Neuroimaging correlates of postural instability in Parkinson's disease

BACKGROUND

Postural instability (PI) is a common disabling symptom in Parkinson's disease (PD), but little is known on its pathophysiological basis.

OBJECTIVE

In this study, we aimed to identify the brain structures associated with PI in PD patients, using different MRI approaches.

METHODS

We consecutively enrolled 142 PD patients and 45 control subjects. PI was assessed using the MDS-UPDRS-III pull-test item (PT). A whole-brain regression analysis identified brain areas where grey matter (GM) volume correlated with the PT score in PD patients. Voxel-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) were also used to compare unsteady (PT ≥ 1) and steady (PT = 0) PD patients. Associations between GM volume in regions of interest (ROI) and several clinical features were then investigated using LASSO regression analysis.

RESULTS

PI was present in 44.4% of PD patients. The whole-brain approach identified the bilateral inferior frontal gyrus (IFG) and superior temporal gyrus (STG) as the only regions associated with the presence of postural instability. VBM analysis showed reduced GM volume in fronto-temporal areas (superior, middle, medial and inferior frontal gyrus, and STG) in unsteady compared with steady PD patients, and the GM volume of these regions was selectively associated with the PT score and not with any other motor or non-motor symptom.

CONCLUSIONS

This study demonstrates a significant atrophy of fronto-temporal regions in unsteady PD patients, suggesting that these brain areas may play a role in the pathophysiological mechanisms underlying postural instability in PD. This result paves the way for further studies on postural instability in Parkinsonism.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study

OBJECTIVE

The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current corticocentric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural magnetic resonance imaging in 1602 adults with epilepsy and 1022 healthy controls across 22 sites from the global ENIGMA-Epilepsy working group.

METHODS

A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in (1) all epilepsies, (2) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS), (3) nonlesional temporal lobe epilepsy, (4) genetic generalized epilepsy, and (5) extratemporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness.

RESULTS

Across all epilepsies, reduced total cerebellar volume was observed (d = .42). Maximum volume loss was observed in the corpus medullare (dmax = .49) and posterior lobe gray matter regions, including bilateral lobules VIIB (dmax = .47), crus I/II (dmax = .39), VIIIA (dmax = .45), and VIIIB (dmax = .40). Earlier age at seizure onset (η ρ max 2  = .05) and longer epilepsy duration (η ρ max 2  = .06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE, with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls.

SIGNIFICANCE

We provide robust evidence of deep cerebellar and posterior lobe subregional gray matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in nonmotor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellar subregional damage into neurobiological models of epilepsy.

May anti-seizure medications alter brain structure in temporal lobe epilepsy? A prospective study

Mild mesial temporal lobe epilepsy (MTLE) patients may remain untreated for a considerable time after disease onset or achieve seizure control with a single anti-seizures medication (ASM). Thus, they represent an optimal population to investigate whether ASMs might have influence on brain structure. We consecutively enrolled 56 mild MTLE patients (22/56 untreated, 34/56 on-monotherapy) and 58 healthy controls, matched for age and gender. All subjects underwent 3T-brain MRI, using FreeSurfer for automated morphometry. Differences in gray matter were assessed using one-way Analysis of Covariance (ANCOVA), adjusting for age, disease duration and intracranial volume. No significant change was observed between treated and untreated patients. We observed a significant reduction in cortical thickness of left inferior parietal, inferior temporal, middle temporal gyri, and right inferior parietal gyrus, temporal pole in monotherapy patients compared to healthy controls, as well as an increase in left isthmus of cingulate gyrus in untreated MTLE subjects compared to controls. Surface and subcortical volumes analysis revealed no differences among groups. Our study demonstrated no substantial morphological abnormalities between untreated mild MTLE patients and those undergoing monotherapy. Although exploratory, these results may reassure about safety of commonly used drugs and their marginal role in influencing neuroimaging results. PLAIN LANGUAGE SUMMARY: This study investigated the following question: can medications against epileptic seizures have an effect on brain structure in mild mesial temporal lobe? Preliminary results from our analyses suggest not, as we did not find any difference in brain gray matter between untreated patients and those treated with a single anti-seizures medication. On the other hand, epilepsy patients presented cortical thinning compared to healthy controls in several regions of the temporal and parietal lobes, in line with previous studies investigating the disease.

A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN

Objectives

Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments.

Methods

We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves.

Results

In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions.

Conclusions

This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study

Objective

The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current cortico-centric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural MRI in 1,602 adults with epilepsy and 1,022 healthy controls across twenty-two sites from the global ENIGMA-Epilepsy working group.

