Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis

Overweight and Obesity in Midlife and Brain Structure and Dementia 26 Years Later: The AGES-Reykjavik Study

High adiposity in midlife might increase risk for late-life brain pathology, including dementia. Using data from the prospective Age, Gene/Environment Susceptibility-Reykjavik Study of men and women (born 1907-1935), we studied the associations of overweight and obesity at midlife (mean age, 50 (standard deviation, 4.7) years) with 1.5-T brain magnetic resonance imaging measures of infarct-like brain lesions, cerebral microbleeds, total brain volume, and white matter lesions volume, as well as dementia, in late life (mean age, 76 (standard deviation, 5.2) years). We used linear and Poisson models to estimate associations in 3,864 persons after adjustment for sociodemographic, health, and lifestyle characteristics. In midlife, the prevalence of overweight was 39% and that of obesity was 8%. After a mean follow-up of 26.2 (standard deviation, 4.9) years, midlife overweight and obesity were not associated with infarct-like brain lesions (relative risk (RR) = 0.82, 95% confidence interval (CI): 0.61, 1.10), cerebral microbleeds (RR = 0.69, 95% CI: 0.37, 1.32), total brain volume (β = 0.05, 95% CI: -0.34, 0.45), white matter lesions volume (β = -0.10, 95% CI: -0.20, 0.01), or dementia (RR = 0.91, 95% CI: 0.49, 1.72) compared with normal weight. These findings do not support the hypothesis that high body mass index in midlife modulates the risk for dementia.

A greater involvement of posterior brain areas in interhemispheric transfer in autism: fMRI, DWI and behavioral evidences

A small corpus callosum (CC) is one of the most replicated neurobiological findings in autism spectrum (AS). However, its effect on interhemispheric (IH) communication is unknown. We combined structural (CC area and DWI), functional (task-related fMRI activation and connectivity analyses) as well as behavioral (Poffenberger and Purdue tasks) measures to investigate IH integration in adult AS individuals of typical intelligence. Despite similar behavioral IH transfer time and performances in bimanual tasks, the CC sub-regions connecting frontal and parietal cortical areas were smaller in AS than in non-AS individuals, while those connecting visual regions were similar. The activation of visual areas was lower in AS than in non-AS individuals during the presentation of visual stimuli. Behavioral IH performances were related to the properties of CC subregions connecting motor areas in non-AS individuals, but to the properties of posterior CC regions in AS individuals. Furthermore, there was greater functional connectivity between visual areas in the AS than in the non-AS group. Levels of connectivity were also stronger in visual than in motor regions in the autistic subjects, while the opposite was true for the non-autistic group. Thus, visual IH transfer plays an important role in visuo-motor tasks in AS individuals. These findings extend the well established enhanced role of perception in autistic cognition to visuo-motor IH information transfer.

•

The size of the corpus callosum connecting the motor region is reduced in autism.

•

The interhemispheric transfer of visuo-motor information is not impaired in autism.

•

In autism, the posterior corpus callosum is more involved than the motor sections.

•

Plastic reorganization in autism leads to atypical structure–function relationship.

•

The results agree with a greater involvement of perceptual brain areas in autism.

Automated Segmentation of Cerebellum Using Brain Mask and Partial Volume Estimation Map

While segmentation of the cerebellum is an indispensable step in many studies, its contrast is not clear because of the adjacent cerebrospinal fluid, meninges, and cerebra peduncle. Thus, various cerebellar segmentation methods, such as a deformable model or a template-based algorithm might exhibit incorrect segmentation of the venous sinuses and the cerebellar peduncle. In this study, we propose a fully automated procedure combining cerebellar tissue classification, a template-based approach, and morphological operations sequentially. The cerebellar region was defined approximately by removing the cerebral region from the brain mask. Then, the noncerebellar region was trimmed using a morphological operator and the brain-stem atlas was aligned to the individual brain to define the brain-stem area. The proposed method was validated with the well-known FreeSurfer and ITK-SNAP packages using the dice similarity index and recall and precision scores. As a result, the proposed method was significantly better than the other methods for the dice similarity index (0.93, FreeSurfer: 0.92, ITK-SNAP: 0.87) and precision (0.95, FreeSurfer: 0.90, ITK-SNAP: 0.93). Therefore, it could be said that the proposed method yielded a robust and accurate segmentation result. Moreover, additional postprocessing with the brain-stem atlas could improve its result.

The autism puzzle: Diffuse but not pervasive neuroanatomical abnormalities in children with ASD

Autism Spectrum Disorder (ASD) is a clinically diagnosed, heterogeneous, neurodevelopmental condition, whose underlying causes have yet to be fully determined. A variety of studies have investigated either cortical, subcortical, or cerebellar anatomy in ASD, but none have conducted a complete examination of all neuroanatomical parameters on a single, large cohort. The current study provides a comprehensive examination of brain development of children with ASD between the ages of 4 and 18 years who are carefully matched for age and sex with typically developing controls at a ratio of one-to-two. Two hundred and ten magnetic resonance images were examined from 138 Control (116 males and 22 females) and 72 participants with ASD (61 males and 11 females). Cortical segmentation into 78 brain-regions and 81,924 vertices was conducted with CIVET which facilitated a region-of-interest- (ROI-) and vertex-based analysis, respectively. Volumes for the cerebellum, hippocampus, striatum, pallidum, and thalamus and many associated subregions were derived using the MAGeT Brain algorithm. The study reveals cortical, subcortical and cerebellar differences between ASD and Control group participants. Diagnosis, diagnosis-by-age, and diagnosis-by-sex interaction effects were found to significantly impact total brain volume but not total surface area or mean cortical thickness of the ASD participants. Localized (vertex-based) analysis of cortical thickness revealed no significant group differences, even when age, age-range, and sex were used as covariates. Nonetheless, the region-based cortical thickness analysis did reveal regional changes in the left orbitofrontal cortex and left posterior cingulate gyrus, both of which showed reduced age-related cortical thinning in ASD. Our finding of region-based differences without significant vertex-based results likely indicates non-focal effects spanning the entirety of these regions. The hippocampi, thalamus, and globus pallidus, were smaller in volume relative to total cerebrum in the ASD participants. Various sub-structures showed an interaction of diagnosis-by-age, diagnosis-by-sex, and diagnosis-by-age-range, in the case where age was divided into childhood (age < 12) and adolescence (12 < age < 18). This is the most comprehensive imaging-based neuro-anatomical pediatric and adolescent ASD study to date. These data highlight the neurodevelopmental differences between typically developing children and those with ASD, and support aspects of the hypothesis of abnormal neuro-developmental trajectory of the brain in ASD.

•

Thorough analysis of neuroanatomical patterns in children and adolescents with ASD

•

Cortical, subcortical, and cerebellar development is assessed.

•

Total brain volume is smaller in males with ASD compared with Controls.

•

Cortical thickness in ASD does not decrease between childhood and adulthood.

•

Hippocampi, thalamus, globus pallidus and cerebellum are relatively smaller in ASD.

