Lesions Causing Alice in Wonderland Syndrome Map to a Common Brain Network Linking Body and Size Perception.

OBJECTIVE: Alice in Wonderland syndrome (AIWS) profoundly affects human perception of size and scale, particularly regarding one's own body and the environment. Its neuroanatomical basis has remained elusive, partly because brain lesions causing AIWS can occur in different brain regions. Here, we aimed to determine if brain lesions causing AIWS map to a distributed brain network. METHODS: A retrospective case-control study analyzing 37 cases of lesion-induced AIWS identified through systematic literature review was conducted. Using resting-state functional connectome data from 1,000 healthy individuals, the whole-brain connections of each lesion were estimated and contrasted with those from a control dataset comprising 1,073 lesions associated with 25 other neuropsychiatric syndromes. Additionally, connectivity findings from lesion-induced AIWS cases were compared with functional neuroimaging results from 5 non-lesional AIWS cases. RESULTS: AIWS-associated lesions were located in various brain regions with minimal overlap (≤33%). However, the majority of lesions (≥85%) demonstrated shared connectivity to the right extrastriate body area, known to be selectively activated by viewing body part images, and the inferior parietal cortex, involved in size and scale judgements. This pattern was uniquely characteristic of AIWS when compared with other neuropsychiatric disorders (family-wise error-corrected p < 0.05) and consistent with functional neuroimaging observations in AIWS due to nonlesional causes (median correlation r = 0.56, interquartile range 0.24). INTERPRETATION: AIWS-related perceptual distortions map to one common brain network, encompassing regions critical for body representation and size-scale processing. These findings lend insight into the neuroanatomical localization of higher-order perceptual functions, and may inform future therapeutic strategies for perceptual disorders. ANN NEUROL 2024.

The brief repeatable battery of neuropsychological tests (BRB-N) version a: update of Italian normative data from the Italian Neuroimaging Network Initiative (INNI).

BACKGROUND: Cognitive impairment is a common clinical manifestation in people with multiple sclerosis (PwMS) and significantly impacts patients' quality life. Cognitive assessment is crucial for treatment decisions and understanding disease progression. Several neuropsychological batteries are used in MS, including the Brief Repeatable Battery of Neuropsychological Tests (BRB-N), Minimal Assessment of Cognitive Function in MS (MACFIMS), and Brief International Cognitive Assessment for MS (BICAMS). However, normative data for BRB-N version A in Italy are outdated. OBJECTIVES: To revise and update normative data for the BRB-N version A in the Italian population. METHODS: From the Italian Neuroimaging Network Initiative (INNI) database, we retrospectively selected 342 healthy subjects (172 males and 170 females) evaluated at four Italian INNI-affiliated sites (Milan, Siena, Rome, Naples). The subjects underwent neuropsychological assessment using the BRB-N version A. Regression-based method relying on scaled scores was used to calculate demographic correction procedures. RESULTS: No significant differences were found in age, education, and sex distribution among the four sites (p ≥ 0.055). Regression analysis provided normative data to calculate demographically adjusted z-scores for each BRB-N version A test. DISCUSSION: This study provides updated normative data for the BRB-N version A in the Italian population. The use of a regression-based method and scaled scores ensures consistency with other neuropsychological batteries commonly used in Italy, namely MACFIMS and BICAMS. The availability of updated normative data increases reliability of neuropsychological assessment of cognitive function in Italian PwMS and other clinical populations using BRB-N version A, providing valuable insights for both clinical and research applications.

Mapping Essential Tremor to a Common Brain Network Using Functional Connectivity Analysis.

