmentation coverage by recovering hard-to-track bundles with generative sampling through the latent space seeding of the subject bundle and the atlas bundle. A latent space of streamlines is learned using autoencoder-based modeling combined with contrastive learning. Using an atlas of bundles in standard space (MNI), our proposed method segments new tractograms using the autoencoder latent distance between each tractogram streamline and its closest neighbor bundle in the atlas of bundles. Intra-subject bundle reliability is improved by recovering hard-to-track streamlines, using the autoencoder to generate new streamlines that increase the spatial coverage of each bundle while remaining anatomically correct. Results show that our method is more reliable than state-of-the-art automated virtual dissection methods such as RecoBundles, RecoBundlesX, TractSeg, White Matter Analysis and XTRACT. Our framework allows for the transition from one anatomical bundle definition to another with marginal calibration efforts. Overall, these results show that our framework improves the practicality and usability of current state-of-the-art bundle segmentation framework

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius of axons in the human brain is challenging. Most axons in the brain have a radius below one micrometer, which falls below the sensitivity limit of dMRI signals even when using the most advanced human MRI scanners. Therefore, new MRI methods that are sensitive to small axon radii are needed. In this proof-of-concept investigation, we examine whether a surface-based axonal relaxation process could mediate a relationship between intra-axonal T2 and T1 times and inner axon radius, as measured using postmortem histology. A unique in vivo human diffusion-T1-T2 relaxation dataset was acquired on a 3T MRI scanner with ultra-strong diffusion gradients, using a strong diffusion-weighting (i.e., b = 6,000 s/mm2) and multiple inversion and echo times. A second reduced diffusion-T2 dataset was collected at various echo times to evaluate the model further. The intra-axonal relaxation times were estimated by fitting a diffusion-relaxation model to the orientation-averaged spherical mean signals. Our analysis revealed that the proposed surface-based relaxation model effectively explains the relationship between the estimated relaxation times and the histological axon radius measured in various corpus callosum regions. Using these histological values, we developed a novel calibration approach to predict axon radius in other areas of the corpus callosum. Notably, the predicted radii and those determined from histological measurements were in close agreement.

Measurement(s) brain connectivity measurement Technology Type(s) Fiber tracking

Abstract Although shared behavioral and neural mechanisms between working memory (WM) and motor sequence learning (MSL) have been suggested, the additive and interactive effects of training have not been studied. This study aimed at investigating changes in brain functional connectivity (FC) induced by sequential (WM + MSL and MSL + WM) and combined (WM × MSL) training programs. 54 healthy subjects (27 women; mean age: 30.2 ± 8.6 years) allocated to three training groups underwent twenty-four 40-min training sessions over 6 weeks and four cognitive assessments including functional MRI. A double-baseline approach was applied to account for practice effects. Test performances were compared using linear mixed-effects models and t-tests. Resting state fMRI data were analysed using FSL. Processing speed, verbal WM and manual dexterity increased following training in all groups. MSL + WM training led to additive effects in processing speed and verbal WM. Increased FC was found after training in a network including the right angular gyrus, left superior temporal sulcus, right superior parietal gyrus, bilateral middle temporal gyri and left precentral gyrus. No difference in FC was found between double baselines. Results indicate distinct patterns of resting state FC modulation related to sequential and combined WM and MSL training suggesting a relevance of the order of training performance. These observations could provide new insight for the planning of effective training/rehabilitation.

It is currently unknown how quantitative diffusion and myelin MRI designs affect the results of a longitudinal study. We used two independent datasets containing 6 monthly MRI measurements from 20 healthy controls and 20 relapsing-remitting multiple sclerosis (RR-MS) patients. Six designs were tested, including 3 MRI acquisitions, either over 6 months or over a shorter study duration, with balanced (same interval) or unbalanced (different interval) time intervals between MRI acquisitions. First, we show that in RR-MS patients, the brain changes over time obtained with 3 MRI acquisitions were similar to those observed with 5 MRI acquisitions and that designs with an unbalanced time interval showed the highest similarity, regardless of study duration. No significant brain changes were found in the healthy controls over the same periods. Second, the study duration affects the sample size in the RR-MS dataset; a longer study requires more subjects and vice versa. Third, the number of follow-up acquisitions and study duration affect the sensitivity and specificity of the associations with clinical parameters, and these depend on the white matter bundle and MRI measure considered. Together, this suggests that the optimal design depends on the assumption of the dynamics of change in the target population and the accuracy required to capture these dynamics. Thus, this work provides a better understanding of key factors to consider in a longitudinal study and provides clues for better strategies in clinical trial design.