Methods

A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in i) all epilepsies; ii) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS); iii) non-lesional temporal lobe epilepsy (TLE-NL); iv) genetic generalised epilepsy; and (v) extra-temporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness.

Results

Across all epilepsies, reduced total cerebellar volume was observed (d=0.42). Maximum volume loss was observed in the corpus medullare (dmax=0.49) and posterior lobe grey matter regions, including bilateral lobules VIIB (dmax= 0.47), Crus I/II (dmax= 0.39), VIIIA (dmax=0.45) and VIIIB (dmax=0.40). Earlier age at seizure onset (ηρ2max=0.05) and longer epilepsy duration (ηρ2max=0.06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls.

Significance

We provide robust evidence of deep cerebellar and posterior lobe subregional grey matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in non-motor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellum subregions into neurobiological models of epilepsy.

Morphometry and network-based atrophy patterns in SCN1A-related Dravet syndrome

Mutations of the voltage-gated sodium channel SCN1A gene (MIM#182389) are among the most clinically relevant epilepsy-related genetic mutations and present variable phenotypes, from the milder genetic epilepsy with febrile seizures plus to Dravet syndrome, a severe developmental and epileptic encephalopathy. Qualitative neuroimaging studies have identified malformations of cortical development in some patients and mild atrophic changes, partially confirmed by quantitative studies. Precise correlations between MRI findings and clinical variables have not been addressed. We used morphometric methods and network-based models to detect abnormal brain structural patterns in 34 patients with SCN1A-related epilepsy, including 22 with Dravet syndrome. By measuring the morphometric characteristics of the cortical mantle and volume of subcortical structures, we found bilateral atrophic changes in the hippocampus, amygdala, and the temporo-limbic cortex (P-value < 0.05). By correlating atrophic patterns with brain connectivity profiles, we found the region of the hippocampal formation as the epicenter of the structural changes. We also observed that Dravet syndrome was associated with more severe atrophy patterns with respect to the genetic epilepsy with febrile seizures plus phenotype (r = -0.0613, P-value = 0.03), thus suggesting that both the underlying mutation and seizure severity contribute to determine atrophic changes.

Cortical involvement in essential tremor with and without rest tremor: a machine learning study

INTRODUCTION

There is some debate on the relationship between essential tremor with rest tremor (rET) and the classic ET syndrome, and only few MRI studies compared ET and rET patients. This study aimed to explore structural cortical differences between ET and rET, to improve the knowledge of these tremor syndromes.

METHODS

Thirty-three ET patients, 30 rET patients and 45 control subjects (HC) were enrolled. Several MR morphometric variables (thickness, surface area, volume, roughness, mean curvature) of brain cortical regions were extracted using Freesurfer on T1-weighted images and compared among groups. The performance of a machine learning approach (XGBoost) using the extracted morphometric features was tested in discriminating between ET and rET patients.

RESULTS

rET patients showed increased roughness and mean curvature in some fronto-temporal areas compared with HC and ET, and these metrics significantly correlated with cognitive scores. Cortical volume in the left pars opercularis was also lower in rET than in ET patients. No differences were found between ET and HC. XGBoost discriminated between rET and ET with mean AUC of 0.86 ± 0.11 in cross-validation analysis, using a model based on cortical volume. Cortical volume in the left pars opercularis was the most informative feature for classification between the two ET groups.

CONCLUSION

Our study demonstrated higher cortical involvement in fronto-temporal areas in rET than in ET patients, which may be linked to the cognitive status. A machine learning approach based on MR volumetric data demonstrated that these two ET subtypes can be distinguished using structural cortical features.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Event-based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross-sectional data

OBJECTIVE

Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features.

METHODS

We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance.

RESULTS

In MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI.

SIGNIFICANCE

From cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.

Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

The impact of one-year COVID-19 containment measures in patients with mesial temporal lobe epilepsy: A longitudinal survey-based study

BACKGROUND

We assessed levels of depression, anxiety, stress, anhedonia, somatization, psychological distress, sleep, and life quality in patients with mesial temporal lobe epilepsy (MTLE) after one year of containment measures started in Italy to stem the COVID-19 pandemic.

