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As atrophy represents the most relevant driver of progression in multiple sclerosis (MS), we investigated the impact of different patterns of brain and spinal cord atrophy on disability worsening in MS. We acquired clinical and MRI data from 90 patients with relapsing–remitting MS and 24 healthy controls (HC). Clinical progression at follow-up (mean 3.7 years) was defined according to the Expanded Disability Status Scale-Plus. Brain and spinal cord volumes were computed on MRI brain scans. After normalizing each participants’ brain and spine volume to the mean of the HC, z-score cut-offs were applied to separate pathologically atrophic from normal brain and spine volumes (accepting a 2.5% error probability). Accordingly, MS patients were classified into four groups (Group I: no brain or spinal cord atrophy N = 40, Group II: brain atrophy/no spinal cord atrophy N = 11, Group III: no brain atrophy/ spinal cord atrophy N = 32, Group IV: both brain and spinal cord atrophy N = 7). All patients’ groups showed significantly lower brain volume than HC (p p p = 0.049) and Group IV (p = 0.023) vs Group I, and in Group IV (p = 0.048) vs Group III. Spinal cord atrophy (OR = 3.75, p = 0.018) and brain + spinal cord atrophy (OR = 5.71, p = 0.046) were significant predictors of disability progression. The presence of concomitant brain and spinal cord atrophy is the strongest correlate of progression over time. Isolated spinal cord atrophy exerts a similar effect, confirming the leading role of spinal cord atrophy in the determination of motor disability.

Essential tremor (ET) is one of the most common movement disorders. Over the last 10 years, magnetic resonance imaging (MRI) has shed light on the structural and functional abnormalities possibly involved in ET pathophysiology. In this systematic review, we aimed to identify the cortical and subcortical structures involved and the role that different brain areas play in the pathophysiology of motor and non-motor ET features. We found that structural (grey and white matter) cerebellar damage and connectivity alterations between the cerebellum and various cortical areas play a role in both motor and non-motor symptoms of ET. In particular, many studies found an association between MRI findings and non-motor symptoms.

We investigated changes in gray matter (GM) and white matter (WM) in the whole brain, including both cortical and subcortical structures, and their relationship with tremor severity, psychiatric symptoms, and cognitive impairment in patients affected by essential tremor (ET). We studied 19 ET patients and 15 healthy subjects (HS). All the subjects underwent a 3-T MRI study based on 3D-T1 and diffusion tensor images. For the GM analysis, cortical thickness was assessed by using the Computational Anatomy Tool, basal ganglia and thalamus volumes by using the FMRIB software library, and cerebellum lobular volumes by using the spatial unbiased atlas template. For the WM assessment, we performed a voxel-wise analysis by means of tract-based spatial statistics. Patients’ tremor severity and psychiatric and cognitive disorders were evaluated by means of standard clinical scales. Neuroimaging data were correlated with clinical scores. We found significantly smaller right and left thalamic volumes in ET patients than in HS, which correlated with cognitive scores. We did not observe any significant differences either in cortical thickness or in cerebellar lobular volumes between patients and HS. WM abnormalities were detected in most hemisphere bundles, particularly in the corticospinal tract, cerebellar peduncles, and corpus callosum. The WM abnormalities significantly correlated with tremor severity, cognitive profile, and depression. Our study indicates that ET is characterized by several GM and WM changes of both infra- and supratentorial brain structures. The results may help to better understand mechanisms underlying tremor severity and psychiatric and cognitive impairment in ET. • We performed a comprehensive evaluation of gray and white matter in the same sample of patients with essential tremor using recently developed data analysis methods. • Essential tremor is characterized by widespread gray and white matter changes in both infra- and supratentorial brain structures. The results may help to better understand motor and non-motor symptoms in patients with essential tremor.