Abstract Background Rett syndrome (RS) is a severe neurodevelopmental disorder for which there is no approved therapy. This study aimed to assess safety and efficacy of oral fingolimod in children with RS using a pre-post and case–control design. Methods At the University of Basel Children’s Hospital, Basel, Switzerland, children with RS were included if they were older than 6 years and met the established diagnostic criteria of RS, including a positive MeCP2 mutation. Participants were observed 6 months before and after treatment and received 12 months of fingolimod treatment. Serum samples of 50 children without RS served as reference for brain-derived neurotrophic factor (BDNF) measurements. Primary outcome measures were safety and efficacy, the latter measured by change in levels of BDNF in serum/CSF (cerebrospinal fluid) and change in deep gray matter volumes measured by magnetic resonance imaging (MRI). Secondary outcome measure was efficacy measured by change in clinical scores [Vineland Adaptive Behaviour Scale (VABS), Rett Severity Scale (RSSS) and Hand Apraxia Scale (HAS)]. Results Six children with RS (all girls, mean and SD age 11.3 ± 3.1 years) were included. Serum samples of 50 children without RS (25 females, mean and SD age 13.5 ± 3.9 years) served as reference for BDNF measurements. No serious adverse events occurred. Primary and secondary outcome measures were not met. CSF BDNF levels were associated with all clinical scores: RSSS (estimate − 0.04, mult.effect 0.96, CI [0.94; 0.98], p = 0.03), HAS (estimate − 0.09, mult.effect 0.91, CI [0.89; 0.94], p < 0.01) and VABS (communication: estimate 0.03, mult.effect 1.03, CI [1.02; 1.04], p

Abstract Objective To determine the levels of brain‐derived neurotrophic factor (BDNF) in the serum of patients suffering from multiple sclerosis (MS) to evaluate the potential of serum BDNF as a biomarker for MS. Methods Using a recently validated enzyme‐linked immunoassay (ELISA) we measured BDNF in patients with MS (pwMS), diagnosed according to the 2001 McDonald criteria and aged between 18 and 70 years, participating in a long‐term cohort study with annual clinical visits, including blood sampling, neuropsychological testing, and brain magnetic resonance imaging (MRI). The results were compared with an age‐ and sex‐matched cohort of healthy controls (HC). Correlations between BDNF levels and a range of clinical and magnetic resonance imaging variables were assessed using an adjusted linear model. Results In total, 259 pwMS and 259 HC were included, with a mean age of 44.42 ± 11.06 and 44.31 ± 11.26 years respectively. Eleven had a clinically isolated syndrome (CIS), 178 relapsing remitting MS (RRMS), 56 secondary progressive MS (SPMS), and 14 primary progressive MS (PPMS). Compared with controls, mean BDNF levels were lower by 8 % (p˂0.001) in pwMS. The level of BDNF in patients with SPMS was lower than in RRMS (p = 0.004). Interpretation We conclude that while the use of comparatively large cohorts enables the detection of a significant difference in BDNF levels between pwMS and HC, the difference is small and unlikely to usefully inform decision‐making processes at an individual patient level.

Objective: This study aimed to investigate longitudinal deep gray matter (DGM) shape changes and their relationship with measures of clinical disability and white matter lesion-load in a large multiple sclerosis (MS) cohort. Materials and Methods: A total of 230 MS patients (179 relapsing-remitting, 51 secondary progressive; baseline age 44.5 ± 11.3 years; baseline disease duration 12.99 ± 9.18) underwent annual clinical and MRI examinations over a maximum of 6 years (mean 4.32 ± 2.07 years). The DGM structures were segmented on the T1-weighted images using the “Multiple Automatically Generated Templates” brain algorithm. White matter lesion-load was measured on T2-weighted MRI. Clinical examination included the expanded disability status scale, 9-hole peg test, timed 25-foot walk test, symbol digit modalities test and paced auditory serial addition test. Vertex‐wise longitudinal analysis of DGM shapes was performed using linear mixed effect models and evaluated the association between average/temporal changes of DGM shapes with average/temporal changes of clinical measurements, respectively. Results: A significant shrinkage over time of the bilateral ventrolateral pallidal and the left posterolateral striatal surface was observed, whereas no significant shape changes over time were observed at the bilateral thalamic and right striatal surfaces. Higher average lesion-load was associated with an average inwards displacement of the global thalamic surface with relative sparing on the posterior side (slight left-side predominance), the antero-dorso-lateral striatal surfaces bilaterally (symmetric on both sides) and the antero-lateral pallidal surface (left-side predominance). There was also an association between shrinkage of large lateral DGM surfaces with higher clinical motor and cognitive disease severity. However, there was no correlation between any DGM shape changes over time and measurements of clinical progression or lesion-load changes over time. Conclusions: This study showed specific shape change of DGM structures occurring over time in relapse-onset MS. Although these shape changes over time were not associated with disease progression, we demonstrated a link between DGM shape and the patients’ average disease severity as well as white matter lesion-load.