METHODS

We consecutively enrolled 51 patients with MTLE, administering an online survey that compared the year before and after the COVID-19 propagation. We analyzed clinical data (e.g., seizure frequency, life quality) and neuropsychological assessment through Somatic Symptom Scale-8 (SSS-8), Beck Depression Inventory (BDI-2), State-Trait Anxiety Inventory (STAI-Y), Depression, Anxiety and Stress Scale (DASS-21), Pittsburgh Sleep Quality Index (PSQI), Snaith-Hamilton Pleasure Scale (SHAPS), Impact of Event Scale-Revised (IES-R). The BDI-2 and STAI-Y scores were compared to those acquired in the same patients before the COVID-19 outbreak.

RESULTS

Comparing our population with MTLE before and after COVID-19 outbreak, we found a significant worsening in life quality (p = 0.03), SSS-8 (p = 0.001), BDI-2 (p = 0.032), and STAI-Y scores (p < 0.001). After one year of pandemic, 88.2% of patients obtained pathological scores at PSQI, 19.6% at SHAPS, 29.4% at IES-R. Reduction of life quality correlated with anxiety, depression, stress, and somatization. Higher levels of anhedonia correlated with stress, depression, and anxiety. Somatization correlated with depression, anxiety, and sleep quality. Distress levels correlated with anxiety, somatization, and depression.

CONCLUSIONS

We demonstrated a significant worsening of depression, anxiety, life quality, and somatization in patients with MTLE after one year of COVID-19 beginning. Concomitantly, results suggest that the pandemic had a negative impact on sleep quality, psychological distress, and anhedonia, but not on epilepsy itself.

A systems-level analysis highlights microglial activation as a modifying factor in common epilepsies

AIMS

The causes of distinct patterns of reduced cortical thickness in the common human epilepsies, detectable on neuroimaging and with important clinical consequences, are unknown. We investigated the underlying mechanisms of cortical thinning using a systems-level analysis.

METHODS

Imaging-based cortical structural maps from a large-scale epilepsy neuroimaging study were overlaid with highly spatially resolved human brain gene expression data from the Allen Human Brain Atlas. Cell-type deconvolution, differential expression analysis and cell-type enrichment analyses were used to identify differences in cell-type distribution. These differences were followed up in post-mortem brain tissue from humans with epilepsy using Iba1 immunolabelling. Furthermore, to investigate a causal effect in cortical thinning, cell-type-specific depletion was used in a murine model of acquired epilepsy.

RESULTS

We identified elevated fractions of microglia and endothelial cells in regions of reduced cortical thickness. Differentially expressed genes showed enrichment for microglial markers and, in particular, activated microglial states. Analysis of post-mortem brain tissue from humans with epilepsy confirmed excess activated microglia. In the murine model, transient depletion of activated microglia during the early phase of the disease development prevented cortical thinning and neuronal cell loss in the temporal cortex. Although the development of chronic seizures was unaffected, the epileptic mice with early depletion of activated microglia did not develop deficits in a non-spatial memory test seen in epileptic mice not depleted of microglia.

CONCLUSIONS

These convergent data strongly implicate activated microglia in cortical thinning, representing a new dimension for concern and disease modification in the epilepsies, potentially distinct from seizure control.

Semi-automated assessment of the principal diffusion direction in the corpus callosum: differentiation of idiopathic normal pressure hydrocephalus from neurodegenerative diseases

BACKGROUND

Idiopathic normal pressure hydrocephalus (iNPH) shares clinical and radiological features with progressive supranuclear palsy (PSP) and Alzheimer's disease (AD). Corpus callosum (CC) involvement in these disorders is well established on structural MRI and diffusion tensor imaging (DTI), but alterations overlap and lack specificity to underlying tissue changes.

OBJECTIVE

We propose a semi-automated approach to assess CC integrity in iNPH based on the spatial distribution of DTI-derived principal diffusion direction orientation (V1).

METHODS

We processed DTI data from 121 subjects (Site1: iNPH = 23, PSP = 27, controls = 14; ADNI: AD = 35, controls = 22) to obtain V1, fractional anisotropy (FA) and mean diffusivity (MD) maps. To increase the estimation accuracy of DTI metrics, analyses were restricted to the midsagittal CC portion (± 6 slices from midsagittal plane). Group-wise comparison of normalized altered voxel count in midsagittal CC was performed using Kruskal-Wallis tests, followed by post hoc comparisons (Bonferroni-corrected p < 0.05). ROC analysis was used to evaluate the diagnostic power of DTI alterations compared to callosal volume.

RESULTS

We found specific changes of V1 distribution in CC splenium of iNPH compared to AD and PSP, while MD and FA showed patterns of alterations common to all disorders. ROC curves showed that, compared to splenial volume, V1 represented the most accurate marker of iNPH diagnosis versus AD and PSP.