Multiple Sclerosis (MS) is a chronic neurological disease that represents a leading cause of disability in young adults and is characterized by inflammation and degeneration of both white matter (WM) and gray matter (GM). Defining the presence or absence of inflammation on individual basis is a key point in choosing the therapy and monitoring the treatment response. Magnetic resonance imaging (MRI) represents the most sensitive non-invasive tool to monitor inflammation in the clinical practice. Indeed, in the early phase of inflammation MRI detects new lesions as extrusion of gadolinium contrast agents across the altered blood-brain-barrier (BBB). The occurrence of MRI lesions is used to confirm diagnosis and has been validated as surrogate marker of relapse to monitor response to treatments. However, focal gadolinium-enhancing lesions represent only an aspect of neuroinflammation. Recent studies have suggested the presence of a widespread inflammation of the central nervous system (CNS), which is mainly related to microglial cells activation occurring both at the edge of chronic focal lesions and throughout the normal-appearing brain tissue. New imaging techniques have been developed to study diffuse inflammation taking place outside the focal plaques. The scope of this review is to examine the various neuroimaging techniques and those biophysical quantities that can be non-invasively detected to enlighten the different aspects of neuroinflammation. Some techniques are commonly used in the clinical practice, while others are used in the research field to better understand the pathophysiological mechanisms of the disease and the role of inflammation.

In‐scanner head motion represents a major confounding factor in functional connectivity studies and it raises particular concerns when motion correlates with the effect of interest. One such instance regards research focused on functional connectivity modulations induced by sustained cognitively demanding tasks. Indeed, cognitive engagement is generally associated with substantially lower in‐scanner movement compared with unconstrained, or minimally constrained, conditions. Consequently, the reliability of condition‐dependent changes in functional connectivity relies on effective denoising strategies. In this study, we evaluated the ability of common denoising pipelines to minimize and balance residual motion‐related artifacts between resting‐state and task conditions. Denoising pipelines—including realignment/tissue‐based regression, PCA/ICA‐based methods (aCompCor and ICA‐AROMA, respectively), global signal regression, and censoring of motion‐contaminated volumes—were evaluated according to a set of benchmarks designed to assess either residual artifacts or network identifiability. We found a marked heterogeneity in pipeline performance, with many approaches showing a differential efficacy between rest and task conditions. The most effective approaches included aCompCor, optimized to increase the noise prediction power of the extracted confounding signals, and global signal regression, although both strategies performed poorly in mitigating the spurious distance‐dependent association between motion and connectivity. Censoring was the only approach that substantially reduced distance‐dependent artifacts, yet this came at the great cost of reduced network identifiability. The implications of these findings for best practice in denoising task‐based functional connectivity data, and more generally for resting‐state data, are discussed., We showed the inefficacy of many denoising strategies in balancing motion‐related artifacts between functional conditions that are differently prone to motion, such as rest and cognitively demanding conditions. While no pipeline was able to completely suppress motion artifacts and simultaneously maximize network identifiability, we found that strategies exploiting an optimized aCompCor yielded the best results. Importantly, we advocate the use of censoring with caution, since we found the method to be cost ineffective, prone to introduce biases and to reduce network identifiability.

Objective: To evaluate baseline characteristics predictive of improving information processing speed in multiple sclerosis (MS) and the relationship between cognitive and motor response to dalfampridine (DA) treatment. Methods: This is a post hoc analysis of a randomized, double-blind, placebo-controlled trial in patients with MS randomized to receive DA 10 mg or placebo twice daily for 12 consecutive weeks. Here, we include only data from 71 patients in the arm treated with DA. According to the median value of Symbol Digit Modalities Test (SDMT) response, patients were categorized as “full responders” (FR) or “partially responders” (PR). Results: There was higher possibility of being FR in the presence of a baseline lower Expanded Disability Status Scale [odds ratio (OR) 0.69; 95% confidence interval (CI) 0.5–0.97, p = 0.034], a higher Multiple Sclerosis Functional Composite value (OR 1.37; 95%CI 1.05–1.8, p = 0.022), a lower Timed 25-Foot Walk Test (OR 0.76; 95% CI 0.6–0.98, p = 0.033), and a lower 9-Hole Peg Test with dominant hand (OR 0.92; 95% CI 0.86–0.99, p = 0.029). FR group did not show any significant improvement of motor performance compared with PR group. Conclusion: The current analysis shows that in MS patients with cognitive deficit, the greatest improvement in SDMT provided by DA was observed in patients with milder motor impairment; cognitive and motor responses to treatments are not related. Trial registration: EU Clinical Trials Register; ID 2013-002558-64 ( https://www.clinicaltrialsregister.eu/ctr-search/search?query=2013-002558-64 )