Brain and behavior in 48, XXYY syndrome

The phenotype of 48, XXYY syndrome (referred to as XXYY) is associated with characteristic but variable developmental, cognitive, behavioral and physical abnormalities. To discern the neuroanatomical phenotype of the syndrome, we conducted quantitative and qualitative analyses on MRI brain scans from 25 males with XXYY and 92 age and SES matched typically developing XY males. Quantitatively, males in the XXYY group had smaller gray and white matter volumes of the frontal and temporal lobes. Conversely, both gray and white matter volumes of the parietal lobe as well as lateral ventricular volume were larger in the XXYY group. Qualitatively, males in the XXYY group had a higher incidence of colpocephaly (84% vs. 34%, p ≤ 0.001), white matter lesions (25% vs. 5%, p = 0.007), and thin posterior body of the corpus callosum (28% vs. 3%, p = 0.001). The specificity of these findings may shed light on the role of the X and Y chromosomes in typical and atypical brain development and help provide direction for future studies of brain-behavior relationships in males with XXYY syndrome.

Alterations in cortical thickness development in preterm-born individuals: Implications for high-order cognitive functions

Very preterm birth (gestational age < 33 weeks) is associated with alterations in cortical thickness and with neuropsychological/behavioural impairments. Here we studied cortical thickness in very preterm born individuals and controls in mid-adolescence (mean age 15 years) and beginning of adulthood (mean age 20 years), as well as longitudinal changes between the two time points. Using univariate approaches, we showed both increases and decreases in cortical thickness in very preterm born individuals compared to controls. Specifically (1) very preterm born adolescents displayed extensive areas of greater cortical thickness, especially in occipitotemporal and prefrontal cortices, differences which decreased substantially by early adulthood; (2) at both time points, very preterm-born participants showed smaller cortical thickness, especially in parahippocampal and insular regions. We then employed a multivariate approach (support vector machine) to study spatially discriminating features between the two groups, which achieved a mean accuracy of 86.5%. The spatially distributed regions in which cortical thickness best discriminated between the groups (top 5%) included temporal, occipitotemporal, parietal and prefrontal cortices. Within these spatially distributed regions (top 1%), longitudinal changes in cortical thickness in left temporal pole, right occipitotemporal gyrus and left superior parietal lobe were significantly associated with scores on language-based tests of executive function. These results describe alterations in cortical thickness development in preterm-born individuals in their second decade of life, with implications for high-order cognitive processing.

•

Individuals born very preterm showed long-term alterations in cortical thickness

•

Such alterations affected predominantly frontal and temporal cortices

•

Multivariate analysis revealed between-group spatially discriminating features, with 86.5% accuracy

•

Longitudinal cortical thickness changes were associated with executive function scores

Age-specific MRI brain and head templates for healthy adults from 20 through 89 years of age

This study created and tested a database of adult, age-specific MRI brain and head templates. The participants included healthy adults from 20 through 89 years of age. The templates were done in five-year, 10-year, and multi-year intervals from 20 through 89 years, and consist of average T1W for the head and brain, and segmenting priors for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). It was found that age-appropriate templates provided less biased tissue classification estimates than age-inappropriate reference data and reference data based on young adult templates. This database is available for use by other investigators and clinicians for their MRI studies, as well as other types of neuroimaging and electrophysiological research.¹

Smoking normalizes cerebral blood flow and oxygen consumption after 12-hour abstention

Acute nicotine administration stimulates [(14)C]deoxyglucose trapping in thalamus and other regions of rat brain, but acute effects of nicotine and smoking on energy metabolism have rarely been investigated in human brain by positron emission tomography (PET). We obtained quantitative PET measurements of cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2) in 12 smokers who had refrained from smoking overnight, and in a historical group of nonsmokers, testing the prediction that overnight abstinence results in widespread, coupled reductions of CBF and CMRO2. At the end of the abstention period, global grey-matter CBF and CMRO2 were both reduced by 17% relative to nonsmokers. At 15 minutes after renewed smoking, global CBF had increased insignificantly, while global CMRO2 had increased by 11%. Regional analysis showed that CMRO2 had increased in the left putamen and thalamus, and in right posterior cortical regions at this time. At 60 and 105 minutes after smoking resumption, CBF had increased by 8% and CMRO2 had increased by 11-12%. Thus, we find substantial and global impairment of CBF/CMRO2 in abstaining smokers, and acute restoration by resumption of smoking. The reduced CBF and CMRO2 during acute abstention may mediate the cognitive changes described in chronic smokers.

The trajectory of gray matter development in Broca's area is abnormal in people who stutter

The acquisition and mastery of speech-motor control requires years of practice spanning the course of development. People who stutter often perform poorly on speech-motor tasks thereby calling into question their ability to establish the stable neural motor programs required for masterful speech-motor control. There is evidence to support the assertion that these neural motor programs are represented in the posterior part of Broca’s area, specifically the left pars opercularis. Consequently, various theories of stuttering causation posit that the disorder is related to a breakdown in the formation of the neural motor programs for speech early in development and that this breakdown is maintained throughout life. To date, no study has examined the potential neurodevelopmental signatures of the disorder across pediatric and adult populations. The current study aimed to fill this gap in our knowledge. We hypothesized that the developmental trajectory of cortical thickness in people who stutter would differ across the lifespan in the left pars opercularis relative to a group of control participants. We collected structural magnetic resonance images from 116 males (55 people who stutter) ranging in age from 6 to 48 years old. Differences in cortical thickness across ages and between patients and controls were investigated in 30 brain regions previously implicated in speech-motor control. An interaction between age and group was found for the left pars opercularis only. In people who stutter, the pars opercularis did not demonstrate the typical maturational pattern of gradual gray matter thinning with age across the lifespan that we observed in control participants. In contrast, the developmental trajectory of gray matter thickness in other regions of interest within the neural network for speech-motor control was similar for both groups. Our findings indicate that the developmental trajectory of gray matter in left pars opercularis is abnormal in people who stutter.

Prediction of brain maturity based on cortical thickness at different spatial resolutions

Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity.

Test-retest reliability of white matter structural brain networks: a multiband diffusion MRI study

The multiband EPI sequence has been developed for the human connectome project to accelerate MRI data acquisition. However, no study has yet investigated the test-retest (TRT) reliability of the graph metrics of white matter (WM) structural brain networks constructed from this new sequence. Here, we employed a multiband diffusion MRI (dMRI) dataset with repeated scanning sessions and constructed both low- and high-resolution WM networks by volume- and surface-based parcellation methods. The reproducibility of network metrics and its dependence on type of construction procedures was assessed by the intra-class correlation coefficient (ICC). We observed conserved topological architecture of WM structural networks constructed from the multiband dMRI data as previous findings from conventional dMRI. For the global network properties, the first order metrics were more reliable than second order metrics. Between two parcellation methods, networks with volume-based parcellation showed better reliability than surface-based parcellation, especially for the global metrics. Between different resolutions, the high-resolution network exhibited higher TRT performance than the low-resolution in terms of the global metrics with a large effect size, whereas the low-resolution performs better in terms of local (region and connection) properties with a relatively low effect size. Moreover, we identified that the association and primary cortices showed higher reproducibility than the paralimbic/limbic regions. The important hub regions and rich-club connections are more reliable than the non-hub regions and connections. Finally, we found WM networks from the multiband dMRI showed higher reproducibility compared with those from the conventional dMRI. Together, our results demonstrated the fair to good reliability of the WM structural brain networks from the multiband EPI sequence, suggesting its potential utility for exploring individual differences and for clinical applications.