CONCLUSIONS

Our results provide evidence that V1 is a powerful biomarker for distinguishing patients with iNPH from patients with AD or PSP. Indeed, our findings also provide more specific insight into the pathophysiological mechanisms that underlie tissue damage across iNPH and its mimics.

Orbito-frontal thinning together with a somatoform dissociation might be the fingerprint of PNES

OBJECTIVE

To investigate neuroanatomical changes in patients with psychogenic nonepileptic seizures (PNES) compared to major depressive disorder (MDD) and healthy controls.

METHODS

Forty-two drug-naïve PNES subjects and 25 patients with MDD, matched for demographic characteristics and level of depression (as measured by Beck Depression Inventory-II, BDI-II), were consecutively recruited. Patients performed an extensive neuropsychiatric assessment including: Hamilton Anxiety Rating Scale, Traumatic Experience Checklist, Dissociative Experiences Scale, Toronto Alexithymia Scale and Somatoform Dissociation Questionnaire (SDQ-20). All patients, together with 78 healthy matched controls, underwent 3T brain MRI followed by surface-based morphometry.

RESULTS

Cortical thickness analysis revealed significant cortical thinning in bilateral medial orbitofrontal cortex (OFC) and left rostral anterior cingulate cortex (ACC) in patients with MDD compared to subjects with PNES and controls. Interestingly, increased thickness of the right pars triangularis was found in PNES subjects compared to controls. PNES showed higher scores in SDQ-20 (p < 0.001) compared to MDD, which was corroborated by neuroimaging data, where somatoform dissociation scores correlated with morphological changes in the left medial OFC.

CONCLUSION

Our results show selective cortical thinning over the medial OFC in patients with PNES compared to wider regions of thinning in patients with MDD. Somatoform dissociation was the only psychopathological assessment significantly different in PNES and MDD.

Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

Microstructural changes in normal-appearing white matter in male sleep apnea patients are reversible after treatment: A pilot study

Visually appreciable white matter (WM) changes have been described in obstructive sleep apnea (OSA). However, few data exist on the involvement of silent WM abnormalities. This prospective study investigated the microstructural integrity of normal-appearing white matter (NAWM) in male OSA patients before and after continuous positive airway pressure (CPAP) treatment, using a neuroimaging approach. Magnetic resonance imaging (MRI) was acquired from 32 participants (16 severe never-treated OSA and 16 controls). Diffusion tensor imaging (DTI) and Tract-Based Spatial Statistics (TBSS) were used to assess the microstructural NAWM changes in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). In order to evaluate the efficacy of the therapy, OSA patients underwent MRI evaluations at baseline and after 3 months of treatment (follow-up). CPAP treatment significantly increased the FA in NAWM of the brain stem, corpus callosum and bilateral internal capsule of OSA patients at follow-up compared to baseline (p < 0.05, TFCE-corrected). OSA patients also showed increases in AD in the corpus callosum, superior corona radiata, and internal capsule of the right hemisphere (p < 0.05, TFCE-corrected) after CPAP treatment. A significant negative correlation was found between the FA of the corona radiata, corpus callosum, internal capsule, limbic structures, and neuropsychological scores at follow-up evaluation. No significant differences were found in MD and RD of NAWM in our patients after treatment. Our results demonstrate that FA and AD of NAWM in major tracts such as the corpus callosum and the internal capsule increased significantly after CPAP treatment, as a potential beneficial effect of ventilatory therapy. The recovery of NAWM alterations might also be related to the improvement in the neurocognitive profile, suggesting that nonclearly visible WM alterations may contribute to the physiopathology of OSA-related cognitive impairment.

Alteration of Iron Concentration in Alzheimer's Disease as a Possible Diagnostic Biomarker Unveiling Ferroptosis

Proper functioning of all organs, including the brain, requires iron. It is present in different forms in biological fluids, and alterations in its distribution can induce oxidative stress and neurodegeneration. However, the clinical parameters normally used for monitoring iron concentration in biological fluids (i.e., serum and cerebrospinal fluid) can hardly detect the quantity of circulating iron, while indirect measurements, e.g., magnetic resonance imaging, require further validation. This review summarizes the mechanisms involved in brain iron metabolism, homeostasis, and iron imbalance caused by alterations detectable by standard and non-standard indicators of iron status. These indicators for iron transport, storage, and metabolism can help to understand which biomarkers can better detect iron imbalances responsible for neurodegenerative diseases.

Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.