Only a few studies have evaluated the brain functional changes associated with disease-modifying therapies (DMTs) in multiple sclerosis (MS), though none used a composite measure of clinical and MRI outcomes to evaluate DMT-related brain functional connectivity (FC) measures predictive of short-term outcome. Therefore, we investigated the following: (1) baseline FC differences between patients who showed evidence of disease activity after a specific DMT and those who did not; (2) DMT-related effects on FC, and; (3) possible relationships between DMT-related FC changes and changes in performance. We used a previously analyzed dataset of 30 relapsing MS patients who underwent fingolimod treatment for 6 months and applied the “no evidence of disease activity” (NEDA-3) status as a clinical response indicator of treatment efficacy. Resting-state fMRI data were analyzed to obtain within- and between-network FC measures. After therapy, 14 patients achieved NEDA-3 status (hereinafter NEDA), while 16 did not (EDA). The two groups significantly differed at baseline, with the NEDA group having higher within-network FC in the anterior and posterior default mode, auditory, orbitofrontal, and right frontoparietal networks than the EDA. After therapy, NEDA showed significantly reduced within-network FC in the posterior default mode and left frontoparietal networks and increased between-network FC in the posterior default mode/orbitofrontal networks; they also showed PASAT improvement, which was correlated with greater within-network FC decrease in the posterior default mode network and with greater between-network FC increase. No significant longitudinal FC changes were found in the EDA. Taken together, these findings suggest that NEDA status after fingolimod is related to higher within-network FC at baseline and to a consistent functional reorganization after therapy.

Tourette syndrome (TS) and obsessive–compulsive disorder (OCD) are two neurodevelopmental disorders characterized by repetitive behaviors. Our recent study in drug-naive children with TS and OCD provided evidence of cerebellar involvement in both disorders. In addition, cerebellar functional connectivity (FC) was similar in TS patients without comorbidities (TSpure) and TS patients with OCD comorbidity (TS + OCD), but differed in pure OCD patients. To investigate in detail the cerebellar involvement in the pathophysiology of TS and OCD, we explored cerebellar structural and functional abnormalities in drug-naive children with TSpure, TS + OCD, and OCD and assessed possible correlations with severity scores. We examined 53 drug-naive children, classified as TSpure (n = 16), TS + OCD (n = 14), OCD (n = 11), or controls (n = 12). All subjects underwent a multimodal 3T magnetic resonance imaging examination. Cerebellar lobular volumes and quantitative diffusion tensor imaging parameters of cerebellar peduncles were used as measures of structural integrity. The dentate nucleus was selected as a region of interest to examine cerebello-cerebral functional connectivity alterations. Structural analysis revealed that both TSpure and TS + OCD patients had higher fractional anisotropy in cerebellar peduncles than controls. Conversely, OCD patients were characterized by lower fractional anisotropy than both controls and TSpure and TS + OCD patients. Lastly, cerebellar functional connectivity analysis revealed significant alterations in the cerebello-thalamo-cortical circuit in TSpure, TS + OCD, and OCD patients. Early cerebellar structural and functional changes in drug-naive pediatric TSpure, TS + OCD, and OCD patients support a primary role of the cerebellum in the pathophysiology of these disorders.

BACKGROUND AND PURPOSE: Conventional MR imaging explains only a fraction of the clinical outcome variance in multiple sclerosis. We aimed to evaluate machine learning models for disability prediction on the basis of radiomic, volumetric, and connectivity features derived from routine brain MR images. MATERIALS AND METHODS: In this retrospective cross-sectional study, 3T brain MR imaging studies of patients with multiple sclerosis, including 3D T1-weighted and T2-weighted FLAIR sequences, were selected from 2 institutions. T1-weighted images were processed to obtain volume, connectivity score (inferred from the T2 lesion location), and texture features for an atlas-based set of GM regions. The site 1 cohort was randomly split into training (n = 400) and test (n = 100) sets, while the site 2 cohort (n = 104) constituted the external test set. After feature selection of clinicodemographic and MR imaging–derived variables, different machine learning algorithms predicting disability as measured with the Expanded Disability Status Scale were trained and cross-validated on the training cohort and evaluated on the test sets. The effect of different algorithms on model performance was tested using the 1-way repeated-measures ANOVA. RESULTS: The selection procedure identified the 9 most informative variables, including age and secondary-progressive course and a subset of radiomic features extracted from the prefrontal cortex, subcortical GM, and cerebellum. The machine learning models predicted disability with high accuracy (r approaching 0.80) and excellent intra- and intersite generalizability (r ≥ 0.73). The machine learning algorithm had no relevant effect on the performance. CONCLUSIONS: The multidimensional analysis of brain MR images, including radiomic features and clinicodemographic data, is highly informative of the clinical status of patients with multiple sclerosis, representing a promising approach to bridge the gap between conventional imaging and disability.