BACKGROUND AND OBJECTIVES: The cerebello-thalamo-cortical circuit plays a critical role in essential tremor (ET). However, abnormalities have been reported in multiple brain regions outside this circuit, leading to inconsistent characterization of ET pathophysiology. Here, we test whether these mixed findings in ET localize to a common functional network and whether this network has therapeutic relevance. METHODS: We conducted a systematic literature search to identify studies reporting structural or metabolic brain abnormalities in ET. We then used 'coordinate network mapping,' which leverages a normative connectome (n = 1,000) of resting-state fMRI data to identify regions commonly connected to findings across all studies. To assess whether these regions may be relevant for the treatment of ET, we compared our network with a therapeutic network derived from lesions that relieved ET. Finally, we investigated whether the functional connectivity of this ET symptom network is abnormal in an independent cohort of patients with ET as compared with healthy controls. RESULTS: Structural and metabolic brain abnormalities in ET were located in heterogeneous regions throughout the brain. However, these coordinates were connected to a common functional brain network, including the cerebellum, thalamus, motor cortex, precuneus, inferior parietal lobe, and insula. The cerebellum was identified as the hub of this network because it was the only brain region that was both functionally connected to the findings of over 90% of studies and significantly different in connectivity compared with a control data set of other movement disorders. This network was strikingly similar to the therapeutic network derived from lesions improving ET, with key regions aligning in the thalamus and cerebellum. Furthermore, positive functional connectivity between the cerebellar network hub and the sensorimotor cortices was significantly reduced in patients with ET compared with healthy controls, and connectivity within this network was correlated with tremor severity and cognitive functioning. DISCUSSION: These findings suggest that the cerebellum is the central hub of a network commonly connected to structural and metabolic abnormalities in ET. This network may have therapeutic utility in refining and informing new targets for neuromodulation of ET.

Cortico-Subcortical White Matter Bundle Changes in Cervical Dystonia and Blepharospasm.

Dystonia is thought to be a network disorder due to abnormalities in the basal ganglia-thalamo-cortical circuit. We aimed to investigate the white matter (WM) microstructural damage of bundles connecting pre-defined subcortical and cortical regions in cervical dystonia (CD) and blepharospasm (BSP). Thirty-five patients (17 with CD and 18 with BSP) and 17 healthy subjects underwent MRI, including diffusion tensor imaging (DTI). Probabilistic tractography (BedpostX) was performed to reconstruct WM tracts connecting the globus pallidus, putamen and thalamus with the primary motor, primary sensory and supplementary motor cortices. WM tract integrity was evaluated by deriving their DTI metrics. Significant differences in mean, radial and axial diffusivity between CD and HS and between BSP and HS were found in the majority of the reconstructed WM tracts, while no differences were found between the two groups of patients. The observation of abnormalities in DTI metrics of specific WM tracts suggests a diffuse and extensive loss of WM integrity as a common feature of CD and BSP, aligning with the increasing evidence of microstructural damage of several brain regions belonging to specific circuits, such as the basal ganglia-thalamo-cortical circuit, which likely reflects a common pathophysiological mechanism of focal dystonia.

White and gray matter alterations in de novo PD patients: which matter most?

OBJECTIVES: This paper aimed to identify white matter (WM) and gray matter (GM) abnormalities in a sample of early PD patients, and their correlations with motor and non-motor symptom severity. METHODS: We enrolled 62 de novo PD patients and 31 healthy subjects. Disease severity and non-motor symptom burden were assessed by the Unified Parkinson's Disease Rating Scale part III and the Non-Motor Symptoms Scale, respectively. Cognitive performance was assessed using Montreal Cognitive Assessment and Frontal Assessment Battery. All subjects underwent a 3-Tesla MRI protocol. MRI analyses included tract-based spatial statistics, cortical thickness, and subcortical and cerebellar volumetry. RESULTS: In comparison to control subjects, PD patients exhibited lower fractional anisotropy and higher mean, axial, and radial diffusivity in most WM bundles, including corticospinal tracts, the internal and external capsule, the anterior and posterior thalamic radiations, the genu and body of the corpus callosum, cerebellar peduncles, and superior and inferior longitudinal and fronto-occipital fasciculi. Correlations between Montreal Cognitive Assessment scores and fractional anisotropy values in the right posterior thalamic radiation, left superior corona radiata, right inferior-fronto-occipital fasciculus, left inferior longitudinal fasciculus, bilateral anterior thalamic radiations, and bilateral superior longitudinal fasciculi were found. Smaller cerebellar volumes in early PD patients in the left and right crus I were also found. No GM changes were present in subcortical or cortical regions. CONCLUSION: The combined evaluation of WM and GM in the same patient sample demonstrates that WM microstructural abnormalities precede GM structural changes in early PD patients.

Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set.

Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T-MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS.

Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative.

The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.

White matter alterations in drug-naïve children with Tourette syndrome and obsessive-compulsive disorder.