Looking for indicative magnetic resonance imaging signs of hippocampal developmental abnormalities in patients with mesial temporal lobe epilepsy and healthy controls

OBJECTIVE

To evaluate the frequency of qualitative features for hippocampal developmental abnormalities (HiDeA) definition on magnetic resonance imaging (MRI) in mesial temporal lobe epilepsy (MTLE) patients and healthy controls, highlighting which were more sensitive and specific to the epileptic syndrome.

METHODS

We enrolled 93 healthy controls and 187 MTLE patients. Among patients, 133 were MRI-negative and 54 had hippocampal sclerosis (HS). Two blinded, trained investigators defined HiDeA if three signs were present, including at least one of the following: (1) globular hippocampal shape (HCS), (2) verticalized collateral sulcus, and (3) medial positioning of hippocampus (HCP). After evaluating the prevalence of HiDeA in MTLE and controls, we assessed the frequency of each sign. Then, we classified differences in type or number of HiDeA diagnostic features, calculating their sensitivity and specificity. Fisher exact test was used to assess statistical significance.

RESULTS

HiDeA was detected in 36 of 187 MTLE cases (19.25%) and in eight of 93 (8.6%) controls. In particular, HiDeA was present in 25 of 133 (18.8%) patients with MRI-negative MTLE. Among all visual criteria here considered, HCS showed higher sensitivity both in the MRI-negative MTLE group (88%) and in the HS-MTLE group (91%). HCP, thickened subiculum, and reduction of the upper horizontal portion of the parahippocampal gyrus (HCTH) signs demonstrated a 100% specificity in both groups. In healthy controls, HCS was confirmed to have the highest sensitivity (100%), whereas HCP showed the highest specificity (98.8%). All these criteria were statistically associated with HiDeA. Electroencephalographic focus was concordant with the HiDeA side in 52.2% of MTLE patients. An association was not found among signs of HiDeA and treatment responsiveness.

SIGNIFICANCE

We identified characteristic signs of HiDeA, such as HCTH or HCP, differentiating HiDeA features between MTLE and healthy controls. The identification of sensitive and, more importantly, specific criteria of HiDeA could be helpful to make a more confident visual diagnosis.

Neurochemical Correlates of Brain Atrophy in Fibromyalgia Syndrome: A Magnetic Resonance Spectroscopy and Cortical Thickness Study

(1) Background: Recently, a series of clinical neuroimaging studies on fibromyalgia (FM) have shown a reduction in cortical volume and abnormally high glutamate (Glu) and glutamate + glutamine (Glx) levels in regions associated with pain modulation. However, it remains unclear whether the volumetric decreases and increased Glu levels in FM are related each other. We hypothesized that higher Glu levels are related to decreases in cortical thickness (CT) and volume in FM patients. (2) Methods: Twelve females with FM and 12 matched healthy controls participated in a session of combined 3.0 Tesla structural magnetic resonance imaging (MRI) and single-voxel MR spectroscopy focused on the thalami and ventrolateral prefrontal cortices (VLPFC). The thickness of the cortical and subcortical gray matter structures and the Glu/Cr and Glx/Cr ratios were estimated. Statistics included an independent t-test and Spearman’s test. (3) Results: The Glu/Cr ratio of the left VLPFC was negatively related to the CT of the left inferior frontal gyrus (pars opercularis (p = 0.01; r = −0.75) and triangularis (p = 0.01; r = −0.70)). Moreover, the Glx/Cr ratio of the left VLPFC was negatively related to the CT of the left middle anterior cingulate gyrus (p = 0.003; r = −0.81). Significantly lower CTs in FM were detected in subparts of the cingulate gyrus on both sides and in the right inferior occipital gyrus (p < 0.001). (4) Conclusions: Our findings are in line with previous observations that high glutamate levels can be related, in a concentration-dependent manner, to the morphological atrophy described in FM patients.

The ENIGMA-Epilepsy working group: Mapping disease from large data sets

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.

Late drug-resistance in mild MTLE: Can it be influenced by preexisting white matter alterations?

OBJECTIVE

To identify early structural alterations preceding the development of drug-resistance in mild mesial temporal lobe epilepsy (mMTLE), a drug-responsive syndrome ideal for investigating epilepsy pathophysiology and potential prognostic markers of long-term clinical outcome, using magnetic resonance imaging (MRI) at baseline and after 12-year follow-up.

