In vivo demonstration of globotriaosylceramide brain accumulation in Fabry Disease using MR Relaxometry.

PURPOSE: How to measure brain globotriaosylceramide (Gb3) accumulation in Fabry Disease (FD) patients in-vivo is still an open challenge. The objective of this study is to provide a quantitative, non-invasive demonstration of this phenomenon using quantitative MRI (qMRI). METHODS: In this retrospective, monocentric cross-sectional study conducted from November 2015 to July 2018, FD patients and healthy controls (HC) underwent an MRI scan with a relaxometry protocol to compute longitudinal relaxation rate (R1) maps to evaluate gray (GM) and white matter (WM) lipid accumulation. In a subgroup of 22 FD patients, clinical (FAbry STabilization indEX -FASTEX- score) and biochemical (residual α-galactosidase activity) variables were correlated with MRI data. Quantitative maps were analyzed at both global ("bulk" analysis) and regional ("voxel-wise" analysis) levels. RESULTS: Data were obtained from 42 FD patients (mean age = 42.4 ± 12.9, M/F = 16/26) and 49 HC (mean age = 42.3 ± 16.3, M/F = 28/21). Compared to HC, FD patients showed a widespread increase in R1 values encompassing both GM (pFWE = 0.02) and WM (pFWE = 0.02) structures. While no correlations were found between increased R1 values and FASTEX score, a significant negative correlation emerged between residual enzymatic activity levels and R1 values in GM (r = -0.57, p = 0.008) and WM (r = -0.49, p = 0.03). CONCLUSIONS: We demonstrated the feasibility and clinical relevance of non-invasively assessing cerebral Gb3 accumulation in FD using MRI. R1 mapping might be used as an in-vivo quantitative neuroimaging biomarker in FD patients.

Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure.

OBJECTIVE: Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults. METHODS: Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid ß1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. RESULTS: AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect. INTERPRETATION: Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.

Assessing brain involvement in Fabry disease with deep learning and the brain-age paradigm.

While neurological manifestations are core features of Fabry disease (FD), quantitative neuroimaging biomarkers allowing to measure brain involvement are lacking. We used deep learning and the brain-age paradigm to assess whether FD patients' brains appear older than normal and to validate brain-predicted age difference (brain-PAD) as a possible disease severity biomarker. MRI scans of FD patients and healthy controls (HCs) from a single Institution were, retrospectively, studied. The Fabry stabilization index (FASTEX) was recorded as a measure of disease severity. Using minimally preprocessed 3D T1-weighted brain scans of healthy subjects from eight publicly available sources (N = 2160; mean age = 33 years [range 4-86]), we trained a model predicting chronological age based on a DenseNet architecture and used it to generate brain-age predictions in the internal cohort. Within a linear modeling framework, brain-PAD was tested for age/sex-adjusted associations with diagnostic group (FD vs. HC), FASTEX score, and both global and voxel-level neuroimaging measures. We studied 52 FD patients (40.6 ± 12.6 years; 28F) and 58 HC (38.4 ± 13.4 years; 28F). The brain-age model achieved accurate out-of-sample performance (mean absolute error = 4.01 years, R2 = .90). FD patients had significantly higher brain-PAD than HC (estimated marginal means: 3.1 vs. -0.1, p = .01). Brain-PAD was associated with FASTEX score (B = 0.10, p = .02), brain parenchymal fraction (B = -153.50, p = .001), white matter hyperintensities load (B = 0.85, p = .01), and tissue volume reduction throughout the brain. We demonstrated that FD patients' brains appear older than normal. Brain-PAD correlates with FD-related multi-organ damage and is influenced by both global brain volume and white matter hyperintensities, offering a comprehensive biomarker of (neurological) disease severity.

CHARON: An Imaging-Based Diagnostic Algorithm to Navigate Through the Sea of Hereditary Degenerative Ataxias.

