Increased cortical curvature reflects white matter atrophy in individual patients with early multiple sclerosis

Elevated intrinsic cortical curvature in treatment-resistant schizophrenia: Evidence of structural deformation in functional connectivity areas and comparison with alternate indices of structure

BACKGROUND

Research suggests structural and connectivity abnormalities in patients with treatment-resistant schizophrenia (TRS) compared to first-line responders and healthy-controls. However, measures of these abnormalities are often influenced by external factors like nicotine and antipsychotics, limiting their clinical utility. Intrinsic-cortical-curvature (ICC) presents a millimetre-scale measure of brain gyrification, highly sensitive to schizophrenia differences, and associated with TRS-like traits in early stages of the disorder. Despite this evidence, ICC in TRS remains unexplored. This study investigates ICC as a marker for treatment resistance in TRS, alongside structural indices for comparison.

METHODS

We assessed ICC in anterior cingulate, dorsolateral prefrontal, temporal, and parietal cortices of 38 first-line responders, 30 clozapine-resistant TRS, 37 clozapine-responsive TRS, and 52 healthy-controls. For comparative purposes, Fold and Curvature indices were also analyzed.

RESULTS

Adjusting for age, sex, nicotine-use, and chlorpromazine equivalence, principal findings indicate ICC elevations in the left hemisphere dorsolateral prefrontal (p < 0.001, η2partial = 0.142) and temporal cortices (LH p = 0.007, η2partial = 0.060; RH p = 0.011, η2partial = 0.076) of both TRS groups, and left anterior cingulate cortex of clozapine-resistant TRS (p = 0.026, η2partial = 0.065), compared to healthy-controls. Elevations that correlated with reduced cognition (p = 0.001) and negative symptomology (p < 0.034) in clozapine-resistant TRS. Fold and Curvature indices only detected group differences in the right parietal cortex, showing interactions with age, sex, and nicotine use. ICC showed interactions with age.

CONCLUSION

ICC elevations were found among patients with TRS, and correlated with symptom severity. ICCs relative independence from sex, nicotine-use, and antipsychotics, may support ICC's potential as a viable marker for TRS, though age interactions should be considered.

Characterizing cognitive subtypes in schizophrenia using cortical curvature

Cognitive deficits are a core symptom of schizophrenia, but research on their neural underpinnings has been challenged by the heterogeneity in deficits' severity among patients. Here, we address this issue by combining logistic regression and random forest to classify two neuropsychological profiles of patients with high (HighCog) and low (LowCog) cognitive performance in two independent samples. We based our analysis on the cortical features grey matter volume (VOL), cortical thickness (CT), and mean curvature (MC) of N = 57 patients (discovery sample) and validated the classification in an independent sample (N = 52). We investigated which cortical feature would yield the best classification results and expected that the 10 most important features would include frontal and temporal brain regions. The model based on MC had the best performance with area under the curve (AUC) values of 76% and 73%, and identified fronto-temporal and occipital brain regions as the most important features for the classification. Moreover, subsequent comparison analyses could reveal significant differences in MC of single brain regions between the two cognitive profiles. The present study suggests MC as a promising neuroanatomical parameter for characterizing schizophrenia cognitive subtypes.

Patterns of brain atrophy in recently-diagnosed relapsing-remitting multiple sclerosis

Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in recently-diagnosed RRMS using volumetry and voxel-based morphometry (VBM). RRMS patients (N = 354) underwent 3T structural MRI <6 months after diagnosis and 1-year follow-up, as part of the Scottish multicentre 'FutureMS' study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish regional patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the brain. Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, cerebellar GM, brainstem, amygdala, basal ganglia, hippocampus, accumbens, thalamus and ventral diencephalon. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 26 regions and 16/26; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe. Widespread GM and NAWM atrophy was observed in this large recently-diagnosed RRMS cohort, particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions; indicative of neurodegeneration across tissue types, and in accord with limited previous studies in early disease. Volumetric and VBM results emphasise different features of longitudinal lobar and loco-regional change, however identify consistent atrophy patterns across individuals. Atrophy measures targeted to specific brain regions may provide improved markers of neurodegeneration, and potential future imaging stratifiers and endpoints for clinical decision making and therapeutic trials.

Questionnaire and structural imaging data accurately predict headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury

BACKGROUND

Our prior work demonstrated that questionnaires assessing psychosocial symptoms have utility for predicting improvement in patients with acute post-traumatic headache following mild traumatic brain injury. In this cohort study, we aimed to determine whether prediction accuracy can be refined by adding structural magnetic resonance imaging (MRI) brain measures to the model.