METHODS

Since 2002, a total of 55 participants with a baseline diagnosis of mMTLE underwent three-dimensional (3D) T1 1.5T MRI. Based on long-term outcome (follow-up 12 ± 3 years), we identified 39 patients with stable mMTLE (smMTLE) and 16 patients who had developed drug-resistance overtime (refractory MTLE [rMTLE]). At follow-up, 21 smMTLE and 13 rMTLE patients underwent 3T-MRI including diffusion-weighted scans. Structural images were processed using longitudinal voxel-based morphometry and standard Freesurfer analysis. Statistical analyses were carried out accounting for age, age at onset, gender, hippocampal volume, and hippocampal sclerosis (Hs).

RESULTS

Patients presented similar demographic, clinical, and Hs features. White matter volume of the arcuate fasciculi, corticospinal tracts, left retrosplenial cingulum, and left inferior longitudinal fasciculus was reduced only in rMTLE patients before the development of drug-resistance. At follow-up, rMTLE showed decreased fractional anisotropy in the corpus callosum, superior longitudinal fasciculi, and major bundles of the right hemisphere.

SIGNIFICANCE

White matter temporal and extratemporal abnormalities are preexisting in patients with mild MTLE who will develop drug-resistance, independently from the presence of Hs. Thus, these changes might be due to an inherited genetic alteration rather than a subordinate worsening after repeated seizures, multiple antiepileptic drugs, or initial precipitating factors.

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen’s d = −0.24 to −0.73; P < 1.49 × 10⁻⁴), and lower thickness in the precentral gyri bilaterally (d = −0.34 to −0.52; P < 4.31 × 10⁻⁶). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = −1.73 to −1.91, P < 1.4 × 10⁻¹⁹), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = −0.36 to −0.52; P < 1.49 × 10⁻⁴). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = −0.29 to −0.54; P < 1.49 × 10⁻⁴). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = −0.27 to −0.51; P < 1.49 × 10⁻⁴). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < −0.0018; P < 1.49 × 10⁻⁴). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

Imaging counterpart of postural instability and vertical ocular dysfunction in patients with PSP: A multimodal MRI study

INTRODUCTION

We investigated the imaging counterpart of two functional domains (ocular motor dysfunction and postural instability) in progressive supranuclear palsy (PSP) patients classified according to the new clinical diagnostic criteria.

METHODS

Forty-eight patients with probable PSP-Richardson's syndrome (PSP-RS), 30 with probable PSP-parkinsonism (PSP-P), 37 with Parkinson's disease (PD), and 38 controls were enrolled. For each functional domain, PSP patients were stratified by two certainty levels: vertical supranuclear gaze palsy (O1) and slowness of vertical saccades (O2) for ocular motor dysfunction; early unprovoked falls and tendency to fall on the pull-test for postural instability. Voxel-based morphometry (VBM), whole-brain fractional anisotropy (FA) and MR planimetric measurements were analysed and compared across patient groups.

RESULTS

O1 was present in 64%, and O2 in 36% of all PSP patients. All PSP-RS patients showed early unprovoked falls. TBSS whole-brain analysis revealed that superior cerebellar peduncles (SCPs) were the only structures with significantly lower FA values in PSP-RS compared with PSP-P patients. PSP/O1 patients had lower FA values in midbrain than PSP/O2 patients. By contrast, VBM revealed no differences in grey matter volume between PSP patient groups. MR Planimetric measurements confirmed atrophy of midbrain and SCPs, in line with DTI findings.

CONCLUSIONS

Our study demonstrates that SCPs were significantly more damaged in patients with PSP-RS in comparison with PSP-P patients, thus suggesting the role of SCPs in developing postural instability. Midbrain damage was less severe in O2 than in O1 patients, suggesting that the degree of vertical ocular dysfunction reflects the severity of midbrain atrophy.

Structural connectivity differences in motor network between tremor-dominant and nontremor Parkinson's disease

Motor phenotypes of Parkinson's disease (PD) are recognized to have different prognosis and therapeutic response, but the neural basis for this clinical heterogeneity remains largely unknown. The main aim of this study was to compare differences in structural connectivity metrics of the main motor network between tremor-dominant and nontremor PD phenotypes (TD-PD and NT-PD, respectively) using probabilistic tractography-based network analysis. A total of 63 PD patients (35 TD-PD patients and 28 NT-PD patients) and 30 healthy controls underwent a 3 T MRI. Next, probabilistic tractography-based network analysis was performed to assess structural connectivity in cerebello-thalamo-basal ganglia-cortical circuits, by measuring the connectivity indices of each tract and the efficiency of each node. Furthermore, dopamine transporter single-photon emission computed tomography (DAT-SPECT) with ¹²³ I-ioflupane was used to assess dopaminergic striatal depletion in all PD patients. Both PD phenotypes showed nodal abnormalities in the substantia nigra, in agreement with DAT-SPECT evaluation. In addition, NT-PD patients displayed connectivity alterations in nigro-pallidal and fronto-striatal pathways, compared with both controls and TD-PD patients, in which the same motor connections seemed to be relatively spared. Of note, in NT-PD group, rigidity-bradykinesia score correlated with fronto-striatal connectivity abnormalities. These findings demonstrate that structural connectivity alterations occur in the cortico-basal ganglia circuit of NT-PD patients, but not in TD-PD patients, suggesting that these anatomical differences may underlie different motor phenotypes of PD. Hum Brain Mapp 38:4716-4729, 2017. © 2017 Wiley Periodicals, Inc.