The complexity in diagnosing hereditary degenerative ataxias lies not only in their rarity, but also in the variety of different genetic conditions that can determine sometimes similar and overlapping clinical findings. In this light, Magnetic Resonance Imaging (MRI) plays a key role in the evaluation of these conditions, being a fundamental diagnostic tool needed not only to exclude other causes determining the observed clinical phenotype, but also to proper guide to an adequate genetic testing. Here, we propose an MRI-based diagnostic algorithm named CHARON (Characterization of Hereditary Ataxias Relying On Neuroimaging), to help in disentangling among the numerous, and apparently very similar, hereditary degenerative ataxias. Being conceived from a neuroradiological standpoint, it is based primarily on an accurate evaluation of the observed MRI findings, with the first and most important being the pattern of cerebellar atrophy. Along with the evaluation of the presence, or absence, of additional signal changes and/or supratentorial involvement, CHARON allows for the identification of a small groups of ataxias sharing similar imaging features. The integration of additional MRI findings, demographic, clinical and laboratory data allow then for the identification of typical, and in some cases pathognomonic, phenotypes of hereditary ataxias.

The impact of image contrast, resolution and reader expertise on black hole identification in Multiple Sclerosis.

OBJECTIVES: In the neuroradiological work-up of Multiple Sclerosis (MS), the detection of "black holes" (BH) represent an information of undeniable importance. Nevertheless, different sequences can be used in clinical practice to evaluate BH in MS. Aim of this study was to investigate the possible impact of different sequences, resolutions, and levels of expertise on the intra- and inter-rater reliability identification of BH in MS. METHODS: Brain MRI scans of 85 MS patients (M/F = 22/63; mean age = 36.0 ± 10.2 years) were evaluated in this prospective single-center study. The acquisition protocol included a 3 mm SE-T1w sequence, a 1 mm 3D-GrE-T1w sequence from which a resliced 3 mm sequence was also obtained. Images were evaluated independently by two readers of different expertise at baseline and after a wash-out period of 30 days. The intraclass correlation coefficient (ICC) was calculated as an index of intra and inter-reader reliability. RESULTS: For both readers, the intra-reader ICC analysis showed that the 3 mm SE-T1w and 3 mm resliced GrE-T1w images achieved an excellent performance (both with an ICC ≥ 0.95), while 1 mm 3D-GrE-T1w scans achieved a moderate one (ICC < 0.90). The inter-reader analysis showed that each of the three sequences achieved a moderate performance (all ICCs < 0.90). CONCLUSIONS: The 1 mm 3D-GrE-T1w sequence seems to be prone to a greater intra-reader variability compared to the 3 mm SE-T1w, with this effect being driven by the higher spatial resolution of the first sequence. To ensure reliability levels comparable with the standard SE-T1w in BH count, an assessment on a 3 mm resliced GrE-T1w sequence should be recommended.

Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis.

Importance: Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective: To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants: This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures: MS/CIS vs non-MS conditions. Main Outcomes and Measures: Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results: The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance: The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.

Visual Snow Syndrome Improves With Modulation of Resting-State Functional MRI Connectivity After Mindfulness-Based Cognitive Therapy: An Open-Label Feasibility Study.