Introduction: Multiple Sclerosis (MS) is a common neurological disease primarily characterized by myelin damage in lesions and in normal - appearing white and gray matter (NAWM, NAGM).Several quantitative MRI (qMRI) methods are sensitive to myelin characteristics by measuring specific tissue biophysical properties. However, there are currently few studies assessing the relative reproducibility and sensitivity of qMRI measures to MS pathology in vivo in patients. Methods: We performed two studies. The first study assessed of the sensitivity of qMRI measures to MS pathology: in this work, we recruited 150 MS and 100 healthy subjects, who underwent brain MRI at 3 T including quantitative T1 mapping (qT1), quantitative susceptibility mapping (QSM), magnetization transfer saturation imaging (MTsat) and myelin water imaging for myelin water fraction (MWF). The sensitivity of qMRIs to MS focal pathology (MS lesions vs peri-plaque white/gray matter (PPWM/PPGM)) was studied lesion-wise; the sensitivity to diffuse normal appearing (NA) pathology was measured using voxel-wise threshold-free cluster enhancement (TFCE) in NAWM and vertex-wise inflated cortex analysis in NAGM. Furthermore, the sensitivity of qMRI to the identification of lesion tissue was investigated using a voxel-wise logistic regression analysis to distinguish MS lesion and PP voxels.The second study assessed the reproducibility of myelin-sensitive qMRI measures in a single scanner. To evaluate the intra-session and inter-session reproducibility of qMRI measures, we have investigated 10 healthy subjects, who underwent two brain 3 T MRIs within the same day (without repositioning), and one after 1-week interval. Five region of interest (ROIs) in white and deep grey matter areas were segmented, and inter- and intra- session reproducibility was studied using the intra-class correlation coefficient (ICC). Further, we also investigated the voxel-wise reproducibility of qMRI measures in NAWM and NAGM. Results: qT1 and QSM showed the highest sensitivity to distinguish MS focal WM and cortical pathology from peri-plaque WM (P

Background: Various working memory (WM) trainings have been tested, but differences in experimental designs, the lack of theoretical background, and the need of identifying task-related processes such as filtering efficiency limit conclusions about their comparative efficacy.Objectives: In this study, we compared the efficacy of a model-based WM training with (MB+) and without (MB) distractor inhibition on improving WM capacity to a dual n-back and active control condition.Methods: This randomized clinical trial included 123 healthy elderly adults (78 women, 45 men; aged 64.1 ± 8.3 years). All groups underwent 12 40-min training sessions over 3 weeks and four cognitive testing sessions. The first two sessions served as double baseline to account for practice effects. Primary outcome was WM capacity post-training measured by complex span tasks. Near and far transfer was assessed by simple span, n-back, visuospatial and verbal learning, processing speed, and reasoning tasks.Results: Due to preliminary termination (COVID-19), 93 subjects completed the post-training and 60 subjects the follow-up session. On a whole group level, practice effects occurred from prebaseline to baseline in WM capacity (b = 4.85, t(103) = 4.01, p < 0.001, r = 0.37). Linear mixed-effects models revealed a difference in WM capacity post-training between MB+ and MB (b = −9.62, t(82) = −2.52, p = 0.014, r = 0.27) and a trend difference between MB+ and dual n-back (b = −7.59, t(82) = −1.87, p = 0.065, r = 0.20) and control training (b = −7.08, t(82) = −1.86, p = 0.067, r = 0.20). Univariate analyses showed an increase between pre- and post-training for WM capacity within MB+ (t(22) = −3.34, p < 0.05) only. There was no difference between groups pre- and post-training regarding near and far transfer. Univariate analyses showed improved visuospatial learning within MB+ (t(21) = −3.8, p < 0.05), improved processing speed (t(23) = 2.19, p< 0.05) and n-back performance (t(23) = 2.12, p < 0.05) in MB, and improved n-back performance (t(25) = 3.83, p < 0.001) in the dual n-back training.Interpretation: A model-based WM training including filtering efficacy may be a promising approach to increase WM capacity and needs further investigation in randomized controlled studies.