A Fully Automated, Atlas-Based Approach for Superior Cerebellar Peduncle Evaluation in Progressive Supranuclear Palsy Phenotypes

BACKGROUND AND PURPOSE

The superior cerebellar peduncle is damaged in progressive supranuclear palsy. However, alterations differ between progressive supranuclear palsy with Richardson syndrome and progressive supranuclear palsy-parkinsonism. In this study, we propose an automated tool for superior cerebellar peduncle integrity assessment and test its performance in patients with progressive supranuclear palsy with Richardson syndrome, progressive supranuclear palsy-parkinsonism, Parkinson disease, and healthy controls.

MATERIALS AND METHODS

Structural and diffusion MRI was performed in 21 patients with progressive supranuclear palsy with Richardson syndrome, 9 with progressive supranuclear palsy-parkinsonism, 20 with Parkinson disease, and 30 healthy subjects. In a fully automated pipeline, the left and right superior cerebellar peduncles were first identified on MR imaging by using a tractography-based atlas of white matter tracts; subsequently, volume, mean diffusivity, and fractional anisotropy were extracted from superior cerebellar peduncles. These measures were compared across groups, and their discriminative power in differentiating patients was evaluated in a linear discriminant analysis.

RESULTS

Compared with those with Parkinson disease and controls, patients with progressive supranuclear palsy with Richardson syndrome showed alterations of all superior cerebellar peduncle metrics (decreased volume and fractional anisotropy, increased mean diffusivity). Patients with progressive supranuclear palsy-parkinsonism had smaller volumes than those with Parkinson disease and controls and lower fractional anisotropy than those with Parkinson disease. Patients with progressive supranuclear palsy with Richardson syndrome had significantly altered fractional anisotropy and mean diffusivity in the left superior cerebellar peduncle compared with those with progressive supranuclear palsy-parkinsonism. Discriminant analysis with the sole use of significant variables separated progressive supranuclear palsy-parkinsonism from progressive supranuclear palsy with Richardson syndrome with 70% accuracy and progressive supranuclear palsy-parkinsonism from Parkinson disease with 74% accuracy.

CONCLUSIONS

We demonstrate the feasibility of an automated approach for extracting multimodal MR imaging metrics from the superior cerebellar peduncle in healthy subjects and patients with parkinsonian. We provide evidence that structural and diffusion measures of the superior cerebellar peduncle might be valuable for computer-aided diagnosis of progressive supranuclear palsy subtypes and for differentiating patients with progressive supranuclear palsy-parkinsonism from with those with Parkinson disease.

Importance of Multimodal MRI in Characterizing Brain Tissue and Its Potential Application for Individual Age Prediction

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2(*) relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. The results of the linear model were used to predict apparent age in different regions of individual brain. This approach pointed to a number of novel applications that could potentially help highlighting areas particularly vulnerable to disease.

CADA-computer-aided DaTSCAN analysis

Background

Dopamine transporter (DaT) imaging (DaTSCAN) is useful for the differential diagnosis of parkinsonian syndromes. Visual evaluation of DaTSCAN images represents the generally accepted diagnostic method, but it is strongly dependent on the observer’s experience and shows inter- and intra-observer variability. A reliable and automatic method for DaTSCAN evaluation can provide objective quantification; it is desirable for longitudinal studies, and it allows for a better follow-up control. Moreover, it is crucial for an automated method to produce coherent measures related to the severity of motor symptoms.

Methods

In this work, we propose a novel fully automated technique for DaTSCAN analysis that generates quantitative measures based on striatal intensity, shape, symmetry and extent. We tested these measures using a support vector machine (SVM) classifier.

Results

The proposed measures reached 100 % accuracy in distinguishing between patients with Parkinson’s disease (PD) and control subjects. We also demonstrate the existence of a linear relationship and an exponential trend between pooled structural and functional striatal characteristics and the Unified Parkinson’s disease Rating Scale (UPDRS) motor score.