Automated identification of brain new lesions in multiple sclerosis using subtraction images

PURPOSE

To propose and evaluate a new automated method for the identification of new/enlarging multiple sclerosis (MS) lesions on subtracted images (SI). The subtraction of serially acquired images has shown great potential in assessing new/enlarging brain magnetic resonance imaging (MRI) lesions in MS patients. However, this approach relies on the manual definition of lesions, which is labor-intensive and subject to operator-dependent variability.

MATERIALS AND METHODS

An overestimated mask of candidate SI lesions was created and then these hyperintense voxel clusters were filtered using specific constraints for extent, shape, and intensity. The method was tested on normal and pathological MRI datasets.

RESULTS

The automated method did not detect hyperintense voxels on SI of healthy controls. SI lesions were identified manually and automatically in a multicenter MS dataset of 19 patients with paired MRI over 36 weeks. Sensitivity of the method was high (0.91) and in agreement with the results of manually defined SI lesions (Cohen's k=0.82,95% confidence interval [CI]: 0.77–0.87). On a second multicenter MS dataset of 103 patients with paired MRI over 76 weeks, the number of SI lesions detected automatically correlated with the number of gadolinium-enhancing lesions(r=0.74).

CONCLUSION

The proposed method is robust, accurate,and sensitive and may be used with confidence in Phase II MS trials.

Early visual deprivation changes cortical anatomical covariance in dorsal-stream structures

Early blind individuals possess thicker occipital cortex compared to sighted ones. Occipital cortical thickness is also predictive of performance on several auditory discrimination tasks in the blind, which suggests that it can serve as a neuroanatomical marker of auditory behavioural abilities. In light of this atypical relationship between occipital thickness and auditory function, we sought to investigate here the covariation of occipital cortical morphology in occipital areas with that of all other areas across the cortical surface, to assess whether the anatomical covariance with the occipital cortex differs between early blind and sighted individuals. We observed a reduction in anatomical covariance between the right occipital cortex and several areas of the visual dorsal stream in a group of early blind individuals relative to sighted controls. In a separate analysis, we show that the performance of the early blind in a transposed melody discrimination task was strongly predicted by the strength of the cortical covariance between the occipital cortex and intraparietal sulcus, a region for which cortical thickness in the sighted was previously shown to predict performance in the same task. These findings therefore constitute the first evidence linking altered anatomical covariance to early sensory deprivation. Moreover, since covariation of cortical morphology could potentially be related to anatomical connectivity or driven by experience-dependent plasticity, it could consequently help guide future functional connectivity and diffusion tractography studies.

Altered cortical thickness related to clinical severity but not the untreated disease duration in schizophrenia

Although previous studies have reported deficits in the gray matter volume of schizophrenic patients, it remains unclear whether these deficits occur at the onset of the disease, before treatment, and whether they are progressive over the duration of untreated disease. Furthermore, the gray matter volume represents the combinations of cortical thickness and surface area; these features are believed to be influenced by different genetic factors. However, cortical thickness and surface area in antipsychotic-naive first-episode schizophrenic patients have seldom been investigated. Here, the cortical thicknesses and surface areas of 128 antipsychotic-naive first-episode schizophrenic patients were compared with 128 healthy controls. The patients exhibited significantly lower cortical thickness, primarily in the bilateral prefrontal and parietal cortex, and increased thickness in the bilateral anterior temporal lobes, left medial orbitofrontal cortex, and left cuneus. Furthermore, decreased cortical thickness was related to positive schizophrenia symptoms but not to the severity of negative symptoms and the untreated disease duration. No significant difference of surface area was observed between the 2 groups. Thus, without the confounding factors of medication and illness progression, this study provides further evidence to support anatomical deficits in the prefrontal and parietal cortex early in course of the illness. The increased thicknesses of the bilateral anterior temporal lobes may represent a compensatory factor or may be an early-course neuronal pathology caused by preapoptotic osmotic changes or hypertrophy. Furthermore, these anatomical deficits are crucial to the pathogenesis of positive symptoms and relatively stable instead of progressing during the early stages of the disease.

Detection of abnormal resting-state networks in individual patients suffering from focal epilepsy: an initial step toward individual connectivity assessment

The spatial coherence of spontaneous slow fluctuations in the blood-oxygen-level dependent (BOLD) signal at rest is routinely used to characterize the underlying resting-state networks (RSNs). Studies have demonstrated that these patterns are organized in space and highly reproducible from subject to subject. Moreover, RSNs reorganizations have been suggested in pathological conditions. Comparisons of RSNs organization have been performed between groups of subjects but have rarely been applied at the individual level, a step required for clinical application. Defining the notion of modularity as the organization of brain activity in stable networks, we propose Detection of Abnormal Networks in Individuals (DANI) to identify modularity changes at the individual level. The stability of each RSN was estimated using a spatial clustering method: Bootstrap Analysis of Stable Clusters (BASC) (Bellec et al., 2010). Our contributions consisted in (i) providing functional maps of the most stable cores of each networks and (ii) in detecting “abnormal” individual changes in networks organization when compared to a population of healthy controls. DANI was first evaluated using realistic simulated data, showing that focussing on a conservative core size (50% most stable regions) improved the sensitivity to detect modularity changes. DANI was then applied to resting state fMRI data of six patients with focal epilepsy who underwent multimodal assessment using simultaneous EEG/fMRI acquisition followed by surgery. Only patient with a seizure free outcome were selected and the resected area was identified using a post-operative MRI. DANI automatically detected abnormal changes in 5 out of 6 patients, with excellent sensitivity, showing for each of them at least one “abnormal” lateralized network closely related to the epileptic focus. For each patient, we also detected some distant networks as abnormal, suggesting some remote reorganization in the epileptic brain.

Puberty and testosterone shape the corticospinal tract during male adolescence

Some of the known sex differences in white matter emerge during adolescence. Here, we replicate and extend our previous findings of sex differences in the structure of the corticospinal tract (Perrin et al. 2009; Hervé et al. 2009). In a large normative sample of adolescents, we observed age × sex interactions in the signal intensity of T1-weighted (T1W) images (n = 941) and in magnetization transfer ratio (MTR; n = 761); both features were inversely associated with age in males but not in females. Moreover, we hypothesized that the age-related differences in CST structure exhibited by males would be mediated by differences in puberty stage and levels of bioavailable testosterone. We confirmed this prediction using mediation analysis with bootstrapping. These findings suggest that sex differences in the CST structure observed during male adolescence may be due to multiple processes associated with puberty, including (but not limited to) the rising levels of testosterone.

Dissociation of glutamate and cortical thickness is restricted to regions subserving trait but not state markers in major depressive disorder

BACKGROUND

The anterior cingulate cortex (ACC) plays an important role in the neuropathology of major depressive disorder (MDD). So far, the effect of local cortical alteration on metabolites in multiple subdivisions of ACC has not been studied. We aimed to investigate structural and biochemical changes and their relationship in the pregenual ACC (pgACC), dorsal ACC (dACC) in MDD.