BACKGROUND: Visual snow syndrome (VSS) is associated with functional connectivity (FC) dysregulation of visual networks (VNs). We hypothesized that mindfulness-based cognitive therapy, customized for visual symptoms (MBCT-vision), can treat VSS and modulate dysfunctional VNs. METHODS: An open-label feasibility study for an 8-week MBCT-vision treatment program was conducted. Primary (symptom severity; impact on daily life) and secondary (WHO-5; CORE-10) outcomes at Week 9 and Week 20 were compared with baseline. Secondary MRI outcomes in a subcohort compared resting-state functional and diffusion MRI between baseline and Week 20. RESULTS: Twenty-one participants (14 male participants, median 30 years, range 22-56 years) recruited from January 2020 to October 2021. Two (9.5%) dropped out. Self-rated symptom severity (0-10) improved: baseline (median [interquartile range (IQR)] 7 [6-8]) vs Week 9 (5.5 [3-7], P = 0.015) and Week 20 (4 [3-6], P < 0.001), respectively. Self-rated impact of symptoms on daily life (0-10) improved: baseline (6 [5-8]) vs Week 9 (4 [2-5], P = 0.003) and Week 20 (2 [1-3], P < 0.001), respectively. WHO-5 Wellbeing (0-100) improved: baseline (median [IQR] 52 [36-56]) vs Week 9 (median 64 [47-80], P = 0.001) and Week 20 (68 [48-76], P < 0.001), respectively. CORE-10 Distress (0-40) improved: baseline (15 [12-20]) vs Week 9 (12.5 [11-16.5], P = 0.003) and Week 20 (11 [10-14], P = 0.003), respectively. Within-subject fMRI analysis found reductions between baseline and Week 20, within VN-related FC in the i) left lateral occipital cortex (size = 82 mL, familywise error [FWE]-corrected P value = 0.006) and ii) left cerebellar lobules VIIb/VIII (size = 65 mL, FWE-corrected P value = 0.02), and increases within VN-related FC in the precuneus/posterior cingulate cortex (size = 69 mL, cluster-level FWE-corrected P value = 0.02). CONCLUSIONS: MBCT-vision was a feasible treatment for VSS, improved symptoms and modulated FC of VNs. This study also showed proof-of-concept for intensive mindfulness interventions in the treatment of neurological conditions.

A Review of Brain and Pituitary Gland MRI Findings in Patients with Ataxia and Hypogonadism.

The association of cerebellar ataxia and hypogonadism occurs in a heterogeneous group of disorders, caused by different genetic mutations often associated with a recessive inheritance. In these patients, magnetic resonance imaging (MRI) plays a pivotal role in the diagnostic workflow, with a variable involvement of the cerebellar cortex, alone or in combination with other brain structures. Neuroimaging involvement of the pituitary gland is also variable. Here, we provide an overview of the main clinical and conventional brain and pituitary gland MRI imaging findings of the most common genetic mutations associated with the clinical phenotype of ataxia and hypogonadism, with the aim of helping neuroradiologists in the identification of these disorders.

Exploring the relation between reserve and fatigue in multiple sclerosis.

INTRODUCTION: Intellectual enrichment and brain reserve modulate the expression of cognitive and motor disability in multiple sclerosis (MS). Their association with fatigue, one of the most debilitating and common symptoms of MS, has never been explored. MATERIALS AND METHODS: Forty-eight MS patients underwent clinical and MRI examination at baseline and after 1 year. Physical and cognitive MS-related fatigue were evaluated via Modified Fatigue Impact subscales (MFIS-P and MFIS-C). Differences in reserve indexes between fatigued and non-fatigued patients were tested. The relationship between clinico-demographic features, global brain structural damage, indexes of reserve (age-adjusted intracranial volume and cognitive reserve index) and fatigue were tested via correlations and hierarchical linear/binary logistic regression, to predict MFIS-P and MFIS-C (at baseline) or new-onset fatigue and meaningful worsening in MFIS (at follow-up). RESULTS: At baseline, although a significant difference was identified for cognitive reserve questionnaire between fatigued and non-fatigued patients (18.19 ± 4.76 versus 15.15 ± 3.56, p = 0.015), only depression accounted for significant variance in MFIS-P and MFIS-C (R2=0.248, p = 0.002; R2=0.252, p<0.001). MFIS-T, MFIS-P and MFIS-C changes over time were associated to depression changes over time (r = 0.56, r = 0.55, and r = 0.57, respectively; all p<0.001). Indexes of reserve did not differ between non-fatigued patients and patients developing new-onset fatigue at follow-up. None of the baseline features was able to predict the new-onset fatigue or meaningful worsening in MFIS at follow-up. CONCLUSIONS: Among the explored features, only depression was strongly associated to both physical and cognitive fatigue. Intellectual enrichment and brain reserve did not seem to affect fatigue symptoms in MS patients.