METHODS

Adults with acute post-traumatic headache (enrolled 0-59 days post-mild traumatic brain injury) underwent T1-weighted brain MRI and completed three questionnaires (Sports Concussion Assessment Tool, Pain Catastrophizing Scale, and the Trait Anxiety Inventory Scale). Individuals with post-traumatic headache completed an electronic headache diary allowing for determination of headache improvement at three- and at six-month follow-up. Questionnaire and MRI measures were used to train prediction models of headache improvement and headache trajectory.

RESULTS

Forty-three patients with post-traumatic headache (mean age = 43.0, SD = 12.4; 27 females/16 males) and 61 healthy controls were enrolled (mean age = 39.1, SD = 12.8; 39 females/22 males). The best model achieved cross-validation Area Under the Curve of 0.801 and 0.805 for predicting headache improvement at three and at six months. The top contributing MRI features for the prediction included curvature and thickness of superior, middle, and inferior temporal, fusiform, inferior parietal, and lateral occipital regions. Patients with post-traumatic headache who did not improve by three months had less thickness and higher curvature measures and notably greater baseline differences in brain structure vs. healthy controls (thickness: p < 0.001, curvature: p = 0.012) than those who had headache improvement.

CONCLUSIONS

A model including clinical questionnaire data and measures of brain structure accurately predicted headache improvement in patients with post-traumatic headache and achieved improvement compared to a model developed using questionnaire data alone.

Cortical Gyrification Morphology in Adult Males with Mild Traumatic Brain Injury

Cortical gyrification, as a specific measure derived from magnetic resonance imaging, remains understudied in mild traumatic brain injury (mTBI). Local gyrification index (lGI) and mean curvature are related measures indexing the patterned folding of the cortex,ml which reflect distinct properties of cortical morphology and geometry. Using both metrics, we examined cortical gyrification morphology in 59 adult males with mTBI (n = 29) versus those without (n = 30) mTBI in the subacute phase of injury (between 2 weeks and 3 months). The effect of IQ on lGI and brain-symptom relations were also examined. General linear models revealed greater lGI in mTBI versus controls in the frontal lobes bilaterally, but reduced lGI in mTBI of the left temporal lobe. An age-related decrease in lGI was found in numerous areas, with no significant group-by-age interaction effects observed. Including other factors (i.e., mTBI severity, symptoms, and IQ) in the lGI model yielded similar results with few exceptions. Mean curvature analyses depicted a significant group-by-age interaction with the absence of significant main effects of group or age. Our results suggest that cortical gyrification morphology is adversely affected by mTBI in both frontal and temporal lobes, which are thought of as highly susceptible regions to mTBI. These findings contribute to understanding the effects of mTBI on neuromorphological properties, such as alterations in cortical gyrification, which reflect underlying microstructural changes (i.e., apoptosis, neuronal number, or white matter alterations). Future studies are needed to infer causal relationships between micro- and macrostructural changes after an mTBI and investigate potential sex differences.

Magnetic Resonance Imaging Demonstrates Gyral Abnormalities in Tourette Syndrome

Tourette syndrome (TS) is a neurological disorder characterized by involuntary and repetitive movements known as tics. A retrospective analysis of magnetic resonance imaging (MRI) scans from 39 children and adolescents with TS was performed and subsequently compared to MRI scans from 834 neurotypical controls. The purpose of this study was to identify any differences in the regions of motor circuitry in TS to further our understanding of their disturbances in motor control (i.e., motor tics). Measures of volume, cortical thickness, surface area, and surface curvature for specific motor regions were derived from each MRI scan. The results revealed increased surface curvature in the opercular part of the inferior frontal gyrus and the triangular part of the inferior frontal gyrus in the TS group compared to the neurotypical control group. These novel findings offer some of the first evidence for surface curvature differences in motor circuitry regions in TS, which may be associated with known motor and vocal tics.

Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings

Objective

To derive and evaluate the association of prostate shape distension descriptors from T2-weighted MRI (T2WI) with prostate cancer (PCa) biochemical recurrence (BCR) post-radical prostatectomy (RP) independently and in conjunction with texture radiomics of PCa.

Methods

This retrospective study comprised 133 PCa patients from two institutions who underwent 3T-MRI prior to RP and were followed up with PSA measurements for ≥3 years. A 3D shape atlas-based approach was adopted to derive prostate shape distension descriptors from T2WI, and these descriptors were used to train a random forest classifier (C_S) to predict BCR. Texture radiomics was derived within PCa regions of interest from T2WI and ADC maps, and another machine learning classifier (C_R) was trained for BCR. An integrated classifier C_S+R was then trained using predictions from C_S and C_R. These models were trained on D₁ (N = 71, 27 BCR+) and evaluated on independent hold-out set D₂ (N = 62, 12 BCR+). C_S+R was compared against pre-RP, post-RP clinical variables, and extant nomograms for BCR-free survival (bFS) at 3 years.