METHODS

We obtained magnetic resonance spectroscopy (MRS) in two investigated regions for 24 depressed patients and matched controls. In each region, cortical thickness (CTh) was calculated within a template mask based on its MRS voxel. We investigated neurotransmitter concentrations of Glx, N-acetyl aspartate (NAA), and myo-inositol (m-Ins) in two investigated regions, as well as their relationships with CTh in depressed individuals and healthy controls.

RESULTS

Patients showed significantly lower cortical thickness in dACC compared to controls. Glx in dACC significantly correlated with CTh in healthy controls but not MDD patients, while NAA and CTh in dACC significantly correlated in both groups. A marginal decrease of Glx in pgACC was found in the subgroup of more severely depressive patients, compared to the mildly depressed patients.

LIMITATIONS

Modest sample size and lack of episodes of depression may limit the generalizability of our findings.

CONCLUSION

Our results indicate an abolished CTh-MRS relation in dACC-associated with structural decline-but not in pgACC, where acute MRS alterations prevailed. Our study provides the first evidence of a neurochemical basis explaining some of the inter-individual variability in CTh in MDD.

Hierarchical multivariate covariance analysis of metabolic connectivity

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Asymmetrical effect of levodopa on the neural activity of motor regions in PD

Parkinson's disease (PD) is a neurodegenerative illness often characterized by asymmetrical symptoms. However, the reason for this asymmetry and the cerebral correlates underlying symptom asymmetry are still not well understood. Furthermore, the effects of levodopa on the cerebral correlates of disease asymmetry have not been investigated. In this study, right-handed PD patients performed self-initiated, externally triggered and repetitive control finger movements with both their right and left hands during functional magnetic resonance imaging (fMRI) to investigate asymmetrical effects of levodopa on the hemodynamic correlates of finger movements. Patients completed two experimental sessions OFF and ON medication after a minimum of 12 hours medication withdrawal. We compared the effect of levodopa on the neural activation patterns underlying the execution of both the more affected and less affected hand for self-initiated and externally triggered movements. Our results show that levodopa led to larger differences in cerebral activity for movements of the more affected, left side: there were significant differences in activity after levodopa administration in regions of the motor cortico-striatal network when patients performed self-initiated and externally triggered movements with their left hand. By contrast, when patients used their right hand, levodopa led to differences in cerebellar activity only. As our patients were affected more severely on their left side, we propose that levodopa may help provide additional dopaminergic input, improving movements for the more severely affected side. These results suggest that the impact of reduced dopamine in the cortico-striatal system and the action of levodopa is not symmetrical.

Cortical thickness maturation and duration of music training: health-promoting activities shape brain development

OBJECTIVE

To assess the extent to which playing a musical instrument is associated with cortical thickness development among healthy youths.

METHOD

Participants were part of the National Institutes of Health (NIH) Magnetic Resonance Imaging (MRI) Study of Normal Brain Development. This study followed a longitudinal design such that participants underwent MRI scanning and behavioral testing on up to 3 separate visits, occurring at 2-year intervals. MRI, IQ, and music training data were available for 232 youths (334 scans), ranging from 6 to 18 years of age. Cortical thickness was regressed against the number of years that each youth had played a musical instrument. Next, thickness was regressed against an "Age × Years of Playing" interaction term. Age, gender, total brain volume, and scanner were controlled for in analyses. Participant ID was entered as a random effect to account for within-person dependence. False discovery rate correction was applied (p ≤ .05).

RESULTS

There was no association between thickness and years playing a musical instrument. The "Age × Years of Playing" interaction was associated with thickness in motor, premotor, and supplementary motor cortices, as well as prefrontal and parietal cortices. Follow-up analysis revealed that music training was associated with an increased rate of thickness maturation. Results were largely unchanged when IQ and handedness were included as covariates.

CONCLUSION

Playing a musical instrument was associated with more rapid cortical thickness maturation within areas implicated in motor planning and coordination, visuospatial ability, and emotion and impulse regulation. However, given the quasi-experimental nature of this study, we cannot rule out the influence of confounding variables.

Computer-assisted delineation of lung tumor regions in treatment planning CT images with PET/CT image sets based on an optimum contour selection method

To assist radiation oncologists in the delineation of tumor regions during treatment planning for lung cancer, we have proposed an automated contouring algorithm based on an optimum contour selection (OCS) method for treatment planning computed tomography (CT) images with positron emission tomography (PET)/CT images. The basic concept of the OCS is to select a global optimum object contour based on multiple active delineations with a level set method around tumors. First, the PET images were registered to the planning CT images by using affine transformation matrices. The initial gross tumor volume (GTV) of each lung tumor was identified by thresholding the PET image at a certain standardized uptake value, and then each initial GTV location was corrected in the region of interest of the planning CT image. Finally, the contours of final GTV regions were determined in the planning CT images by using the OCS. The proposed method was evaluated by testing six cases with a Dice similarity coefficient (DSC), which denoted the degree of region similarity between the GTVs contoured by radiation oncologists and the proposed method. The average three-dimensional DSC for the six cases was 0.78 by the proposed method, but only 0.34 by a conventional method based on a simple level set method. The proposed method may be helpful for treatment planners in contouring the GTV regions.

Dopamine transporter SLC6A3 genotype affects cortico-striatal activity of set-shifts in Parkinson's disease

Parkinson's disease is a neurodegenerative condition that affects motor function along with a wide range of cognitive domains, including executive function. The hallmark of the pathology is its significant loss of nigrostriatal dopamine, which is necessary for the cortico-striatal interactions that underlie executive control. Striatal dopamine reuptake is mediated by the SLC6A3 gene (formerly named DAT1) and its polymorphisms, which have been largely overlooked in Parkinson's disease. Thirty patients (ages 53-68 years; 19 males, 11 females) at early stages of Parkinson's disease, were genotyped according to a 9-repeat (9R) or 10-repeat (10R) allele on the SLC6A3/DAT1 gene. They underwent neuropsychological assessment and functional magnetic resonance imaging while performing a set-shifting task (a computerized Wisconsin Card Sorting Task) that relies on fronto-striatal interactions. Patients homozygous on the 10R allele performed significantly better on working memory tasks than 9R-carrier patients. Most importantly, patients carrying a 9R allele exhibited less activation than their 10R homozygous counterparts in the prefrontal cortex, premotor cortex and caudate nucleus, when planning and executing a set-shift. This pattern was exacerbated for conditions that usually recruit the striatum compared to those that do not. This is the first study indicating that the SLC6A3/DAT1 genotype has a significant effect on fronto-striatal activation and performance in Parkinson's disease. This effect is stronger for conditions that engage the striatum. Longitudinal studies are warranted to assess this polymorphism's effect on the clinical evolution of patients with Parkinson's disease, especially with cognitive decline.