Neural substrates of verbal memory impairment in schizophrenia: A multimodal connectomics study.

While verbal memory is among the most compromised cognitive domains in schizophrenia (SZ), its neural substrates remain elusive. Here, we explored the structural and functional brain network correlates of verbal memory impairment in SZ. We acquired diffusion and resting-state functional MRI data of 49 SZ patients, classified as having preserved (VMP, n = 22) or impaired (VMI, n = 26) verbal memory based on the List Learning task, and 55 healthy controls (HC). Structural and functional connectivity matrices were obtained and analyzed to assess associations with disease status (SZ vs. HC) and verbal memory impairment (VMI vs. VMP) using two complementary data-driven approaches: threshold-free network-based statistics (TFNBS) and hybrid connectivity independent component analysis (connICA). TFNBS showed altered connectivity in SZ patients compared with HC (p < .05, FWER-corrected), with distributed structural changes and functional reorganization centered around sensorimotor areas. Specifically, functional connectivity was reduced within the visual and somatomotor networks and increased between visual areas and associative and subcortical regions. Only a tiny cluster of increased functional connectivity between visual and bilateral parietal attention-related areas correlated with verbal memory dysfunction. Hybrid connICA identified four robust traits, representing fundamental patterns of joint structural-functional connectivity. One of these, mainly capturing the functional connectivity profile of the visual network, was significantly associated with SZ (HC vs. SZ: Cohen's d = .828, p < .0001) and verbal memory impairment (VMP vs. VMI: Cohen's d = -.805, p = .01). We suggest that aberrant connectivity of sensorimotor networks may be a key connectomic signature of SZ and a putative biomarker of SZ-related verbal memory impairment, in consistency with bottom-up models of cognitive disruption.

Using The Virtual Brain to study the relationship between structural and functional connectivity in patients with multiple sclerosis: a multicenter study.

The relationship between structural connectivity (SC) and functional connectivity (FC) captured from magnetic resonance imaging, as well as its interaction with disability and cognitive impairment, is not well understood in people with multiple sclerosis (pwMS). The Virtual Brain (TVB) is an open-source brain simulator for creating personalized brain models using SC and FC. The aim of this study was to explore SC-FC relationship in MS using TVB. Two different model regimes have been studied: stable and oscillatory, with the latter including conduction delays in the brain. The models were applied to 513 pwMS and 208 healthy controls (HC) from 7 different centers. Models were analyzed using structural damage, global diffusion properties, clinical disability, cognitive scores, and graph-derived metrics from both simulated and empirical FC. For the stable model, higher SC-FC coupling was associated with pwMS with low Single Digit Modalities Test (SDMT) score (F=3.48, P$\lt$0.05), suggesting that cognitive impairment in pwMS is associated with a higher SC-FC coupling. Differences in entropy of the simulated FC between HC, high and low SDMT groups (F=31.57, P$\lt$1e-5), show that the model captures subtle differences not detected in the empirical FC, suggesting the existence of compensatory and maladaptive mechanisms between SC and FC in MS.

Clinical correlates of R1 relaxometry and magnetic susceptibility changes in multiple sclerosis: a multi-parameter quantitative MRI study of brain iron and myelin.