Results

C_S+R resulted in a higher AUC (0.75) compared to C_R (0.70, p = 0.04) and C_S (0.69, p = 0.01) on D₂ in predicting BCR. On univariable analysis, C_S+R achieved a higher hazard ratio (2.89, 95% CI 0.35–12.81, p < 0.01) compared to other pre-RP clinical variables for bFS. C_S+R, pathologic Gleason grade, extraprostatic extension, and positive surgical margins were associated with bFS (p < 0.05). C_S+R resulted in a higher C-index (0.76 ± 0.06) compared to CAPRA (0.69 ± 0.09, p < 0.01) and Decipher risk (0.59 ± 0.06, p < 0.01); however, it was comparable to post-RP CAPRA-S (0.75 ± 0.02, p = 0.07).

Conclusions

Radiomic shape descriptors quantifying prostate surface distension complement texture radiomics of prostate cancer on MRI and result in an improved association with biochemical recurrence post-radical prostatectomy.

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

Background and purpose

To investigate the relationship between the functional connectivity (FC) of the sensorimotor and cognitive cerebellum and measures of structural damage in patients with multiple sclerosis (MS) and no physical disability.

Methods

We selected 144 relapsing–remitting MS patients with an Expanded Disability Status Scale score of ≤1.5 and 98 healthy controls from the Italian Neuroimaging Network Initiative database. From multimodal 3T magnetic resonance imaging (MRI), including functional MRI at rest, we calculated lesion load, cortical thickness, and white matter, cortical gray matter, and caudate, putamen, thalamic, and cerebellar volumes. Voxel‐wise FC of the sensorimotor and cognitive cerebellum was assessed with seed‐based analysis, and multiple regression analysis was used to evaluate the relationship between FC and structural damage.

Results

Whole brain, white matter, caudate, putamen, and thalamic volumes were reduced in patients compared to controls, whereas cortical gray matter was not significantly different in patients versus controls. Both the sensorimotor and cognitive cerebellum showed a widespread pattern of increased and decreased FC that were negatively associated with structural measures, indicating that the lower the FC, the greater the tissue loss. Lastly, among multiple structural measures, cortical gray matter and white matter volumes were the best predictors of cerebellar FC alterations.

Conclusions

Increased and decreased cerebellar FC with several brain areas coexist in MS patients with no disability. Our data suggest that white matter loss hampers FC, whereas, in the absence of atrophy, cortical volume represents the framework for FC to increase.

Gray Matter Structural Alterations in Chronic and Episodic Migraine: A Morphometric Magnetic Resonance Imaging Study

OBJECTIVE

This study evaluates different parameters describing the gray matter structure to analyze differences between healthy controls, patients with episodic migraine, and patients with chronic migraine.

DESIGN

Cohort study.

SETTING

Spanish community.

SUBJECTS

Fifty-two healthy controls, 57 episodic migraine patients, and 57 chronic migraine patients were included in the study and underwent T1-weighted magnetic resonance imaging acquisition.

METHODS

Eighty-four cortical and subcortical gray matter regions were extracted, and gray matter volume, cortical curvature, thickness, and surface area values were computed (where applicable). Correlation analysis between clinical features and structural parameters was performed.

RESULTS

Statistically significant differences were found between all three groups, generally consisting of increases in cortical curvature and decreases in gray matter volume, cortical thickness, and surface area in migraineurs with respect to healthy controls. Furthermore, differences were also found between chronic and episodic migraine. Significant correlations were found between duration of migraine history and several structural parameters.

CONCLUSIONS

Migraine is associated with structural alterations in widespread gray matter regions of the brain. Moreover, the results suggest that the pattern of differences between healthy controls and episodic migraine patients is qualitatively different from that occurring between episodic and chronic migraine patients.

Differential Patterns of Gyral and Sulcal Morphological Changes During Normal Aging Process

The cerebral cortex is a highly convoluted structure with distinct morphologic features, namely the gyri and sulci, which are associated with the functional segregation or integration in the human brain. During the lifespan, the brain atrophy that is accompanied by cognitive decline is a well-accepted aging phenotype. However, the detailed patterns of cortical folding change during aging, especially the changing age-dependencies of gyri and sulci, which is essential to brain functioning, remain unclear. In this study, we investigated the morphology of the gyral and sulcal regions from pial and white matter surfaces using MR imaging data of 417 healthy participants across adulthood to old age (21–92 years). To elucidate the age-related changes in the cortical pattern, we fitted cortical thickness and intrinsic curvature of gyri and sulci using the quadratic model to evaluate their age-dependencies during normal aging. Our findings show that comparing to gyri, the sulcal thinning is the most prominent pattern during the aging process, and the gyrification of pial and white matter surfaces were also affected differently, which implies the vulnerability of functional segregation during aging. Taken together, we propose a morphological model of aging that may provide a framework for understanding the mechanisms underlying gray matter degeneration.