Tourette syndrome (TS) and early-onset obsessive-compulsive disorder (OCD) are frequently associated and conceptualized as distinct phenotypes of a common disease spectrum. However, the nature of their relationship is still largely unknown on a pathophysiological level. In this study, early structural white matter (WM) changes investigated through diffusion tensor imaging (DTI) were compared across four groups of drug-naïve children: TS-pure (n = 16), TS+OCD (n = 14), OCD (n = 10), and 11 age-matched controls. We analyzed five WM tracts of interest, i.e., cortico-spinal tract (CST), anterior thalamic radiations (ATR), inferior longitudinal fasciculus (ILF), corpus callosum (CC), and cingulum and evaluated correlations of DTI changes to symptom severity. Compared to controls, TS-pure and TS+OCD showed a comparable pattern of increased fractional anisotropy (FA) in CST, ATR, ILF and CC, with FA changes displaying negative correlation to tic severity. Conversely, in OCD, FA decreased in all WM tracts (except for the cingulum) compared to controls and negatively correlated to symptoms. We demonstrate different early WM microstructural alterations in children with TS-pure/TS+OCD as opposed to OCD. Our findings support the conceptualization of TS+OCD as a subtype of TS while suggesting that OCD is characterized by independent pathophysiological mechanisms affecting WM development.

Investigating Functional Network Abnormalities and Associations With Disability in Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: In multiple sclerosis (MS), functional networks undergo continuous reconfiguration and topography changes over the disease course. In this study, we aimed to investigate functional network to pography abnormalities in MS and their association with disease phenotype, clinical and cognitive disability, and structural MRI damage. METHODS: This is a multicenter cross-sectional study. Enrolled participants performed MRI and neurologic and neuropsychological assessment. Network topography was assessed on resting state fMRI data using degree centrality, which counted the number of functional connections of each gray matter voxel with the rest of the brain. SPM12 age-adjusted, sex-adjusted, scanner-adjusted, framewise displacement, and gray matter-volume adjusted analysis of variance and multivariable regressions were used (p < 0.05, family-wise error [FWE] corrected). RESULTS: We enrolled 971 patients with MS (624 female patients; mean age = 43.1 ± 11.8 years; 47 clinically isolated syndrome [CIS], 704 relapsing-remitting MS [RRMS], 145 secondary progressive MS [SPMS], and 75 primary progressive MS [PPMS]) and 330 healthy controls (186 female patients; mean age = 41.2 ± 13.3 years). Patients with MS showed reduced centrality in the salience and sensorimotor networks as well as increased centrality in the default-mode network vs controls (p < 0.05, FWE). Abnormal centrality was already found in CIS vs controls and in RRMS vs CIS (p < 0.001, uncorrected); however, it became more severe in SPMS vs RRMS (p < 0.05, FWE) and in PPMS vs controls (p < 0.001, uncorrected). Cognitively impaired patients (39%) showed reduced centrality in the salience network and increased centrality in the default-mode network vs cognitively preserved patients (p < 0.001, conjunction analysis). More severe disability correlated with increased centrality in the right precuneus (r = 0.18, p < 0.05 FWE). Higher T2 lesion volume and brain/gray matter atrophy were associated with reduced centrality in the bilateral insula and cerebellum (r = range -0.17/-0.15 and 0.26/0.28, respectively; p < 0.05, FWE). Higher brain/gray matter atrophy was also associated with increased centrality in the default-mode network (r = range -0.31/-0.22, p < 0.05, FWE). DISCUSSION: Patients with MS presented with reduced centrality in the salience and primary sensorimotor networks and increased centrality in the default-mode network. Centrality abnormalities were specific for different disease phenotypes and associated with clinical and cognitive disability, hence suggesting that voxel-wise centrality analysis may reflect pathologic substrates underpinning disability accrual.

Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques.

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.

How Dual-Energy Contrast-Enhanced Spectral Mammography Can Provide Useful Clinical Information About Prognostic Factors in Breast Cancer Patients: A Systematic Review of Literature.

