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.
•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.
Objectives
To evaluate the accuracy of a data-driven approach, such as machine learning classification, in predicting disability progression in MS.
Methods
We analyzed structural brain images of 163 ...subjects diagnosed with MS acquired at two different sites. Participants were followed up for 2–6 years, with disability progression defined according to the expanded disability status scale (EDSS) increment at follow-up. T2-weighted lesion load (T2LL), thalamic and cerebellar gray matter (GM) volumes, fractional anisotropy of the normal appearing white matter were calculated at baseline and included in supervised machine learning classifiers. Age, sex, phenotype, EDSS at baseline, therapy and time to follow-up period were also included. Classes were labeled as stable or progressed disability. Participants were randomly chosen from both sites to build a sample including 50% patients showing disability progression and 50% patients being stable. One-thousand machine learning classifiers were applied to the resulting sample, and after testing for overfitting, classifier confusion matrix, relative metrics and feature importance were evaluated.
Results
At follow-up, 36% of participants showed disability progression. The classifier with the highest resulting metrics had accuracy of 0.79, area under the true positive versus false positive rates curve of 0.81, sensitivity of 0.90 and specificity of 0.71. T2LL, thalamic volume, disability at baseline and administered therapy were identified as important features in predicting disability progression. Classifiers built on radiological features had higher accuracy than those built on clinical features.
Conclusions
Disability progression in MS may be predicted via machine learning classifiers, mostly evaluating neuroradiological features.
Background:
Damage to the cerebellar sensorimotor and cognitive domains may underlie physical and cognitive disability.
Objective:
To investigate resting-state functional connectivity (FC) of ...sensorimotor and cognitive cerebellum, and clinical correlates in multiple sclerosis (MS).
Methods:
A total of 119 patients with MS and 42 healthy subjects underwent multimodal 3T-magnetic resonance imaging (MRI). Patients were evaluated using the Expanded Disability Status Scale and Multiple Sclerosis Functional Composite Scale. After parcellation of sensorimotor (lobules I–V + VIII) and cognitive cerebellum (lobules VI, VII, IX, X), we calculated cerebellar resting-state FC using a seed-based approach.
Results:
In patients with MS, the sensorimotor cerebellum showed increased FC mainly with cerebellar, thalamic, and cortical (frontal, parietal, temporal) areas and decreased FC with insular areas; the cognitive cerebellum showed increased FC mainly with thalamic and cortical (temporal-occipital) areas, and decreased FC with frontal-insular areas. Both sensorimotor and cognitive cerebellar FC negatively correlated with disability, and positively with cognitive scores. Cerebellar structural damage only partially influenced results.
Conclusion:
The two neocerebellar circuits showed altered FC with subcortical and cortical areas. The association between increased sensorimotor and cognitive cerebellar FC and low levels of physical and cognitive disability suggests that altered FC might modulate the effects of cerebellar structural damage on clinical condition.
Objectives
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).
Methods
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.
Results
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.
Conclusion
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.
Key Points
• 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.
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
< 0.0001). Group III and IV showed lower spine volume than HC (
p
< 0.0001 for both). Higher brain lesion load was identified in Group II (
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.
Purpose
In multiple sclerosis (MS), how brain functional changes relate to clinical conditions is still a matter of debate. The aim of this study was to investigate how functional connectivity (FC) ...reorganization at three different scales, ranging from local to whole brain, is related to tissue damage and disability.
Methods
One-hundred-nineteen patients with MS were clinically evaluated with the Expanded Disability Status Scale and the Multiple Sclerosis Functional Composite. Patients and 42 healthy controls underwent a multimodal 3 T MRI, including resting-state functional MRI.