Conclusions

We present a novel, highly reproducible, user-independent technique for DaTSCAN analysis producing quantitative measures directly connected to striatum uptake and shape. In our method, no a priori assumption is required on the spatial conformation and localization of striatum, and both uptake and symmetry contribute to the index quantification. These measures can reliably support a computer-assisted decision system.

Electronic supplementary material

The online version of this article (doi:10.1186/s40658-016-0140-9) contains supplementary material, which is available to authorized users.

Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.

3-T magnetic resonance imaging simultaneous automated multimodal approach improves detection of ambiguous visual hippocampal sclerosis

BACKGROUND AND PURPOSE

To evaluate if an automatic magnetic resonance imaging (MRI) processing system may improve detection of hippocampal sclerosis (Hs) in patients with mesial temporal lobe epilepsy (MTLE).

METHODS

Eighty consecutive patients with a diagnosis of MTLE and 20 age- and sex-matched controls were prospectively recruited and included in our study. The entire group had 3-T MRI visual assessment of Hs analysed by two blinded imaging epilepsy experts. Logistic regression was used to evaluate the performances of neuroradiologists and multimodal analysis.

RESULTS

The multimodal automated tool gave no evidence of Hs in all 20 controls and classified the 80 MTLE patients as follows: normal MRI (54/80), left Hs (14/80), right Hs (11/80) and bilateral Hs (1/80). Of note, this multimodal automated tool was always concordant with the side of MTLE, as determined by a comprehensive electroclinical evaluation. In comparison with standard visual assessment, the multimodal automated tool resolved five ambiguous cases, being able to lateralize Hs in four patients and detecting one case of bilateral Hs. Moreover, comparing the performances of the three logistic regression models, the multimodal approach overcame performances obtained with a single image modality for both the hemispheres, reaching a global accuracy value of 0.97 for the right and 0.98 for the left hemisphere.

CONCLUSIONS

Multimodal quantitative automated MRI is a reliable and useful tool to depict and lateralize Hs in patients with MTLE, and may help to lateralize the side of MTLE especially in subtle and uncertain cases.

The relationship between regional microstructural abnormalities of the corpus callosum and physical and cognitive disability in relapsing-remitting multiple sclerosis

Significant corpus callosum (CC) involvement has been found in relapsing–remitting multiple sclerosis (RRMS), even if conventional magnetic resonance imaging measures have shown poor correlation with clinical disability measures. In this work, we tested the potential of multimodal imaging of the entire CC to explain physical and cognitive disability in 47 patients with RRMS. Values of thickness, fractional anisotropy (FA) and mean diffusivity (MD) were extracted from 50 regions of interest (ROIs) sampled along the bundle. The relationships between clinical, neuropsychological and imaging variables were assessed by using Spearman's correlation. Multiple linear regression analysis was employed in order to identify the relative importance of imaging metrics in modeling different clinical variables. Regional fiber composition of the CC differentially explained the response variables (Expanded Disability Status Scale [EDSS], cognitive impairment). Increases in EDSS were explained by reductions in CC thickness and MD. Cognitive impairment was mainly explained by FA reductions in the genu and splenium. Regional CC imaging properties differentially explained disability within RRMS patients revealing strong, distinct patterns of correlation with clinical and cognitive status of patients affected by this specific clinical phenotype.

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We assess corpus callosum damage in relapsing–remitting multiple sclerosis.

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We used no a priori subdivisions to model the bundle in a continuous fashion.

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Imaging–clinical relationship was explored by correlation and regression analyses.

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Damage of large, heavily myelinated axons was mainly linked to physical disability.

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Damage of small-diameter axons was mainly linked to cognitive impairment.

Magnetic resonance support vector machine discriminates between Parkinson disease and progressive supranuclear palsy

BACKGROUND

The aim of the current study was to distinguish patients with Parkinson disease (PD) from those with progressive supranuclear palsy (PSP) at the individual level using pattern recognition of magnetic resonance imaging data.

METHODS

We combined diffusion tensor imaging and voxel-based morphometry in a support vector machine algorithm to evaluate 21 patients with PSP and 57 patients with PD.

RESULTS

The automated algorithm correctly distinguished patients who had PD from those who had PSP with 100% accuracy. This accuracy value was obtained when white matter atrophy was considered. Diffusion parameters combined with gray matter atrophy exhibited 90% sensitivity and 96% specificity.

CONCLUSIONS

Our findings demonstrate that automated pattern recognition can help distinguish patients with PSP from those with PD on an individual basis.