Introduction: In the past decade, a new technique derived from full-field digital mammography has been developed, named contrast-enhanced spectral mammography (CESM). The aim of this study was to define the association between CESM findings and usual prognostic factors, such as estrogen receptors, progesterone receptors, HER2, and Ki67, in order to offer an updated overview of the state of the art for the early differential diagnosis of breast cancer and following personalized treatments. Materials and Methods: According to the PRISMA guidelines, two electronic databases (PubMed and Scopus) were investigated, using the following keywords: breast cancer AND (CESM OR contrast enhanced spectral mammography OR contrast enhanced dual energy mammography) AND (receptors OR prognostic factors OR HER2 OR progesterone OR estrogen OR Ki67). The search was concluded in August 2021. No restriction was applied to publication dates. Results: We obtained 28 articles from the research in PubMed and 114 articles from Scopus. After the removal of six replicas that were counted only once, out of 136 articles, 37 articles were reviews. Eight articles alone have tackled the relation between CESM imaging and ER, PR, HER2, and Ki67. When comparing radiological characterization of the lesions obtained by either CESM or contrast-enhanced MRI, they have a similar association with the proliferation of tumoral cells, as expressed by Ki-67. In CESM-enhanced lesions, the expression was found to be 100% for ER and 77.4% for PR, while moderate or high HER2 positivity was found in lesions with non-mass enhancement and with mass closely associated with a non-mass enhancement component. Conversely, the non-enhancing breast cancer lesions were not associated with any prognostic factor, such as ER, PR, HER2, and Ki67, which may be associated with the probability of showing enhancement. Radiomics on CESM images has the potential for non-invasive characterization of potentially heterogeneous tumors with different hormone receptor status. Conclusions: CESM enhancement is associated with the proliferation of tumoral cells, as well as to the expression of estrogen and progesterone receptors. As CESM is a relatively young imaging technique, a few related works were found; this may be due to the "off-label" modality. In the next few years, the role of CESM in breast cancer diagnostics will be more thoroughly investigated.

Eating Hubs in Multiple Sclerosis: Exploring the Relationship Between Mediterranean Diet and Disability Status in Italy.

Background: Multiple Sclerosis (MS) is a complex disease in which multiple factors contribute to disability accrual. Mediterranean Diet (MeDi) has shown beneficial effects across neurodegenerative diseases. We hypothesize that specific food habits, rather than global adherence to MeDi, might impact on MS. We aimed to (i) evaluate differences in adherence to MeDi between people living with MS (PwMS) and healthy controls (HC); (ii) characterize eating patterns in PwMS and HC, identifying the most influential MeDi items for each group by the use of network analysis; (iii) explore the relationship between patients' eating habits and disability. Materials and Methods: In this cross-sectional study, we consecutively recruited 424 PwMS and 165 matched HC. Data were obtained through the administration of self-reported questionnaires. Expanded Disability Status Scale (EDSS) and Fatigue Severity Scale (FSS) were evaluated in the MS population. We performed between-groups comparisons via unpaired two-sample t-test and X2 test as appropriate. We calculated food networks in both MS cases and HC using and tested the association between hub nodes and disability. Finally, we conducted a post-hoc analysis, investigating the relationship between food items, lifestyle factors (smoking, exercise) and clinical outcomes. Results: Most participants adhered sufficiently to MeDi. Exploring each group separately, fruit, vegetables, cereal, and fish were identified as hubs in PwMS, while meat and alcohol were identified as hubs in HC. Hubs were all inter-correlated, indicating that eating habits of PwMS include a large intake of all the foods identified as hubs. EDSS was predicted by the intake of vegetables (beta = -0.36, p < 0.03) and fish (beta = -0.34, p < 0.02). The model including smoking pack/year, International Physical Activity Questionnaire (IPAQ) score and intake of "negative foods" predicted 6% of the variance in EDSS (p < 0.001), while the model including smoking pack/year and IPAQ score predicted 4% of the variance in FSS (p < 0.001). Conclusions: We identified a sufficient adherence to MeDi in our population. PwMS showed overall a healthier dietary pattern than HC. Vegetables and fish intake were associated with disability outcomes. Future longitudinal studies applying integrated approaches are needed to understand lifestyle added value to the use of standard pharmacological therapies.

Relation of sensorimotor and cognitive cerebellum functional connectivity with brain structural damage in patients with multiple sclerosis and no disability.