Objective To explore whether abnormal thalamic resting-state functional connectivity (rsFC) contributes to altered sensorimotor integration and hand dexterity impairment in multiple sclerosis (MS). Methods To evaluate sensorimotor integration, we recorded kinematic features of index finger abductions during somatosensory temporal discrimination threshold (STDT) testing in 36 patients with relapsing-remitting MS and 39 healthy controls (HC). Participants underwent a multimodal 3T structural and functional MRI protocol. Results Patients had lower index finger abduction velocity during STDT testing compared to HC. Thalamic rsFC with the precentral and postcentral gyri, supplementary motor area (SMA), insula, and basal ganglia was higher in patients than HC. Intrathalamic rsFC and thalamic rsFC with caudate and insula bilaterally was lower in patients than HC. Finger movement velocity positively correlated with intrathalamic rsFC and negatively correlated with thalamic rsFC with the precentral and postcentral gyri, SMA, and putamen. Conclusions Abnormal thalamic rsFC is a possible substrate for altered sensorimotor integration in MS, with high intrathalamic rsFC facilitating finger movements and increased thalamic rsFC with the basal ganglia and sensorimotor cortex contributing to motor performance deterioration. Significance The combined study of thalamic functional connectivity and upper limb sensorimotor integration may be useful in identifying patients who can benefit from early rehabilitation to prevent upper limb motor impairment.

To evaluate the role of iron deposition in subcortical nuclei of patients with essential tremor (ET). Twenty-three patients with ET underwent a standardized 3T-MRI protocol. We specifically assessed iron deposition using susceptibility-weighted angiography (SWAN) images in seven specific regions of interest (ROIs): the thalamus, putamen, globus pallidus, caudate nucleus, substantia nigra, red nucleus, and dentate nucleus. Tremor in ET patients was clinically assessed using the Fahn-Tolosa-Marin Tremor Rating Scale (FTM-TRS). ET patient data were compared with data obtained from 23 Parkinson’s disease (PD) patients and 14 healthy subjects (HS). No differences in iron deposition in the seven ROIs were found between ET patients and HS. Conversely, PD patients showed increased iron deposition in the substantia nigra in comparison with both ET patients and HS. Our results indicate the absence of iron deposition in subcortical nuclei of ET patients, which is generally considered a marker of neurodegeneration.

Previous studies in cohorts of Tourette syndrome (TS) or obsessive-compulsive disorder (OCD) patients have not clarified whether these two disorders represent two clinical conditions or they are distinct clinical phenotypes of a common disease spectrum. The study aimed to compare functional connectivity (FC) patterns in a pediatric drug-naive cohort of 16 TS patients without any comorbidity (TS), 14 TS patients with OCD (TS + OCD), and 10 pure OCD patients as well as 11 matched controls that underwent resting state fMRI. Via independent component analysis, we examined FC in the basal ganglia (BGN), sensorimotor (SMN), cerebellum (CBN), frontoparietal (FPN), default-mode (DMN), orbitofrontal (OBFN), and salience (SAN) networks among the above cohorts and their association with clinical measures. Compared to controls, TS and TS + OCD patients showed higher FC in the BGN, SMN, CBN and DMN and lower FC in the FPN and SAN. The TS and TS + OCD groups showed comparable FC in all networks. In contrast to controls, OCD patients exhibited increased FC in the BGN, SMN, CBN, DMN, FPN, and SAN. OCD patients also showed higher FC in CBN and FPN when compared with TS and TS + OCD patients both separately and as one group. Tic severity negatively correlated with FC in CBN and FPN in the TS group, while the compulsiveness scores positively correlated with the same two networks in OCD patients. Our findings suggest common FC changes in TS and TS + OCD patients. In contrast, OCD is characterized by a distinctive pattern of FC changes prominently involving the CBN and FPN.