Multimodal fusion analysis of structural connectivity and gray matter morphology in migraine

No specific migraine biomarkers have been found in single‐modality MRI studies. We aimed at establishing biomarkers for episodic and chronic migraine using diverse MRI modalities. We employed canonical correlation analysis and joint independent component analysis to find structural connectivity abnormalities that are related to gray matter morphometric alterations. The number of streamlines (trajectories of estimated fiber‐tracts from tractography) was employed as structural connectivity measure, while cortical curvature, thickness, surface area, and volume were used as gray matter parameters. These parameters were compared between 56 chronic and 54 episodic migraine patients, and 50 healthy controls. Cortical curvature alterations were associated with abnormalities in the streamline count in episodic migraine patients compared to controls, with higher curvature values in the frontal and temporal poles being related to a higher streamline count. Lower streamline count was found in migraine compared to controls in connections between cortical regions within each of the four lobes. Higher streamline count was found in migraine in connections between subcortical regions, the insula, and the cingulate and orbitofrontal cortex, and between the insula and the temporal region. The connections between the caudate nucleus and the orbitofrontal cortex presented worse connectivity in chronic compared to episodic migraine. The hippocampus was involved in connections with higher and lower number of streamlines in chronic migraine. Strengthening of structural networks involving pain processing and subcortical regions coexists in migraine with weakening of cortical networks within each lobe. The multimodal analysis offers a new insight about the association between brain structure and connectivity.

Vulnerability to mood degradation during sleep deprivation is influenced by white-matter compactness of the triple-network model

Sleep deprivation (SD) is often associated with significant shifts in mood state relative to baseline functioning. Prior work suggests that there are consistent trait-like differences among individuals in the degree to which their mood and performances are affected by sleep loss. The goal of this study was to determine the extent to which trait-like individual differences in vulnerability/resistance to mood degradation during a night of SD are dependent upon region-specific white and grey matter (WM/GM) characteristics of a triple-network model, including the default-mode network (DMN), control-execution network (CEN) and salience network (SN). Diffusion-weighted and anatomical brain data were collected from 45 healthy individuals several days prior to a 28-h overnight SD protocol. During SD, a visual analog mood scale was administered every hour from 19:15 (time point1; TP1) to 11:15 (TP17) the following morning to measure two positive and six negative mood states. Four core regions within the DMN, five within the CEN, and seven within the SN were used as regions of interest (ROIs). An index of mood resistance (IMR) was defined as the averaged differences between positive and negative mood states over 12 TPs (TP5 to TP16) relative to baseline (TP1 to TP4). For each ROI, characteristics of WM - quantitative anisotropy (QA) and mean curvature index (WM-MCI), and GM - cortical volume (CV) and GM-MCI were estimated, and used to predict IMR. WM characteristics, particularly QA, of all of regions within the DMN, and most of the regions within the CEN and SN predicted IMR during SD. In contrast, most ROIs did not show significant association between IMR and any of the GM characteristics (CV and MCI) or WM MCI. Our findings suggest that greater resilience to mood degradation induced by total SD appears to be associated with more compact axonal pathways within the DMN, CEN and SN.

Sex differences in limbic network and risk-taking propensity in healthy individuals

Little is known about the structural neural substrates that may contribute to sex differences in risk-taking propensity (RTP). A close association between risk-seeking behavior and the emotional-regulation network led us to hypothesize that the sex differences in RTP would be associated with sex differences in brain morphometry of the limbic network (LN). We collected RTP scores using the bubble sheet version of the evaluation of risk (EVAR) scale and neuroanatomical data from 57 healthy individuals (29 males). The EVAR scale included sub-scales measuring recklessness/impulsivity, self-confidence, and need for control (NFC). We observed significant sex differences in NFC showing greater desire for control and dominance in males than females (multivariate analysis of covariance, MANCOVAN: p = .01). Morphometry analysis showed that it was only the right LN, which showed significant sex differences in normalized surface area, normalized cortical volume, and adjusted mean curvature index (females > males) at p < .01 (MANCOVAN, corrected for multiple comparisons). Correlation analysis showed that greater curvature of the right LN was significantly associated with lower desire for control in high-risk events (r = -.31, p = .02 at 95% CI of [-0.53, -0.05]). Our findings suggest that the normalized cortical measures could indicate specific sex differences in brain morphometry, particularly within the LN. The curvature index was the only differentiating factor for greater/lower propensity for risk-taking behavior in overall sample. Therefore, the LN and the curvature measures could be key biomarkers, which play an important role in predicting risk-taking behavior.