A case-control study of brain structure and behavioral characteristics in 47,XXX syndrome

Trisomy X, the presence of an extra X chromosome in females (47,XXX), is a relatively common but under-recognized chromosomal disorder associated with characteristic cognitive and behavioral features of varying severity. The objective of this study was to determine whether there were neuroanatomical differences in girls with Trisomy X that could relate to cognitive and behavioral differences characteristic of the disorder during childhood and adolescence. MRI scans were obtained on 35 girls with Trisomy X (mean age 11.4, SD 5.5) and 70 age- and sex-matched healthy controls. Cognitive and behavioral testing was also performed. Trisomy X girls underwent a semi-structured psychiatric interview. Regional brain volumes and cortical thickness were compared between the two groups. Total brain volume was significantly decreased in subjects with Trisomy X, as were all regional volumes with the exception of parietal gray matter. Differences in cortical thickness had a mixed pattern. The subjects with Trisomy X had thicker cortex in bilateral medial prefrontal cortex and right medial temporal lobe, but decreased cortical thickness in both lateral temporal lobes. The most common psychiatric disorders present in this sample of Trisomy X girls included anxiety disorders (40%), attention-deficit disorder (17%) and depressive disorders (11%). The most strongly affected brain regions are consistent with phenotypic characteristics such as language delay, poor executive function and heightened anxiety previously described in population-based studies of Trisomy X and also found in our sample.

Birth size and brain function 75 years later

BACKGROUND

There are several lines of evidence pointing to fetal and other early origins of diseases of the aging brain, but there are no data directly addressing the hypotheses in an older population. We investigated the association of fetal size to late-age measures of brain structure and function in a large cohort of older men and women and explored the modifying effect of education on these associations.

METHODS

Within the AGES (Age Gene/Environment Susceptibility)-Reykjavik population-based cohort (born between 1907 and 1935), archived birth records were abstracted for 1254 men and women who ∼75 years later underwent an examination that included brain MRI and extensive cognitive assessment.

RESULTS

Adjustment for intracranial volume, demographic and medical history characteristics, and lower Ponderal index at birth (per kg/m(3)), an indicator of third-trimester fetal wasting, was significantly associated with smaller volumes of total brain and white matter; βs (95% confidence intervals) were -1.0 (-1.9 to -0.0) and -0.5 (-1.0 to -0.0) mL. Furthermore, lower Ponderal index was associated with slower processing speed and reduced executive functioning but only in those with low education (β [95% confidence interval]: -0.136 [-0.235 to -0.036] and -0.077 [-0.153 to -0.001]).

CONCLUSIONS

This first study of its kind provides clinical measures suggesting that smaller birth size, as an indicator of a suboptimal intrauterine environment, is associated with late-life alterations in brain tissue volume and function. In addition, it shows that the effects of a suboptimal intrauterine environment on late-life cognitive function were present only in those with lower educational levels.

Adiposity is associated with structural properties of the adolescent brain

Obesity, a major risk factor for cardiometabolic disease, is associated with variations in a number of structural properties in the adult brain, as assessed with magnetic resonance imaging (MRI). In this study, we investigated the cross-sectional relationship between visceral fat (VF), total body fat (TBF) and three MRI parameters in the brains of typically developing adolescents: (i) T1-weighted (T1W) signal intensity; (ii) T1W signal contrast between white matter (WM) and gray matter (GM); and (iii) magnetization transfer ratio (MTR). In a community-based sample of 970 adolescents (12-18 years old, 466 males), VF was quantified using MRI, and total body fat was measured using a multifrequency bioimpedance. T1W images of the brain were used to determine signal intensity in lobar GM and WM, as well as WM:GM signal contrast. A magnetization transfer (MT) sequence of MT(ON) and MT(OFF) was used to obtain MTR in GM and WM. We found that both larger volumes of VF and more TBF were independently associated with higher signal intensity in WM and higher WM:GM signal contrast, as well as higher MTR in both GM and WM. These relationships were independent of a number of potential confounders, including age, sex, puberty stage, household income and height. Our results suggest that both visceral fat and fat deposited elsewhere in the body are associated independently with structural properties of the adolescent brain. We speculate that these relationships suggest the presence of adiposity-related variations in phospholipid composition of brain lipids.

Sex differences in neocortical structure and cognitive performance: A surface-based morphometry study

On average, men show larger brain volumes than women. Regional differences have been also observed, although most of the available studies apply voxel-based morphometry (VBM). Reports applying surface-based morphometry (SBM) have been focused mainly on cortical thickness (CT). Here we apply SBM for obtaining global and regional indices of CT, cortical surface area (CSA), and cortical gray matter volume (CGMV) from samples of men (N=40) and women (N=40) matched for their performance on four cognitive factors varying in their complexity: processing speed, attention control, working memory capacity, and fluid intelligence. These were the main findings: 1) CT and CSA produced very weak correlations in both sexes, 2) men showed larger values in CT, CSA, and CGMV, and 3) cognitive performance was unrelated to brain structural variation within sexes. Therefore, we found substantial group differences in brain structure, but there was no relationship with cognitive performance both between and within-sexes.

Illness denial in schizophrenia spectrum disorders: a function of left hemisphere dominance

Impaired illness awareness or anosognosia is a common, but poorly understood feature of schizophrenia that contributes to medication nonadherence and poor treatment outcomes. Here we present a functional imaging study to measure brain activity at the moment of illness denial. To accomplish this, participants with schizophrenia (n = 18) with varying degrees of illness awareness were confronted with their illness beliefs while undergoing functional MRI. To link structure with function, we explored the relationships among impaired illness awareness and brain activity during the illness denial task with cortical thickness. Impaired illness awareness was associated with increased brain activity in the left temporoparieto-occipital junction (TPO) and left medial prefrontal cortex (mPFC) at the moment of illness denial. Brain activity in the left mPFC appeared to be a function of participants' degree of self-reflectiveness, while the activity in the left TPO was associated with cortical thinning in this region and more specific to illness denial. Participants with impaired illness awareness had slower response times to illness related stimuli than those with good illness awareness. Increased left hemisphere brain activity in association with illness denial is consistent with the literature in other neuropsychiatric conditions attributing anosognosia or impaired illness awareness to left hemisphere dominance. The TPO and mPFC may represent putative targets for noninvasive treatment interventions, such as transcranial magnetic or direct current stimulation.

White matter lesion filling improves the accuracy of cortical thickness measurements in multiple sclerosis patients: a longitudinal study

Background

Previous studies have demonstrated that white matter (WM) lesions bias automated brain tissue classifications and cerebral volume measurements. However, filling WM lesions using the intensity of neighbouring normal-appearing WM has been shown to increase the accuracy of automated volume measurements in the brain. In the present study, we investigate the influence of WM lesions on cortical thickness (CTh) measures and assessed the impact of lesion filling on both cross-sectional/longitudinal and global/regional measurements of CTh in multiple sclerosis (MS) patients.

Methods

Fifty MS patients were studied at baseline as well as after three and six years of follow-up. CTh was estimated using a fully automated pipeline (CIVET) on T1-weighted magnetic resonance images data acquired at 1.5 Tesla without (original) and with WM lesion filling (filled). WM lesions were semi-automatically segmented and then filled with the mean intensity of the neighbouring voxels. For both original and filled T1 images we investigated and compared the main CIVET’s steps: tissue classification, surfaces generation and CTh measurement.

Results

On the original T1 images, the majority of WM lesion volume (72%) was wrongly classified as gray matter (GM). After lesion filling the accuracy of WM lesions classification improved significantly (p < 0.001, 94% of WM lesion volume correctly classified) as well as the WM surface generation (p < 0.0001). The mean CTh computed on the original T1 images, overall time points, was significantly thinner (p < 0.001) compared the CTh estimated on the filled T1 images. The vertex-wise longitudinal analysis performed on the filled T1 images showed an increased number of vertices in the fronto-temporal region with a significantly decrease of CTh over time compared the analysis performed on the original images.