Results
We identified 16 resting-state networks via independent component analysis and measured within-network, between-network, and whole-brain (global efficiency and degree centrality) FC. Within-network FC was higher in patients than in controls in default mode, frontoparietal, and executive-control networks, and corresponded to low clinical impairment (default mode network versus Expanded Disability Status Scale
r
= − 0.31,
p
< 0.01; right frontoparietal network versus Paced Auditory Serial Addition Test
r
= 0.33,
p
< 0.01). All measures of between-network and whole-brain FC, except default mode network global efficiency, were lower in patients than in controls, and corresponded to high disability (i.e., basal ganglia global efficiency versus Timed 25-Foot Walk
r
= − 0.25,
p
< 0.03; default mode global efficiency versus Expanded Disability Status Scale
r
= − 0.44,
p
< 0.001). Altered measures of within-network, between-network, and whole-brain FC were combined in functional indices that were linearly related to disease duration, Paced Auditory Serial Addition Test and lesion load and non-linearly related to Expanded Disability Status Scale.
Conclusion
We suggest that the combined evaluation of functional alterations occurring at different levels, from local to whole brain, could exhaustively describe neuroplastic changes in MS, while increased within-network FC likely represents adaptive compensatory processes, decreased between-network and whole-brain FC likely represent loss of functional network integration consequent to structural disruption.
Neuroplasticity, which is the ability of the brain to adapt to internal and external environmental changes, physiologically occurs during growth and in response to damage. The brain’s response to ...damage is of particular interest in multiple sclerosis, a chronic disease characterized by inflammatory and neurodegenerative damage to the central nervous system. Functional MRI (fMRI) is a tool that allows functional changes related to the disease and to its evolution to be studied in vivo. Several studies have shown that abnormal brain recruitment during the execution of a task starts in the early phases of multiple sclerosis. The increased functional activation during a specific task observed has been interpreted mainly as a mechanism of adaptive plasticity designed to contrast the increase in tissue damage. More recent fMRI studies, which have focused on the activity of brain regions at rest, have yielded nonunivocal results, suggesting that changes in functional brain connections represent mechanisms of either adaptive or maladaptive plasticity. The few longitudinal studies available to date on disease evolution have also yielded discrepant results that are likely to depend on the clinical features considered and the length of the follow-up. Lastly, fMRI has been used in interventional studies to investigate plastic changes induced by pharmacological therapy or rehabilitation, though whether such changes represent a surrogate of neuroplasticity remains unclear. The aim of this paper is to systematically review the existing literature in order to provide an overall description of both the neuroplastic process itself and the evolution in the use of fMRI techniques as a means of assessing neuroplasticity. The quantitative and qualitative approach adopted here ensures an objective analysis of published, peer-reviewed research and yields an overview of up-to-date knowledge.
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)
Short-term disability progression was predicted from a baseline evaluation in patients with multiple sclerosis (MS) using their three-dimensional T1-weighted (3DT1) magnetic resonance images (MRI). ...One-hundred-and-eighty-one subjects diagnosed with MS underwent 3T-MRI and were followed up for two to six years at two sites, with disability progression defined according to the expanded-disability-status-scale (EDSS) increment at the follow-up. The patients’ 3DT1 images were bias-corrected, brain-extracted, registered onto MNI space, and divided into slices along coronal, sagittal, and axial projections. Deep learning image classification models were applied on slices and devised as ResNet50 fine-tuned adaptations at first on a large independent dataset and secondly on the study sample. The final classifiers’ performance was evaluated via the area under the curve (AUC) of the false versus true positive diagram. Each model was also tested against its null model, obtained by reshuffling patients’ labels in the training set. Informative areas were found by intersecting slices corresponding to models fulfilling the disability progression prediction criteria. At follow-up, 34% of patients had disability progression. Five coronal and five sagittal slices had one classifier surviving the AUC evaluation and null test and predicted disability progression (AUC > 0.72 and AUC > 0.81, respectively). Likewise, fifteen combinations of classifiers and axial slices predicted disability progression in patients (AUC > 0.69). Informative areas were the frontal areas, mainly within the grey matter. Briefly, 3DT1 images may give hints on disability progression in MS patients, exploiting the information hidden in the MRI of specific areas of the brain.
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