Imaging in mice and men: Pathophysiological insights into multiple sclerosis from conventional and advanced MRI techniques

Magnetic resonance imaging (MRI) is the most important tool for diagnosing multiple sclerosis (MS). However, MRI is still unable to precisely quantify the specific pathophysiological processes that underlie imaging findings in MS. Because autopsy and biopsy samples of MS patients are rare and biased towards a chronic burnt-out end or fulminant acute early stage, the only available methods to identify human disease pathology are to apply MRI techniques in combination with subsequent histopathological examination to small animal models of MS and to transfer these insights to MS patients. This review summarizes the existing combined imaging and histopathological studies performed in MS mouse models and humans with MS (in vivo and ex vivo), to promote a better understanding of the pathophysiology that underlies conventional MRI, diffusion tensor and magnetization transfer imaging findings in MS patients. Moreover, it provides a critical view on imaging capabilities and results in MS patients and mouse models and for future studies recommends how to combine those particular MR sequences and parameters whose underlying pathophysiological basis could be partly clarified. Further combined longitudinal in vivo imaging and histopathological studies on rationally selected, appropriate mouse models are required.

BMI-related cortical morphometry changes are associated with altered white matter structure

BACKGROUND

While gross measures of brain structure have shown alterations with increasing body mass index (BMI), the extent and nature of such changes has varied substantially across studies. Here, we sought to determine whether small-scale morphometric measures might prove more sensitive and reliable than larger scale measures and whether they might offer a valuable opportunity to link cortical changes to underlying white matter changes. To examine this, we explored the association of BMI with millimetre-scale Gaussian curvature, in addition to standard measures of morphometry such as cortical thickness, surface area and mean curvature. We also assessed the volume and integrity of the white matter, using white matter signal intensity and fractional anisotropy (FA). We hypothesised that BMI would be linked to small-scale changes in Gaussian curvature and that this phenomenon would be mediated by changes in the integrity of the underlying white matter.

METHODS

The association of global measures of T1-weighted cortical morphometry with BMI was examined using linear regression and mediation analyses in two independent groups of healthy young to middle aged human subjects (n1 = 52, n2 = 202). In a third dataset of (n3 = 897), which included diffusion tensor images, we sought to replicate the significant associations established in the first two datasets, and examine the potential mechanistic link between BMI-associated cortical changes and global FA.

RESULTS

Gaussian curvature of the white matter surface showed a significant, positive association with BMI across all three independent datasets. This effect was mediated by a negative association between the integrity of the white matter and BMI.

CONCLUSIONS

Increasing BMI is associated with changes in white matter microstructure in young to middle-aged healthy adults. Our results are consistent with a model whereby BMI-linked cortical changes are mediated by the effects of BMI on white matter microstructure.

Subcortical volume and cortical surface architecture in women with acute and remitted anorexia nervosa: An exploratory neuroimaging study

BACKGROUND

Anorexia nervosa (AN) is a highly heritable psychiatric disorder characterized by starvation and emaciation and associated with changes in brain structure. The precise nature of these changes remains unclear, as does their developmental time course and capacity for reversal with weight-restoration. In this comprehensive neuroimaging study, we sought to characterize these changes by measuring subcortical volume and cortical surface architecture in women with acute and remitted AN.

METHODS

Structural magnetic resonance imaging data was acquired from underweight women with a current diagnosis of AN (acAN: n = 23), weight-recovered women with a past diagnosis of AN (recAN: n = 24), and female controls (HC: n = 24). Subcortical segmentation and cortical surface reconstruction were performed with FreeSurfer 6.0.0, and group differences in regional volume and vertex-wise, cortex-wide thickness, surface area, and local gyrification index (LGI), a measure of folding, were tested with separate univariate analyses of covariance.

RESULTS

Mean hippocampal and thalamic volumes were significantly reduced in acAN participants, as was mean cortical thickness in four frontal and temporal clusters. Mean LGI was significantly reduced in acAN and recAN participants in five frontal and parietal clusters. No significant group differences in cortical surface area were detected.

CONCLUSIONS

Reductions in subcortical volume, cortical thickness, and right postcentral LGI were unique to women with acute AN, indicating state-dependence and pointing towards cellular remodeling and sulcal widening as consequences of disease manifestation. Reductions in bilateral frontal LGI were observed in women with acute and remitted AN, suggesting a role of atypical neurodevelopment in disease vulnerability.