Conclusion

These results indicate that WM lesions bias the CTh estimation both cross-sectionally as well as longitudinally. The lesion filling approach significantly improved the accuracy of the regional CTh estimation and has an impact also on the global estimation of CTh.

Globally Divergent but Locally Convergent X- and Y-Chromosome Influences on Cortical Development

Owing to their unique evolutionary history, modern mammalian X- and Y-chromosomes have highly divergent gene contents counterbalanced by regulatory features, which preferentially restrict expression of X- and Y-specific genes. These 2 characteristics make opposing predictions regarding the expected dissimilarity of X- vs. Y-chromosome influences on biological structure and function. Here, we quantify this dissimilarity using in vivo neuroimaging within a rare cohort of humans with diverse sex chromosome aneuploidies (SCAs). We show that X- and Y-chromosomes have opposing effects on overall brain size but exert highly convergent influences on local brain anatomy, which manifest across biologically distinct dimensions of the cerebral cortex. Large-scale online meta-analysis of functional neuroimaging data indicates that convergent sex chromosome dosage effects preferentially impact centers for social perception, communication, and decision-making. Thus, despite an almost complete lack of sequence homology, and opposing effects on overall brain size, X- and Y-chromosomes exert congruent effects on the proportional size of cortical systems involved in adaptive social functioning. These convergent X-Y effects (i) track the dosage of those few genes that are still shared by X- and Y-chromosomes, and (ii) may provide a biological substrate for the link between SCA and increased rates of psychopathology.

Pydpiper: a flexible toolkit for constructing novel registration pipelines

Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available software package that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines “out-of-the-box.” In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code.

Neuroanatomical correlates of behavioral rating versus performance measures of working memory in typically developing children and adolescents

OBJECTIVE

The frequent lack of correspondence between performance and observational measures of executive functioning, including working memory, has raised questions about the validity of the observational measures. This study was conducted to investigate sources of this discrepancy through correlation of volumetric and cortical thickness (CT) neuroimaging values with performance and questionnaire measures of working memory (WM).

METHODS

Using longitudinal data from the NIH MRI Study of Normal Brain Development (Volumes, N= 347, 54.3% female; CT, N= 350, 54.6% female; age range: 6 to 16.9 years), scores on the Behavioral Rating Inventory of Executive Function (BRIEF) WM, Emotional Control (EC) and Inhibition (INH) scales; Wechsler Scale of Intelligence for Children-III Digit Span; and Cambridge Neuropsychological Test Battery Spatial Working Memory (CANTAB SWM) were correlated with each other and with morphometric measurements using mixed effects linear regression models.

RESULTS

BRIEF WM was correlated with CANTAB SWM (p < .001). With whole brain correction, BRIEF WM and EC were both correlated with CT of the posterior parahippocampal gyrus (PHG), EC on the right side only. Performance measures of WM were unrelated to lobar volumes or CT, but were associated with volumes of hippocampus and amygdala.

CONCLUSIONS

The known role of PHG in contextual learning suggests that the BRIEF WM assesses contextualized learning/memory, potentially explaining its loose correspondence to the decontextualized performance measures. Observational measures can be useful and valid functional metrics, complementing performance measures. Labels used to characterize scales should be interpreted with caution, however.

Cortical thinning in temporo-parietal junction (TPJ) in non-affective first-episode of psychosis patients with persistent negative symptoms

BACKGROUND

Negative symptoms represent an unmet therapeutic need in many patients with schizophrenia. In an extension to our previous voxel-based morphometry findings, we employed a more specific, vertex-based approach to explore cortical thinning in relation to persistent negative symptoms (PNS) in non-affective first-episode of psychosis (FEP) patients to advance our understanding of the pathophysiology of primary negative symptoms.

METHODS

This study included 62 non-affective FEP patients and 60 non-clinical controls; 16 patients were identified with PNS (i.e., at least 1 primary negative symptom at moderate or greater severity sustained for at least 6 consecutive months). Using cortical thickness analyses, we explored for differences between PNS and non-PNS patients as well as between each patient group and healthy controls; cut-off threshold was set at p<0.01, corrected for multiple comparisons.

RESULTS

A thinner cortex prominently in the right superior temporal gyrus extending into the temporo-parietal junction (TPJ), right parahippocampal gyrus, and left orbital frontal gyrus was identified in PNS patients vs. non-PNS patients. Compared with healthy controls, PNS patients showed a thinner cortex prominently in the right superior temporal gyrus, right parahippocampal gyrus, and right cingulate; non-PNS patients showed a thinner cortex prominently in the parahippocampal gyrus bi-laterally.

CONCLUSION

Cortical thinning in the early stages of non-affective psychosis is present in the frontal and temporo-parietal regions in patients with PNS. With these brain regions strongly related to social cognitive functioning, our finding suggests a potential link between primary negative symptoms and social cognitive deficits through common brain etiologies.

Trail making test performance in youth varies as a function of anatomical coupling between the prefrontal cortex and distributed cortical regions

While researchers have gained a richer understanding of the neural correlates of executive function in adulthood, much less is known about how these abilities are represented in the developing brain and what structural brain networks underlie them. Thus, the current study examined how individual differences in executive function, as measured by the Trail Making Test (TMT), relate to structural covariance in the pediatric brain. The sample included 146 unrelated, typically developing youth (80 females), ages 9-14 years, who completed a structural MRI scan of the brain and the Halstead-Reitan TMT (intermediate form). TMT scores used to index executive function included those that evaluated set-shifting ability: Trails B time (number-letter sequencing) and the difference in time between Trails B and A (number sequencing only). Anatomical coupling was measured by examining correlations between mean cortical thickness (MCT) across the entire cortical ribbon and individual vertex thickness measured at ~81,000 vertices. To examine how TMT scores related to anatomical coupling strength, linear regression was utilized and the interaction between age-normed TMT scores and both age and sex-normed MCT was used to predict vertex thickness. Results revealed that stronger Trails B scores were associated with greater anatomical coupling between a large swath of prefrontal cortex and the rest of cortex. For the difference between Trails B and A, a network of regions in the frontal, temporal, and parietal lobes was found to be more tightly coupled with the rest of cortex in stronger performers. This study is the first to highlight the importance of structural covariance in in the prediction of individual differences in executive function skills in youth. Thus, it adds to the growing literature on the neural correlates of childhood executive functions and identifies neuroanatomic coupling as a biological substrate that may contribute to executive function and dysfunction in childhood.

MBIS: multivariate Bayesian image segmentation tool

We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.

Local cortical thinning links to resting-state disconnectivity in major depressive disorder

BACKGROUND

Local structural and metabolic as well as inter-regional connectivity abnormalities have been implicated in the neuropathology of major depressive disorder (MDD). How local tissue properties affect intrinsic functional connectivity is, however, unclear. Using a cross-sectional, multi-modal imaging approach, we investigated the relationship between local cortical tissue abnormalities and intrinsic resting-state functional connectivity (RSFC) in MDD.

