Background and purpose
Alice in Wonderland syndrome (AIWS) is a rare neurological disorder, characterized by an erroneous perception of the body schema or surrounding space. It may be caused by a ...variety of neurological disorders, but to date, there is no agreement on which brain areas are affected. The aim of this study was to identify brain areas involved in AIWS.
Methods
We conducted a literature search for AIWS cases following brain lesions. Patients were classified according to their symptoms as type A (somesthetic), type B (visual), or type C (somesthetic and visual). Using a lesion mapping approach, lesions were mapped onto a standard brain template and sites of overlap were identified.
Results
Of 30 lesions, maximum spatial overlap was present in six cases. Local maxima were identified in the right occipital lobe, specifically in the extrastriate visual cortices and white matter tracts, including the ventral occipital fasciculus, optic tract, and inferior fronto-occipital fasciculus. Overlap was primarily due to type B patients (the most prevalent type,
n
= 22), who shared an occipital site of brain damage. Type A (
n
= 5) and C patients (
n
= 3) were rarer, with lesions disparately located in the right hemisphere (thalamus, insula, frontal lobe, hippocampal/parahippocampal cortex).
Conclusions
Lesion-associated AIWS in type B patients could be related to brain damage in visual pathways located preferentially, but not exclusively, in the right hemisphere. Conversely, the lesion location disparity in cases with somesthetic symptoms suggests underlying structural/functional disconnections requiring further evaluation.
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.
Multiple sclerosis (MS) is characterized by demyelinating and degenerative processes within the central nervous system. Unlike conventional MRI,new advanced imaging techniques improve pathological ...specificity and better highlight the relationship between anatomical damage and clinical impairment.
To investigate the relationship between clinical disability and both grey (GM) and white matter (WM) regional damage in MS patients.
Thirty-six relapsing remitting-MS patients and 25 sex- and age-matched controls were enrolled. All patients were clinically evaluated by the Expanded Disability Status Scale and the Multiple Sclerosis Functional Composite (MSFC) scale, which includes the 9-hole peg test (9HPT), the timed 25-feet walking test (T25FW) and the paced auditory serial addition test (PASAT). All subjects were imaged by a 3.0 T scanner: dual-echo fast spin-echo, 3DT1-weighted and diffusion-tensor imaging (DTI) sequences were acquired. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) analyses were run for regional GM and WM assessment, respectively. T2 lesion volumes were also calculated, by using a semi-automated technique.
Brain volumetric assessment of GM and DTI measures revealed significant differences between patients and controls. In patients, different measures of WM damage correlated each-other (p<0.0001), whereas none of them correlated with GM volume. In patients, focal GM atrophy and widespread WM damage significantly correlated with clinical measures. In particular, VBM analysis revealed a significant correlation (p<0.05) between GM volume and 9HPT in cerebellum and between GM volume and PASAT in orbito-frontal cortex. TBSS showed significant correlations between DTI metrics with 9HPT and PASAT scores in many WM bundles (p<0.05), including corpus callosum, internal capsule, posterior thalamic radiations, cerebral peduncles.
Selective GM atrophy and widespread WM tracts damage are associated with functional impairment of upper-limb motion and cognition. The combined analysis of volumetric and DTI data may help to better understand structural alterations underlying physical and cognitive dysfunction in MS.
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.
Diffusion tensor imaging (DTI) is an effective means of quantifying parameters of demyelination and axonal loss. The application of DTI in Multiple Sclerosis (MS) has yielded noteworthy results. DTI ...abnormalities, which are already detectable in patients with clinically isolated syndrome (CIS), become more pronounced as disease duration and neurological impairment increase. The assessment of the microstructural alterations of white and grey matter in MS may shed light on mechanisms responsible for irreversible disability accumulation. In this paper, we examine the DTI analysis methods, the results obtained in the various tissues of the central nervous system, and correlations with clinical features and other MRI parameters. The adoption of DTI metrics to assess the outcome of prognostic measures may represent an extremely important step forward in the MS research field.
Objective:
To investigate the disease-altered structure–function relationship underlying the cognitive–postural interference (CPI) phenomenon in multiple sclerosis (MS).
Methods:
We measured postural ...sway of 96 patients and 48 sex-/age-matched healthy controls by force platform in quiet standing (single-task (ST)) while performing the Stroop test (dual-task (DT)) to estimate the dual-task cost (DTC) of balance. In patient group, binary T2 and T1 lesion masks and their corresponding lesion volumes were obtained from magnetic resonance imaging (MRI) of brain. Normalized brain volume (NBV) was also estimated by SIENAX. Correlations between DTC and lesion location were determined by voxel-based lesion symptom mapping (VLSM) analyses.
Results:
Patients had greater DTC than controls (p < 0.001). Among whole brain MRI metrics, only T1 lesion volume correlated with DTC (r = −0.27; p < 0.01). However, VLSM analysis did not reveal any association with DTC using T1 lesion masks. By contrast, we found clusters of T2 lesions in distinct anatomical regions (anterior and superior corona radiata, bilaterally) to be correlated with DTC (p < 0.01 false discovery rate (FDR)-corrected). A multivariable stepwise regression model confirmed findings from VLSM analysis. NBV did not contribute to fit the model.
Conclusion:
Our findings suggest that the CPI phenomenon in MS can be explained by disconnection along specific areas implicated in task-switching abilities and divided attention.
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.
Background:
Somatosensory temporal discrimination threshold (STDT) is altered in multiple sclerosis (MS). In healthy subjects (HS), voluntary movement modulates the STDT through mechanisms of ...subcortical sensory gating.
Objective:
With neurophysiological and magnetic resonance imaging (MRI) techniques, we investigated sensory gating and sensorimotor integration in MS.
Methods:
We recruited 38 relapsing-remitting multiple sclerosis (RR-MS) patients with no-to-mild disability and 33 HS. We tested STDT at rest and during index finger abductions and recorded the movement kinematics. Participants underwent a 3T MRI protocol.
Results:
Patients exhibited higher STDT values and performed slower finger movements than HS. During voluntary movement, STDT values increased in both groups, albeit to a lesser extent in patients, while the mean angular velocity of finger movements decreased in patients alone. Patients had a smaller volume of the thalamus, pallidum and caudate nucleus, and displayed higher mean diffusivity in the putamen, pallidum and thalamus. STDT correlated with thalamic volume while mean angular velocity correlated with putaminal volume. Changes in mean angular velocity during sensorimotor integration inversely correlated with mean diffusivity in the thalamus and pallidum. Changes in STDT and velocity were associated with fatigue score.
Conclusion:
Altered STDT and sensorimotor integration are related to structural damage in the thalamus and basal ganglia in MS and likely to affect motor performance.
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.
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