Protective potential of dimethyl fumarate in a mouse model of thalamocortical demyelination

Alterations in cortical cellular organization, network functionality, as well as cognitive and locomotor deficits were recently suggested to be pathological hallmarks in multiple sclerosis and corresponding animal models as they might occur following demyelination. To investigate functional changes following demyelination in a well-defined, topographically organized neuronal network, in vitro and in vivo, we focused on the primary auditory cortex (A1) of mice in the cuprizone model of general de- and remyelination. Following myelin loss in this model system, the spatiotemporal propagation of incoming stimuli in A1 was altered and the hierarchical activation of supra- and infragranular cortical layers was lost suggesting a profound effect exerted on neuronal network level. In addition, the response latency in field potential recordings and voltage-sensitive dye imaging was increased following demyelination. These alterations were accompanied by a loss of auditory discrimination abilities in freely behaving animals, a reduction of the nuclear factor-erythroid 2-related factor-2 (Nrf-2) protein in the nucleus in histological staining and persisted during remyelination. To find new strategies to restore demyelination-induced network alteration in addition to the ongoing remyelination, we tested the cytoprotective potential of dimethyl fumarate (DMF). Therapeutic treatment with DMF during remyelination significantly modified spatiotemporal stimulus propagation in the cortex, reduced the cognitive impairment, and prevented the demyelination-induced decrease in nuclear Nrf-2. These results indicate the involvement of anti-oxidative mechanisms in regulating spatiotemporal cortical response pattern following changes in myelination and point to DMF as therapeutic compound for intervention.

Urgent challenges in quantification and interpretation of brain grey matter atrophy in individual MS patients using MRI

Atrophy of the brain grey matter (GM) is an accepted and important feature of multiple sclerosis (MS). However, its accurate measurement is hampered by various technical, pathological and physiological factors. As a consequence, it is challenging to investigate the role of GM atrophy in the disease process as well as the effect of treatments that aim to reduce neurodegeneration. In this paper we discuss the most important challenges currently hampering the measurement and interpretation of GM atrophy in MS. The focus is on measurements that are obtained in individual patients rather than on group analysis methods, because of their importance in clinical trials and ultimately in clinical care. We discuss the sources and possible solutions of the current challenges, and provide recommendations to achieve reliable measurement and interpretation of brain GM atrophy in MS.

Non-lesional cerebellar damage in patients with clinically isolated syndrome: DTI measures predict early conversion into clinically definite multiple sclerosis

Background

Today, no specific test for the diagnosis of multiple sclerosis (MS) is available due to the lack of characteristic symptoms at beginning. This circumstance also complicates estimation of disease progression. Recent findings provided evidence for early, non-lesional cerebellar damage in patients with (clinically definite) relapsing-remitting MS.

Objective

To investigate if microstructural cerebellar alterations can also serve as early structural biomarker for disease progression and conversion from clinically isolated syndrome (CIS) to MS.

Methods

46 patients diagnosed with CIS and 26 age-matched healthy controls were admitted to high-resolution MRI including diffusion tensor imaging (DTI) to examine atrophy and microstructural integrity of the cerebellum. Microstructural integrity of cerebellar white matter was assessed by fractional anisotropy (FA) as derived from DTI.

Results

Although all 46 patients of our CIS cohort showed no cerebellar lesions in structural MRI (T1w, T2w, FLAIR), their mean cerebellar FA was already reduced compared to healthy controls. Significant FA reduction at follow-up DTI 6 months after baseline examination was observed. In 16 patients that converted to MS, we found a correlation between initial cerebellar FA and conversion latency (R = 0.71, p < 0.002). Initial cerebellar FA under FA_crit = 0.352 predicted conversion into relapsing-remitting MS within 24 months (FA_crit: mean cerebellar FA of patients with early MS, determined in another study).

Conclusion

DTI seems to reflect early tissue injury in beginning MS, when atrophy and lesions are not yet detectable. Decreased cerebellar FA in patients with CIS might indicate an active and unstable disease stage, resulting in a shorter conversion time into MS.

A Fully Automated Pipeline for Normative Atrophy in Patients with Neurodegenerative Disease

Introduction

Volumetric image analysis to detect progressive brain tissue loss in patients with multiple sclerosis (MS) has recently been suggested as a promising marker for "no evidence of disease activity." Software packages for longitudinal whole-brain volume analysis in individual patients are already in clinical use; however, most of these methods have omitted region-based analysis. Here, we suggest a fully automatic analysis pipeline based on the free software packages FSL and FreeSurfer.

Materials and methods

Fifty-five T1-weighted magnetic resonance imaging (MRI) datasets of five patients with confirmed relapsing-remitting MS and mild to moderate disability were longitudinally analyzed compared to a morphometric reference database of 323 healthy controls (HCs). After lesion filling, the volumes of brain segmentations and morphometric parameters of cortical parcellations were automatically screened for global and regional abnormalities. Error margins and artifact probabilities of regional morphometric parameters were estimated. Linear models were fitted to the series of follow-up MRIs and checked for consistency with cross-sectional aging in HCs.

Results

As compared to leave-one-out cross-validation in a subset of the control dataset, anomaly detection rates were highly elevated in MRIs of two patients. We detected progressive volume changes that were stronger than expected compared to normal aging in 4/5 patients. In individual patients, we also identified stronger than expected regional decreases of subcortical gray matter, of cortical thickness, and areas of reducing gray-white contrast over time.