Highlights • This systematic review focuses on structural and functional neuroimaging findings in PD patients with FOG. • The existing neuroimaging literature may explain several mechanisms underpinning FOG in PD. • FOG in PD reflect structural or functional damage in brain regions responsible for human locomotion., Freezing of gait (FOG) is a paroxysmal gait disorder that often occurs at advanced stages of Parkinson's disease (PD). FOG consists of abrupt walking interruption and severe difficulty in locomotion with an increased risk of falling. Pathophysiological mechanisms underpinning FOG in PD are still unclear. However, advanced MRI and nuclear medicine studies have gained relevant insights into the pathophysiology of FOG in PD. Neuroimaging studies have demonstrated structural and functional abnormalities in a number of cortical and subcortical brain regions in PD patients with FOG. In this paper, we systematically review existing neuroimaging literature on the structural and functional brain changes described in PD patients with FOG, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We evaluate previous studies using various MRI techniques to estimate grey matter loss and white matter degeneration. Moreover, we review functional brain changes by examining functional MRI and nuclear medicine imaging studies. The current review provides up-to-date knowledge in this field and summarizes the possible mechanisms responsible for FOG in PD.

Despite previous functional MRI studies on alterations within the cerebello-thalamo-cortical circuit in patients with essential tremor (ET), the specific role of disconnection of the dentate nucleus (DN), the main output cerebellar pathway, still needs clarification. In this study, we evaluated DN functional connectivity (FC) changes and their relationship with motor and non-motor symptoms in ET. We studied 25 ET patients and 26 healthy controls. Tremor severity was assessed using the Fahn–Tolosa–Marin tremor rating scale (FTM-TRS) and tremor amplitude and frequency were evaluated using kinematic techniques. Cognitive profile was assessed by montreal cognitive assessment (MoCA) and frontal assessment battery (FAB). All participants underwent a 3 T MRI protocol including resting-state blood oxygenation level dependent and diffusion tensor sequences. We used a seed-based approach to investigate DN FC and to explore the diffusion properties of cerebellar peduncles. There was significantly decreased DN FC with cortical, subcortical, and cerebellar areas in ET patients compared with healthy controls. Correlation analysis showed that: (1) the DN FC with the supplementary motor area, pre and postcentral gyri, and prefrontal cortex negatively correlated with FTM-TRS score and disease duration; (2) DN FC changes in the thalamus and caudate negatively correlated with peak tremor frequency, changes in the cerebellum positively correlated with tremor amplitude, and changes in the bilateral thalamus negatively correlated with tremor amplitude, and (3) DN FC with the associative prefrontal and parietal cortices, basal ganglia, and thalamus positively correlated with the MoCA score. Diffusion abnormalities were found in the three cerebellar peduncles, which did not correlate with clinical scores.

To characterize the relation between brain functional connectivity and disability in patients with multiple sclerosis; to investigate the existence of critical values of both disability and functional connectivity corresponding to exhaustion of functional adaptive mechanisms.Hundred-and-nineteen patients with no-to-severe disability and 42 healthy subjects were studied via 3T resting state functional MRI. Out of 116 regions extracted from Automated Anatomical Labeling atlas, pairs of regions whose functional connectivity correlated with Expanded Disability Status Score were identified. In patients, mathematical modeling was applied to find the best models describing Expanded-Disability-Status-Score vs structural or functional measures. Functional vs structural models intersecting points were identified.Disability had direct linear relation with lesion load (r = 0.40, p 5E-6), inverse of thalamic volume (r = 0.31 p 1E-3) and functional connectivity in bi-frontal pairs of regions (r 0.40, p 0.04), while being non-linearly associated with functional connectivity in cerebello-temporal and cerebello-frontal pairs of regions (F 1.73, p 0.02). Structural vs functional models intersecting points corresponded to Expanded Disability Status Score of 3.0. 85% of patients scoring more than 3.0 showed functional connectivity in cerebello-temporal and cerebello-frontal pairs of regions below confidence intervals (z = [2.28-2.88] 95% CI) measured in healthy subjects.Functional brain connectivity changes may represent mechanisms of adaptation to structural damage and inflammation and may be not always clinically beneficial. Functional connectivity decreases in comparison with structural measure at Expanded Disability Status Score greater than 3.0, which may be critical and indicate exhaustion of compensatory mechanisms.