OBJECTIVES: The clinical impact of brain microstructural abnormalities in multiple sclerosis (MS) remains elusive. We aimed to characterize the topography of longitudinal relaxation rate (R1) and quantitative susceptibility (χ) changes, as indices of iron and myelin, together with brain atrophy, and to clarify their contribution to cognitive and motor disability in MS. METHODS: In this cross-sectional study, voxel-based morphometry, and voxel-based quantification analyses of R1 and χ maps were conducted in gray matter (GM) and white matter (WM) of 117 MS patients and 53 healthy controls. Voxel-wise between-group differences were assessed with nonparametric permutation tests, while correlations between MRI metrics and clinical variables (global disability, cognitive and motor performance) were assessed both globally and voxel-wise within clusters emerging from the between-group comparisons. RESULTS: MS patients showed widespread R1 decrease associated with more limited modifications of χ, with atrophy mainly involving deep GM, posterior and infratentorial regions (p < 0.02). While R1 and χ showed a parallel reduction in several WM tracts (p < 0.001), reduced GM R1 values (p < 0.001) were associated with decreased thalamic χ (p < 0.001) and small clusters of increased χ in the caudate nucleus and prefrontal cortex (p < 0.02). In addition to the atrophy, χ values in the cingulum and corona radiata correlated with global disability and motor performance, while focal demyelination correlated with cognitive performance (p < 0.04). CONCLUSIONS: We confirmed the presence of widespread R1 changes, involving both GM and WM, and atrophy in MS, with less extensive modifications of tissue χ. While atrophy and χ changes are related to global and motor disability, R1 changes are meaningful correlates of cognition. KEY POINTS: • Compared to healthy controls, multiple sclerosis patients showed R1 and χ changes suggestive of iron increase within the basal ganglia and reduced iron and myelin content within (subnuclei of) the thalamus. • Thalamic volume and χ changes significantly predicted clinical disability, as well as pulvinar R1 and χ changes, independently from atrophy. • Atrophy-independent R1 and χ changes, suggestive of thalamic iron and myelin depletion, may represent a sensitive marker of subclinical inflammation.

Altered Patterns of Brain Glucose Metabolism Involve More Extensive and Discrete Cortical Areas in Treatment-resistant Schizophrenia Patients Compared to Responder Patients and Controls: Results From a Head-to-Head 2-[18F]-FDG-PET Study.

BACKGROUND AND HYPOTHESIS: Treatment resistant schizophrenia (TRS) affects almost 30% of patients with schizophrenia and has been considered a different phenotype of the disease. In vivo characterization of brain metabolic patterns associated with treatment response could contribute to elucidate the neurobiological underpinnings of TRS. Here, we used 2-[18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) to provide the first head-to-head comparative analysis of cerebral glucose metabolism in TRS patients compared to schizophrenia responder patients (nTRS), and controls. Additionally, we investigated, for the first time, the differences between clozapine responders (Clz-R) and non-responders (Clz-nR). STUDY DESIGN: 53 participants underwent FDG-PET studies (41 patients and 12 controls). Response to conventional antipsychotics and to clozapine was evaluated using a standardized prospective procedure based on PANSS score changes. Maps of relative brain glucose metabolism were processed for voxel-based analysis using Statistical Parametric Mapping software. STUDY RESULTS: Restricted areas of significant bilateral relative hypometabolism in the superior frontal gyrus characterized TRS compared to nTRS. Moreover, reduced parietal and frontal metabolism was associated with high PANSS disorganization factor scores in TRS (P < .001 voxel level uncorrected, P < .05 cluster level FWE-corrected). Only TRS compared to controls showed significant bilateral prefrontal relative hypometabolism, more extensive in CLZ-nR than in CLZ-R (P < .05 voxel level FWE-corrected). Relative significant hypermetabolism was observed in the temporo-occipital regions in TRS compared to nTRS and controls. CONCLUSIONS: These data indicate that, in TRS patients, altered metabolism involved discrete brain regions not found affected in nTRS, possibly indicating a more severe disrupted functional brain network associated with disorganization symptoms.

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.

Structural disconnection and functional reorganization in Fabry disease: a multimodal MRI study.