METHOD

A total of 20 MDD in-patients and 20 healthy controls underwent magnetic resonance imaging at 3 T for structural and functional imaging. Whole-brain cortical thickness was calculated and compared between groups. Regions with reduced cortical thickness defined seeds for subsequent whole-brain RSFC analyses. Contributions of structural tissue abnormalities on inter-regional RSFC were explicitly investigated.

RESULTS

Lower cortical thickness was observed in MDD in the right dorsomedial prefrontal cortex (PFC), superior temporal gyrus/temporal pole, middle-posterior cingulate cortex, and dorsolateral PFC. No differences in local fractional amplitude of low-frequency fluctuations were observed. Lower thickness in patients' dorsomedial PFC further directly and selectively affected its RSFC with the precuneus, which was unaffected by symptom severity. No effects of cortical thickness in other regions showing abnormal thickness were observed to influence functional connectivity.

CONCLUSIONS

Abnormal cortical thickness in the dorsomedial PFC in MDD patients was observed to selectively and directly affect its intrinsic connectivity with the precuneus in MDD patients independent of depression severity, thereby marking a potential vulnerability for maladaptive mood regulation. Future studies should include an unmedicated sample and replicate findings using independent component analysis to test for morphometric effects on network integrity.

Cortical thinning in temporo-parietal junction (TPJ) in non-affective first-episode of psychosis patients with persistent negative symptoms

BACKGROUND

Negative symptoms represent an unmet therapeutic need in many patients with schizophrenia. In an extension to our previous voxel-based morphometry findings, we employed a more specific, vertex-based approach to explore cortical thinning in relation to persistent negative symptoms (PNS) in non-affective first-episode of psychosis (FEP) patients to advance our understanding of the pathophysiology of primary negative symptoms.

METHODS

This study included 62 non-affective FEP patients and 60 non-clinical controls; 16 patients were identified with PNS (i.e., at least 1 primary negative symptom at moderate or greater severity sustained for at least 6 consecutive months). Using cortical thickness analyses, we explored for differences between PNS and non-PNS patients as well as between each patient group and healthy controls; cut-off threshold was set at p<0.01, corrected for multiple comparisons.

RESULTS

A thinner cortex prominently in the right superior temporal gyrus extending into the temporo-parietal junction (TPJ), right parahippocampal gyrus, and left orbital frontal gyrus was identified in PNS patients vs. non-PNS patients. Compared with healthy controls, PNS patients showed a thinner cortex prominently in the right superior temporal gyrus, right parahippocampal gyrus, and right cingulate; non-PNS patients showed a thinner cortex prominently in the parahippocampal gyrus bi-laterally.

CONCLUSION

Cortical thinning in the early stages of non-affective psychosis is present in the frontal and temporo-parietal regions in patients with PNS. With these brain regions strongly related to social cognitive functioning, our finding suggests a potential link between primary negative symptoms and social cognitive deficits through common brain etiologies.

Cortical thinning correlates with cognitive change in multiple sclerosis but not in neuromyelitis optica

OBJECTIVES

To compare spatial patterns of cortical thickness alterations in neuromyelitis optica (NMO) and multiple sclerosis (MS); and to investigate the correlations between cortical thinning and clinical variables in NMO and MS.

METHODS

We studied 23 patients with NMO, 27 patients with MS and 26 healthy controls (HCs). The global, brain region and vertex-based cortical thickness (CTh) were analysed and compared among the three groups. A general linear model was used to investigate the correlations between cortical thinning and clinical measures.

RESULTS

A limited number of cortical regions in visual cortex were found to be significantly thinner in NMO patients than in HCs. The MS patients exhibited more widespread cortical thinning compared with HCs, and significantly greater cortical thinning in the insula and the parahippocampus compared with NMO. The extent of cortical thinning in several brain regions correlated with cognitive measures in MS, but not in NMO.

CONCLUSIONS

Neocortical thinning in NMO mainly affects visual cortex, while MS patients show much more extensive cortical thinning. Cognitive changes are correlated with cortical atrophy in MS not in NMO. The substrates of cognitive changes in MS and NMO could therefore be different.

KEY POINTS

MS patients show much more extensive cortical thinning than NMO. Cortical thinning of insula and parahippocampus particularly distinguishes MS from NMO. Cognitive changes are correlated with cortical atrophy in MS but not in NMO.

Joint effect of mid- and late-life blood pressure on the brain: the AGES-Reykjavik study

OBJECTIVE

We hypothesized that in participants with a history of hypertension, lower late-life blood pressure (BP) will be associated with more brain pathology.

METHODS

Participants are 4,057 older men and women without dementia with midlife (mean age 50 ± 6 years) and late-life (mean age 76 ± 5 years) vascular screening, cognitive function, and brain structures on MRI ascertained as part of the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study.

RESULTS

The association of late-life BP to brain measures depended on midlife hypertension history. Higher late-life systolic and diastolic BP (DBP) was associated with an increased risk of white matter lesions and cerebral microbleeds, and this was most pronounced in participants without a history of midlife hypertension. In contrast, in participants with a history of midlife hypertension, lower late-life DBP was associated with smaller total brain and gray matter volumes. This finding was reflected back in cognitive performance; in participants with midlife hypertension, lower DBP was associated with lower memory scores.

CONCLUSION

In this large population-based cohort, late-life BP differentially affects brain pathology and cognitive performance, depending on the history of midlife hypertension. Our study suggests history of hypertension is critical to understand how late-life BP affects brain structure and function.

Evidence for both compensatory plastic and disuse atrophy-related neuroanatomical changes in the blind

The behavioural and neurofunctional consequences of blindness are becoming increasingly well established, and it has become evident that the amount of reorganization is directly linked to the behavioural adaptations observed in the blind. However investigations of potential neuroanatomical changes resulting from blindness have yielded conflicting results as to the nature of the observed changes, because apparent loss of occipital tissue is difficult to reconcile with observed functional recruitment. To address this issue we used two complementary brain measures of neuroanatomy, voxel-based morphometry and magnetization transfer imaging, with the latter providing insight into myelin concentration through the magnetization transfer ratio. Both early and late blind, as well as sighted control subjects participated in the study and were tested on a series of auditory and tactile tasks to provide behavioural data that we could relate to neuroanatomy. The behavioural findings show that the early blind outperform the sighted in four of five tasks, whereas the late blind do so for only one. Moreover, correlations between the auditory and tactile performance of early blind individuals seem to indicate that they might benefit from some general-purpose compensatory plasticity mechanisms, as opposed to modality-specific ones. Neuroanatomical findings reveal three key findings: (i) occipital regions in the early blind have higher magnetization transfer ratio and grey matter concentration than in the sighted; (ii) behavioural performance of the blind is strongly predicted by magnetization transfer ratio and grey matter concentration in different occipital regions; and (iii) lower grey matter and white matter concentration was also found in other occipital areas in the early blind compared to the sighted. We thus show a clear dissociation between anatomical changes that are direct result of sensory deprivation and consequent atrophy, and those related to compensatory reorganization and behavioural adaptations. Moreover, the magnetization transfer ratio results also suggest that one mechanism for this reorganization may be related to increased myelination of intracortical neurons, or perhaps of fibres conveying information to and from remote locations.