Objectives: Lateral geniculate nucleus (LGN) volume is reduced after optic neuritis (ON) in neuromyelitis optica spectrum disorders (NMOSD). We aimed at a longitudinal assessment of LGN volume in NMOSD. Methods: Twenty-nine patients with aquaporin 4-IgG seropositive NMOSD (age: 47.8 ± 14.6 years (y), female: n = 27, history of ON (NMO-ON): n = 17, median time since ON: 3[1.2–12.1]y) and 18 healthy controls (HC; age: 39.3 ± 15.8y; female: n = 13) were included. Median follow-up was 4.1[1.1–4.7]y for patients and 1.7[0.9–3.2]y for HC. LGN volume was measured using a multi-atlas-based approach of automated segmentation on 3 Tesla magnetic resonance images. Retinal optical coherence tomography and probabilistic tractography of the optic radiations (OR) were also performed. Results: At baseline, NMO-ON patients had lower LGN volumes (395.4 ± 48.9 mm3) than patients without ON (NMO-NON: 450.7 ± 55.6 mm3; p = 0.049) and HC (444.5 ± 61.5 mm3, p = 0.025). LGN volume was associated with retinal neuroaxonal loss and microstructural OR damage. Longitudinally, there was no change in LGN volumes in the absence of ON, neither in all patients (B = −0.6, SE = 1.4, p = 0.670), nor in NMO-ON (B = −0.8, SE = 1.6, p = 0.617) and NMO-NON (B = 1.7, SE = 3.5, p = 0.650). However, in four patients with new ON during follow-up, LGN volume was reduced at last visit (median time since ON: 2.6 [1.8–3.9] y) compared to the measurement before ON (352 ± 52.7 vs. 371.1 ± 55.9 mm3; t = −3.6, p = 0.036). Conclusion: Although LGN volume is reduced after ON in NMOSD, this volume loss is not progressive over longer follow-up or independent of ON. Thus, our findings -at least in this relatively small cohort- do not support occult neurodegeneration of the afferent visual pathway in NMOSD.

Brain atrophy has been identified as an important contributing factor to the development of disability in multiple sclerosis (MS). In this respect, more and more interest is focussing on the role of deep grey matter (DGM) areas. Novel data analysis pipelines are available for the automatic segmentation of DGM using three-dimensional (3D) MRI data. However, in clinical trials, often no such high-resolution data are acquired and hence no conclusions regarding the impact of new treatments on DGM atrophy were possible so far. In this work, we used FMRIB's Integrated Registration and Segmentation Tool (FIRST) to evaluate the possibility of segmenting DGM structures using standard two-dimensional (2D) T1-weighted MRI. In a cohort of 70 MS patients, both 2D and 3D T1-weighted data were acquired. The thalamus, putamen, pallidum, nucleus accumbens, and caudate nucleus were bilaterally segmented using FIRST. Volumes were calculated for each structure and for the sum of basal ganglia (BG) as well as for the total DGM. The accuracy and reliability of the 2D data segmentation were compared with the respective results of 3D segmentations using volume difference, volume overlap and intra-class correlation coefficients (ICCs). The mean differences for the individual substructures were between 1.3% (putamen) and −25.2% (nucleus accumbens). The respective values for the BG were −2.7% and for DGM 1.3%. Mean volume overlap was between 89.1% (thalamus) and 61.5% (nucleus accumbens); BG: 84.1%; DGM: 86.3%. Regarding ICC, all structures showed good agreement with the exception of the nucleus accumbens. The results of the segmentation were additionally validated through expert manual delineation of the caudate nucleus and putamen in a subset of the 3D data. In conclusion, we demonstrate that subcortical segmentation of 2D data are feasible using FIRST. The larger subcortical GM structures can be segmented with high consistency. This forms the basis for the application of FIRST in large 2D MRI data sets of clinical trials in order to determine the impact of therapeutic interventions on DGM atrophy in MS.