Central nervous system involvement in Fabry disease, a rare systemic X-linked lysosomal storage disorder, is characterized by the presence of heterogeneous but consistent functional and microstructural changes. Nevertheless, knowledge about the degree and extension of macro-scale brain connectivity modifications is to date missing. In this work, we performed connectomic analyses of diffusion and resting-state functional MRI to investigate changes of both structural and functional brain organization in Fabry disease, as well as to explore the relationship between the two and their clinical correlates. In this retrospective cross-sectional study, 46 patients with Fabry disease (28F, 42.2 ± 13.2years) and 49 healthy controls (21F, 42.3 ± 16.3years) were included. All subjects underwent an MRI examination including anatomical, diffusion and resting-state functional sequences. Images were processed to obtain quantitative structural and functional connectomes, where the connections between regions of interest were weighted by the total intra-axonal signal contribution of the corresponding bundle and by the correlation between blood-oxygen level-dependent time series, respectively. We explored between-group differences in terms of both global network properties, expressed with graph measures and specific connected subnetworks, identified using a network-based statistics approach. As exploratory analyses, we also investigated the possible association between cognitive performance and structural and functional connectome modifications at both global and subnetwork level in a subgroup of patients (n = 11). Compared with healthy controls, patients with Fabry disease showed a significantly reduced global efficiency (P = 0.005) and mean strength (P < 0.001) in structural connectomes, together with an increased modularity (P = 0.005) in functional networks. As for the network-based statistics analysis, a subnetwork with decreased structural connectivity in patients with Fabry disease compared with healthy controls emerged, with eight nodes mainly located at the level of frontal or deep grey-matter areas. When probing the relation between altered global network metrics and neuropsychological tests, correlations emerged between the structural and functional disruption with results at verbal and working memory tests, respectively. Furthermore, structural disruption at subnetwork level was associated with worse executive functioning, with a significant moderation effect of functional changes suggesting a compensation mechanism. Taken together, these results further expand the current knowledge about brain involvement in Fabry disease, showing widespread structural disconnection and functional reorganization, primarily sustained by loss in axonal integrity and correlating with cognitive performance.

Relationship between high-frequency activity in the cortical sensory and the motor hand areas, and their myelin content.

BACKGROUND: The human primary sensory (S1) and primary motor (M1) hand areas feature high-frequency neuronal responses. Electrical nerve stimulation evokes high-frequency oscillations (HFO) at around 650 Hz in the contralateral S1. Likewise, transcranial magnetic stimulation (TMS) of M1 can evoke a series of descending volleys in the corticospinal pathway that can be detected non-invasively with a paired-pulse TMS protocol, called short interval intracortical facilitation (SICF). SICF features several peaks of facilitation of motor evoked potentials in contralateral hand muscles, which are separated by inter-peak intervals resembling HFO rhythmicity. HYPOTHESIS: In this study, we tested the hypothesis that the individual expressions of HFO and SICF are tightly related to each other and to the regional myelin content in the sensorimotor cortex. METHODS: In 24 healthy volunteers, we recorded HFO and SICF, and, in a subgroup of 20 participants, we mapped the cortical myelin content using the ratio between the T1- and T2-weighted MRI signal as read-out. RESULTS: The individual frequencies and magnitudes of HFO and SICF curves were tightly correlated: the intervals between the first and second peak of cortical HFO and SICF showed a positive linear relationship (r = 0.703, p < 0.001), while their amplitudes were inversely related (r = -0.613, p = 0.001). The rhythmicity, but not the magnitude of the high-frequency responses, was related to the cortical myelin content: the higher the cortical myelin content, the shorter the inter-peak intervals of HFO and SICF. CONCLUSION: The results confirm a tight functional relationship between high-frequency responses in S1 (i.e., HFO) and M1 (i.e., as measured with SICF). They also establish a link between the degree of regional cortical myelination and the expression of high-frequency responses in the human sensorimotor cortex, giving further the opportunity to infer their generators.

Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach.