Stable Atlas-based Mapped Prior (STAMP) machine-learning segmentation for multicenter large-scale MRI data

Machine learning (ML)-based segmentation methods are a common technique in the medical image processing field. In spite of numerous research groups that have investigated ML-based segmentation frameworks, there remains unanswered aspects of performance variability for the choice of two key components: ML algorithm and intensity normalization. This investigation reveals that the choice of those elements plays a major part in determining segmentation accuracy and generalizability. The approach we have used in this study aims to evaluate relative benefits of the two elements within a subcortical MRI segmentation framework. Experiments were conducted to contrast eight machine-learning algorithm configurations and 11 normalization strategies for our brain MR segmentation framework. For the intensity normalization, a Stable Atlas-based Mapped Prior (STAMP) was utilized to take better account of contrast along boundaries of structures. Comparing eight machine learning algorithms on down-sampled segmentation MR data, it was obvious that a significant improvement was obtained using ensemble-based ML algorithms (i.e., random forest) or ANN algorithms. Further investigation between these two algorithms also revealed that the random forest results provided exceptionally good agreement with manual delineations by experts. Additional experiments showed that the effect of STAMP-based intensity normalization also improved the robustness of segmentation for multicenter data sets. The constructed framework obtained good multicenter reliability and was successfully applied on a large multicenter MR data set (n>3000). Less than 10% of automated segmentations were recommended for minimal expert intervention. These results demonstrate the feasibility of using the ML-based segmentation tools for processing large amount of multicenter MR images. We demonstrated dramatically different result profiles in segmentation accuracy according to the choice of ML algorithm and intensity normalization chosen.

Network inefficiencies in autism spectrum disorder at 24 months

Autism spectrum disorder (ASD) is a developmental disorder defined by behavioral symptoms that emerge during the first years of life. Associated with these symptoms are differences in the structure of a wide array of brain regions, and in the connectivity between these regions. However, the use of cohorts with large age variability and participants past the generally recognized age of onset of the defining behaviors means that many of the reported abnormalities may be a result of cascade effects of developmentally earlier deviations. This study assessed differences in connectivity in ASD at the age at which the defining behaviors first become clear. There were 113 24-month-old participants at high risk for ASD, 31 of whom were classified as ASD, and 23 typically developing 24-month-old participants at low risk for ASD. Utilizing diffusion data to obtain measures of the length and strength of connections between anatomical regions, we performed an analysis of network efficiency. Our results showed significantly decreased local and global efficiency over temporal, parietal and occipital lobes in high-risk infants classified as ASD, relative to both low- and high-risk infants not classified as ASD. The frontal lobes showed only a reduction in global efficiency in Broca's area. In addition, these same regions showed an inverse relation between efficiency and symptom severity across the high-risk infants. The results suggest delay or deficits in infants with ASD in the optimization of both local and global aspects of network structure in regions involved in processing auditory and visual stimuli, language and nonlinguistic social stimuli.

Methods and considerations for longitudinal structural brain imaging analysis across development

•

There have now been several longitudinal studies of structural brain development.

•

We discuss current methods and analysis techniques in longitudinal MRI.

•

We relate MRI measures to possible underlying physiological mechanisms.

•

We encourage more open discussion amongst researchers regarding best practices.

Magnetic resonance imaging (MRI) has allowed the unprecedented capability to measure the human brain in vivo. This technique has paved the way for longitudinal studies exploring brain changes across the entire life span. Results from these studies have given us a glimpse into the remarkably extended and multifaceted development of our brain, converging with evidence from anatomical and histological studies. Ever-evolving techniques and analytical methods provide new avenues to explore and questions to consider, requiring researchers to balance excitement with caution. This review addresses what MRI studies of structural brain development in children and adolescents typically measure and how. We focus on measurements of brain morphometry (e.g., volume, cortical thickness, surface area, folding patterns), as well as measurements derived from diffusion tensor imaging (DTI). By integrating finding from multiple longitudinal investigations, we give an update on current knowledge of structural brain development and how it relates to other aspects of biological development and possible underlying physiological mechanisms. Further, we review and discuss current strategies in image processing, analysis techniques and modeling of brain development. We hope this review will aid current and future longitudinal investigations of brain development, as well as evoke a discussion amongst researchers regarding best practices.

Limbic system mGluR5 availability in cocaine dependent subjects: a high-resolution PET [(11)C]ABP688 study

Cocaine self-administration decreases type 5 metabotropic glutamate receptor (mGluR5) tissue concentrations in laboratory rats during early abstinence. These changes are thought to influence the drug's reinforcing properties and the ability of drug-related cues to induce relapse. Here, our goal was to measure brain regional mGluR5 availability in recently abstinent cocaine dependent humans. Participants meeting DSM-IV diagnostic criteria for current cocaine dependence (n=9) were recruited from the general population. mGluR5 availability (binding potential, non-displaceable; BPND) was measured with high-resolution positron emission tomography (PET HRRT) and [(11)C]ABP688. Compared to age- and sex-matched healthy controls (n=9), cocaine dependent subjects showed significantly lower BPND values in the ventral (bilateral: -28.2%, p=0.011), associative (right: -21.4%, p=0.043), and sensorimotor striatum (bilateral: -21.7%, p=0.045), amygdala (left: -26%, p=0.046) and insula (right: -23.3%, p=0.041). Among the cocaine users, receptor availabilities were related to abstinence (range: 2 to 14days). The longer the duration of abstinence, the lower the BPND values in the sensorimotor striatum (r=-0.71, p=0.034), left amygdala (r=-0.73, p=0.026) and right insula (r=-0.67, p=0.046). Compared to healthy controls, BPND values were significantly reduced in those who tested negative for cocaine on the PET test session in the ventral (p=0.018) and sensorimotor striatum (p=0.017), left amygdala (p=0.008), and right insula (p=0.029), but not in those who tested positive. Together, these results provide evidence of time-related mGluR5 alterations in striatal and limbic regions in humans during early cocaine abstinence.

Anatomical coupling among distributed cortical regions in youth varies as a function of individual differences in vocabulary abilities

Patient lesion and functional magnetic resonance imaging (fMRI) studies have provided convincing evidence that a distributed brain network subserves word knowledge. However, little is known about the structural correlates of this network within the context of typical development and whether anatomical coupling in linguistically relevant regions of cortex varies as a function of vocabulary skill. Here we investigate the association between vocabulary and anatomical coupling in 235 typically developing youth (ages 6-19 years) using structural MRI. The study's primary aim was to evaluate whether higher vocabulary performance was associated with greater vertex-level cortical thickness covariation in distributed regions of cortex known to be associated with word knowledge. Results indicate that better vocabulary skills are associated with greater anatomical coupling in several linguistically relevant regions of cortex, including the left inferior parietal (temporal-parietal junction), inferior temporal, middle frontal, and superior frontal gyri and the right inferior frontal and precentral gyri. Furthermore, in high vocabulary scorers, stronger coupling is found among these regions. Thus, complementing patient and fMRI studies, this is the first investigation to highlight the relevance of anatomical covariance within the cortex to vocabulary skills in typically developing youth, further elucidating the distributed nature of neural systems subserving word knowledge.

A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.