Background: Migraine is associated with increased cardiovascular risk and vascular dysfunction. Since aerobic exercise can reduce cardiovascular risk, the present randomized controlled trail aimed at investigating the effects of high-intensity interval training (HIT) vs. moderate continuous exercise training (MCT) on arterial stiffness in migraine patients.Methods: Forty-eight episodic migraineurs were initially enrolled in the study. 37 patients [female: 30; age: 37 (SD: 10); BMI: 23.1 (5.2); Migraine days per month: 3.7 (2.5)] completed the intervention. Central blood pressure, pulse wave reflection, and aortic pulse wave velocity (PWV) were obtained by an oscillometric monitor. Incremental treadmill exercise testing yielded maximal and submaximal fitness parameters. Participants were randomly assigned to either HIT, MCT, or a control group (CON). The intervention groups trained twice a week over a 12-week intervention period.Results: After adjustment for between-group baseline differences, a moderate meaningful overall reduction of the augmentation index at 75 min−1 heart rate (AIx@75) was observed [partial eta squared (ηp2) = 0.16; p = 0.06]. With 91% likely beneficial effects, HIT was more effective in reducing AIx@75 than MCT [HIT: pre 22.0 (9.7), post 14.9 (13.0), standardized mean difference (SMD) = 0.62; MCT: pre 16.6 (8.5), post 21.3 (10.4), SMD −0.49]. HIT induced a relevant reduction in central systolic blood pressure [cSBP: pre 118 (23) mmHg, post 110 (16) mmHg, SMD = 0.42] with a 59% possibly beneficial effect compared to CON, while MCT showed larger effects in lowering central diastolic blood pressure [pre 78 (7) mmHg, post 74 (7) mmHg, SMD = 0.61], presenting 60% possibly beneficial effects compared to CON. Central aortic PWV showed no changes in any of the three groups. Migraine days were reduced more successfully by HIT than MCT (HIT: SMD = 1.05; MCT: SMD = 0.43).Conclusion: HIT but not MCT reduces AIx@75 as a measure of pulse wave reflection and indirect marker of systemic arterial stiffness. Both exercise modalities beneficially affect central blood pressure. HIT proved to be an effective complementary treatment option to reduce vascular dysfunction and blood pressure in migraineurs.

The cerebellum is known to be involved not only in motor but also cognitive and affective processes. Structural changes in the cerebellum in relation to cognitive dysfunction are an emerging topic in the field of neuro-psychiatric disorders. In Multiple Sclerosis (MS) cerebellar motor and cognitive dysfunction occur in parallel, early in the onset of the disease, and the cerebellum is one of the predilection sites of atrophy. This study is aimed at determining the relationship between cerebellar volumes, clinical cerebellar signs, cognitive functioning and fatigue in MS. Cerebellar volumetry was conducted using T1-weighted MPRAGE magnetic resonance imaging of 172 MS patients. All patients underwent a clinical and brief neuropsychological assessment (information processing speed, working memory), including fatigue testing. Patients with and without cerebellar signs differed significantly regarding normalized cerebellar total volume (nTCV), normalized brain volume (nBV) and whole brain T2 lesion volume (LV). Patients with cerebellar dysfunction likewise performed worse in cognitive tests. A regression analysis indicated that age and nTCV explained 26.3% of the variance in SDMT (symbol digit modalities test) performance. However, only age, T2 LV and nBV remained predictors in the full model (r(2) = 0.36). The full model for the prediction of PASAT (Paced Auditory Serial Addition Test) scores (r(2) = 0.23) included age, cerebellar and T2 LV. In the case of fatigue, only age and nBV (r(2) = 0.17) emerged as significant predictors. These data support the view that cerebellar abnormalities contribute to disability, including cognitive impairment in MS. However, this contribution does not seem to be independent of, and may even be dominated by wider spread MS pathology as reflected by nBV and T2 LV.

Multiple sclerosis (MS) has traditionally been considered to be primarily an inflammatory demyelinating disorder. Nowadays it is recognised as both an inflammatory and a neurodegenerative condition. This recognition is reflected in the development of new disease-modifying therapies that may offer the potential to reduce axon damage, either by inhibiting neurodegeneration or by promoting endogenous repair mechanisms. Since there is only a limited correlation between the clinical features of MS and findings on conventional magnetic resonance imaging (MRI), for the evaluation of such therapies new outcome measures are warranted. Grey matter atrophy occurs in the earliest stages of MS, progresses faster than in healthy individuals, and shows significant correlations with MRI lesion load, cognitive function and measures of physical disability; indeed, brain atrophy is the best predictor of subsequent disability and can be readily measured using MRI. Furthermore, it is becoming clear that currently available therapies differ in their effects on brain atrophy, and this may have important implications for the management of MS. New MRI techniques and advances in software development offer an opportunity to extend brain atrophy measurements beyond research studies to the routine management of MS patients.