OBJECTIVES: To stratify patients with multiple sclerosis (pwMS) based on brain MRI-derived volumetric features using unsupervised machine learning. METHODS: The 3-T brain MRIs of relapsing-remitting pwMS including 3D-T1w and FLAIR-T2w sequences were retrospectively collected, along with Expanded Disability Status Scale (EDSS) scores and long-term (10 ± 2 years) clinical outcomes (EDSS, cognition, and progressive course). From the MRIs, volumes of demyelinating lesions and 116 atlas-defined gray matter regions were automatically segmented and expressed as z-scores referenced to external populations. Following feature selection, baseline MRI-derived biomarkers entered the Subtype and Stage Inference (SuStaIn) algorithm, which estimates subgroups characterized by distinct patterns of biomarker evolution and stages within subgroups. The trained model was then applied to longitudinal MRIs. Stability of subtypes and stage change over time were assessed via Krippendorf's α and multilevel linear regression models, respectively. The prognostic relevance of SuStaIn classification was assessed with ordinal/logistic regression analyses. RESULTS: We selected 425 pwMS (35.9 ± 9.9 years; F/M: 301/124), corresponding to 1129 MRI scans, along with healthy controls (N = 148; 35.9 ± 13.0 years; F/M: 77/71) and external pwMS (N = 80; 40.4 ± 11.9 years; F/M: 56/24) as reference populations. Based on 11 biomarkers surviving feature selection, two subtypes were identified, designated as "deep gray matter (DGM)-first" subtype (N = 238) and "cortex-first" subtype (N = 187) according to the atrophy pattern. Subtypes were consistent over time (α = 0.806), with significant annual stage increase (b = 0.20; p < 0.001). EDSS was associated with stage and DGM-first subtype (p ≤ 0.02). Baseline stage predicted long-term disability, transition to progressive course, and cognitive impairment (p ≤ 0.03), with the latter also associated with DGM-first subtype (p = 0.005). CONCLUSIONS: Unsupervised learning modelling of brain MRI-derived volumetric features provides a biologically reliable and prognostically meaningful stratification of pwMS. KEY POINTS: • The unsupervised modelling of brain MRI-derived volumetric features can provide a single-visit stratification of multiple sclerosis patients. • The so-obtained classification tends to be consistent over time and captures disease-related brain damage progression, supporting the biological reliability of the model. • Baseline stratification predicts long-term clinical disability, cognition, and transition to secondary progressive course.

The central vein sign helps in differentiating multiple sclerosis from its mimickers: lessons from Fabry disease.

OBJECTIVES: Although the use of specific MRI criteria has significantly increased the diagnostic accuracy of multiple sclerosis (MS), reaching a correct neuroradiological diagnosis remains a challenging task, and therefore the search for new imaging biomarkers is crucial. This study aims to evaluate the incidence of one of the emerging neuroradiological signs highly suggestive of MS, the central vein sign (CVS), using data from Fabry disease (FD) patients as an index of microvascular disorder that could mimic MS. METHODS: In this retrospective study, after the application of inclusion and exclusion criteria, MRI scans of 36 FD patients and 73 relapsing-remitting (RR) MS patients were evaluated. Among the RRMS participants, 32 subjects with a disease duration inferior to 5 years (early MS) were also analyzed. For all subjects, a Fazekas score (FS) was recorded, excluding patients with FS = 0. Different neuroradiological signs, including CVS, were evaluated on FLAIR T2-weighted and spoiled gradient recalled echo sequences. RESULTS: Among all the recorded neuroradiological signs, the most striking difference was found for the CVS, with a detectable prevalence of 78.1% (57/73) in RRMS and of 71.4% (25/32) in early MS patients, while this sign was absent in FD (0/36). CONCLUSIONS: Our results confirm the high incidence of CVS in MS, also in the early phases of the disease, while it seems to be absent in conditions with a different etiology. These results corroborate the possible role of CVS as a useful neuroradiological sign highly suggestive of MS. KEY POINTS: • The search for new imaging biomarkers is crucial to achieve a correct neuroradiological diagnosis of MS. • The CVS shows an incidence superior to 70% in MS patients, even in the early phases of the disease, while it appears to be absent in FD. • These findings further corroborate the possible future central role of CVS in distinguishing between MS and its mimickers.