Conclusion

Statistical comparison with a large normative database may provide complementary and rater independent quantitative information about regional morphological changes related to disease progression or drug-related disease modification in individual patients. Regional volume loss may also be detected in clinically stable patients.

Biological and cognitive correlates of cortical curvature in schizophrenia

Mean cortical curvature may relate to cortico-cortical connections integrity. We explored the association between prefrontal (PFC) cortical curvature and fractional anisotropy (FA) values for tracts connecting PFC and relevant cortical regions. In schizophrenia Anatomical and diffusion magnetic resonance images were obtained from 34 patients (16 of them first-episodes) and 32 healthy controls. We calculated curvature at rostral lateral prefrontal (RLPF) and superior medial prefrontal (SMPF) areas and mean FA for the tracts respectively connecting RLPF and SMPF areas with anterior caudal cingulate (ACC), superior temporal gyrus (STG) and superior parietal SP regions. Cognitive and clinical data were collected, including baseline symptoms, Clinical Global Impression change scores from baseline to follow-up, illness duration and treatment dosage. Patients showed significantly lower FA values in the tracts linking right RLPF-ACC, right SMPF-SPG and bilaterally PFC-STG. FA values in short-range cortico-cortical connections (linking PFC and ACC) were inversely associated with PFC curvature. In patients, cognitive performance was negatively associated with PFC curvature. Larger curvature values were associated to lack of clinical improvement at follow-up. We conclude that cortical curvature is influenced by integrity in short-range cortico-cortical connections and relates to cognition and clinical outcome in schizophrenia patients.

Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects

The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner.

Mindboggling morphometry of human brains

Mindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains ever conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, while more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggle's algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available.

The quality of cortical network function recovery depends on localization and degree of axonal demyelination

Myelin loss is a severe pathological hallmark common to a number of neurodegenerative diseases, including multiple sclerosis (MS). Demyelination in the central nervous system appears in the form of lesions affecting both white and gray matter structures. The functional consequences of demyelination on neuronal network and brain function are not well understood. Current therapeutic strategies for ameliorating the course of such diseases usually focus on promoting remyelination, but the effectiveness of these approaches strongly depends on the timing in relation to the disease state. In this study, we sought to characterize the time course of sensory and behavioral alterations induced by de- and remyelination to establish a rational for the use of remyelination strategies. By taking advantage of animal models of general and focal demyelination, we tested the consequences of myelin loss on the functionality of the auditory thalamocortical system: a well-studied neuronal network consisting of both white and gray matter regions. We found that general demyelination was associated with a permanent loss of the tonotopic cortical organization in vivo, and the inability to induce tone-frequency-dependent conditioned behaviors, a status persisting after remyelination. Targeted, focal lysolecithin-induced lesions in the white matter fiber tract, but not in the gray matter regions of cortex, were fully reversible at the morphological, functional and behavioral level. These findings indicate that remyelination of white and gray matter lesions have a different functional regeneration potential, with the white matter being able to regain full functionality while cortical gray matter lesions suffer from permanently altered network function. Therefore therapeutic interventions aiming for remyelination have to consider both region- and time-dependent strategies.

Early silent microstructural degeneration and atrophy of the thalamocortical network in multiple sclerosis

Recent studies on patients with clinically isolated syndrome (CIS) and multiple sclerosis (MS) demonstrated thalamic atrophy. Here we addressed the following question: Is early thalamic atrophy in patients with CIS and relapsing-remitting MS (RRMS) mainly a direct consequence of white matter (WM) lesions-as frequently claimed-or is the atrophy stronger correlated to "silent" (nonlesional) microstructural thalamic alterations? One-hundred and ten patients with RRMS, 12 with CIS, and 30 healthy controls were admitted to 3 T magnetic resonance imaging. Fractional anisotropy (FA) was computed from diffusion tensor imaging (DTI) to assess thalamic and WM microstructure. The relative thalamic volume (RTV) and thalamic FA were significantly reduced in patients with CIS and RRMS relative to healthy controls. Both measures were also correlated. The age, gender, WM lesion load, thalamic FA, and gray matter volume-corrected RTV were reduced even in the absence of thalamic and extensive white matter lesions-also in patients with short disease duration (≤24 months). A voxel-based correlation analysis revealed that the RTV reduction had a significant effect on local WM FA-in areas next to the thalamus and basal ganglia. These WM alterations could not be explained by WM lesions, which had a differing spatial distribution. Early thalamic atrophy is mainly driven by silent microstructural thalamic alterations. Lesions do not disclose the early damage of thalamocortical circuits, which seem to be much more affected in CIS and RRMS than expected. Thalamocortical damage can be detected by DTI in normal appearing brain tissue. Hum Brain Mapp 37:1866-1879, 2016. © 2016 Wiley Periodicals, Inc.