BACKGROUND AND PURPOSE: To investigate the relationship between the functional connectivity (FC) of the sensorimotor and cognitive cerebellum and measures of structural damage in patients with multiple sclerosis (MS) and no physical disability. METHODS: We selected 144 relapsing-remitting MS patients with an Expanded Disability Status Scale score of ≤1.5 and 98 healthy controls from the Italian Neuroimaging Network Initiative database. From multimodal 3T magnetic resonance imaging (MRI), including functional MRI at rest, we calculated lesion load, cortical thickness, and white matter, cortical gray matter, and caudate, putamen, thalamic, and cerebellar volumes. Voxel-wise FC of the sensorimotor and cognitive cerebellum was assessed with seed-based analysis, and multiple regression analysis was used to evaluate the relationship between FC and structural damage. RESULTS: Whole brain, white matter, caudate, putamen, and thalamic volumes were reduced in patients compared to controls, whereas cortical gray matter was not significantly different in patients versus controls. Both the sensorimotor and cognitive cerebellum showed a widespread pattern of increased and decreased FC that were negatively associated with structural measures, indicating that the lower the FC, the greater the tissue loss. Lastly, among multiple structural measures, cortical gray matter and white matter volumes were the best predictors of cerebellar FC alterations. CONCLUSIONS: Increased and decreased cerebellar FC with several brain areas coexist in MS patients with no disability. Our data suggest that white matter loss hampers FC, whereas, in the absence of atrophy, cortical volume represents the framework for FC to increase.

Focal Dystonia: Functional Connectivity Changes in Cerebellar-Basal Ganglia-Cortical Circuit and Preserved Global Functional Architecture.

BACKGROUND AND OBJECTIVES: Neuroimaging studies suggest that changes in the cerebellar-basal ganglia-thalamo-cortical sensorimotor circuit are a pathophysiologic feature of focal dystonia. However, it remains unclear whether structural and functional alterations vary in different forms of focal dystonia. Thus, in patients with cervical dystonia (CD) and blepharospasm (BSP), we aimed to investigate structural damage and resting-state functional alterations using whole-brain and seed-based approaches to test the hypothesis of possible functional connectivity (FC) alterations in specific circuits, including the cerebellum, basal ganglia, and cerebral cortex, in the context of preserved global FC. METHODS: In this cross-sectional study, we applied a multimodal 3T MRI protocol, including 3-dimensional T1-weighted images to extract brain volumes and cortical thickness, and fMRI at rest to study FC of the dentate nucleus and globus pallidus with a seed-based approach and whole-brain FC with a graph theory approach. RESULTS: This study included 33 patients (17 with CD [14 female] age 55.7 ± 10.1 years, 16 with BSP [11 female] age 62.9 ± 8.8 years) and 16 age- and sex-matched healthy controls (HC) (7 female) 54.3 ± 14.3 years if age. Patients with CD, patients with BSP, and HC did not differ in terms of cortical or subcortical volume. Compared to HC, both patients with CD and patients with BSP had a loss of dentate FC anticorrelation with the sensorimotor cortex. Patients with CD and those with BSP showed increased pallidal FC with the cerebellum, supplementary motor area, and prefrontal cortices with respect to HC. Increased dentate FC with the cerebellum and thalamus and increased pallidal FC with the bilateral thalamus, sensorimotor and temporo-occipital cortices, and right putamen were present in patients with CD but not patients with BSP compared to HC. Measures of global FC, that is, global efficiency and small-worldness, did not differ between patients and HC. DISCUSSION: Both patients with CD and those with BSP showed altered dentate and pallidal FC with regions belonging to the integrated cerebellar-basal ganglia-thalamo-cortical sensorimotor circuit, supporting the concept that focal dystonia is a disorder of specific networks and not merely a result of basal ganglia alterations in the context of a preserved whole-brain functional architecture. Differences in functional interplay among specific brain structures may distinguish CD and BSP.

The Cerebellum in Drug-naive Children with Tourette Syndrome and Obsessive-Compulsive Disorder.

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.

The Contribution of Neuroimaging to the Understanding of Essential Tremor Pathophysiology: a Systematic Review.

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.

Dalfampridine improves slowed processing speed in multiple sclerosis patients with mild motor disability: post hoc analysis of a randomized controlled trial.

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).

Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis.

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.

A matter of atrophy: differential impact of brain and spine damage on disability worsening in multiple sclerosis.

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.