Mean cortical curvature reflects cytoarchitecture restructuring in mild traumatic brain injury

In the United States alone, the number of persons living with the enduring consequences of traumatic brain injuries is estimated to be between 3.2 and 5 million. This number does not include individuals serving in the United States military or seeking care at Veterans Affairs hospitals. The importance of understanding the neurobiological consequences of mild traumatic brain injury (mTBI) has increased with the return of veterans from conflicts overseas, many of who have suffered this type of brain injury. However, identifying the neuroanatomical regions most affected by mTBI continues to prove challenging. The aim of this study was to assess the use of mean cortical curvature as a potential indicator of progressive tissue loss in a cross-sectional sample of 54 veterans with mTBI compared to 31 controls evaluated with MRI. It was hypothesized that mean cortical curvature would be increased in veterans with mTBI, relative to controls, due in part to cortical restructuring related to tissue volume loss. Mean cortical curvature was assessed in 60 bilateral regions (31 sulcal, 29 gyral). Of the 120 regions investigated, nearly 50% demonstrated significantly increased mean cortical curvature in mTBI relative to controls with 25% remaining significant following multiple comparison correction (all, pFDR < .05). These differences were most prominent in deep gray matter regions of the cortex. Additionally, significant relationships were found between mean cortical curvature and gray and white matter volumes (all, p < .05). These findings suggest potentially unique patterns of atrophy by region and indicate that changes in brain microstructure due to mTBI are sensitive to measures of mean curvature.

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Mean cortical curvature was used to assess mTBI related changes to the cortex.

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Curvature was increased in widespread cortical regions in mTBI relative to controls.

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Increased curvature was linked with brain volumes differentially in gyri and sulci.

Identification of two clusters within schizophrenia with different structural, functional and clinical characteristics

BACKGROUND

Several biologically distinct subgroups may coexist within schizophrenia, which may hamper the necessary replicability to translate research findings into clinical practice.

METHODS

Cortical thickness, curvature and area values and subcortical volumes of 203 subjects (121 schizophrenia patients, out of which 64 were first episodes), 60 healthy controls and 22 bipolar patients were used to identify clusters using principal components and canonical discriminant analyses. Regional glucose metabolism using positron emission tomography, P300 event related potential, baseline clinical data and percentage of improvement with treatment were used to validate possible clusters based on MRI data.

RESULTS

All the controls, the bipolar patients and most of the schizophrenia patients were grouped in a cluster (cluster A). A group of 24 schizophrenia patients (12 first episodes), characterized by large intrinsic curvature values, was identified (cluster B). These patients, but not those in cluster A, showed reduced thalamic and cingulate glucose metabolism in comparison to controls, as well as a worsening of negative symptoms at follow-up. Patients in cluster A showed a significant putaminal metabolic increase, which was not observed for those in cluster B. P300 amplitude was reduced in patients of both clusters, in comparison to controls.

CONCLUSIONS

Results of this study support the existence of a biologically distinct group within the schizophrenia syndrome, characterized by increased cortical curvature values, reduced thalamic and cingulate metabolism, lack of the expected increased putaminal metabolism with antipsychotics and persistent negative symptoms.

Evidence for early, non-lesional cerebellar damage in patients with multiple sclerosis: DTI measures correlate with disability, atrophy, and disease duration

BACKGROUND

Common symptoms of multiple sclerosis (MS) such as gait ataxia, poor coordination of the hands, and intention tremor are usually the result of dysfunctionality in the cerebellum. Magnetic resonance imaging (MRI) has frequently failed to detect cerebellar damage in the form of inflammatory lesions in patients presenting with symptoms of cerebellar dysfunction.

OBJECTIVE

To detect microstructural cerebellar tissue alterations in early MS patients with a "normal appearing" cerebellum using diffusion tensor imaging (DTI).

METHODS

A total of 68 patients with relapsing-remitting MS (RRMS) and without cerebellar lesions and 26 age-matched healthy controls were admitted to high-resolution MRI and DTI to assess microstructure and volume of the cerebellar white matter (CBWM).

RESULTS

We found cerebellar fractional anisotropy (FA) and CBWM volume reductions in the group of 68 patients. Interestingly, a subgroup of these patients that was derived by including only patients with early and mild MS (N=23, median age 30 years, median Expanded Disability Status Scale =1.5, median duration 28 months) showed already cerebellar FA but no CBWM volume reductions. FA reductions were correlated with disability, atrophy, and disease duration.

CONCLUSION

"Normal appearing" cerebellar white matter can be damaged in a very early stage of RRMS. DTI seems to be a sensitive tool for detecting this hidden cerebellar damage.