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

Cerebral oxygen metabolism in patients with early Parkinson's disease

AIM

Decreased activity of the mitochondrial electron transport chain (ETC) has been implicated in the pathogenesis of Parkinson's disease (PD). This model would most likely predict a decrease in the rate of cerebral oxygen consumption (CMRO(2)). To test this hypothesis, we compared CMRO(2) and cerebral blood flow (CBF) PET scans from PD patients and healthy controls.

MATERIALS AND METHODS

Nine early-stage PD patients and 15 healthy age-matched controls underwent PET scans for quantitative mapping of CMRO(2) and CBF. Between-group differences were evaluated for absolute data and intensity-normalized values.

RESULTS

No group differences were detected in regional magnitudes of CMRO(2) or CBF. Upon normalization using the reference cluster method, significant relative CMRO(2) decreases were evident in widespread prefrontal, parieto-occipital, and lateral temporal regions. Sensory-motor and subcortical regions, brainstem, and the cerebellum were spared. A similar pattern was evident in normalized CBF data, as described previously.

CONCLUSION

While the data did not reveal substantially altered absolute CMRO(2) in brain of PD patients, employing data-driven intensity normalization revealed widespread relative CMRO(2) decreases in cerebral cortex. The detected pattern was very similar to that reported in earlier CBF and CMRglc studies of PD, and in the CBF images from the same subjects. Thus, the present results are consistent with the occurrence of parallel declines in CMRO(2), CBF, and CMRglc in spatially contiguous cortical regions in early PD, and support the hypothesis that ETC dysfunction could be a primary pathogenic mechanism in early PD.

Cortical thickness analysis and optimized voxel-based morphometry in children and adolescents with prelingually profound sensorineural hearing loss

Crossmodal neuroplastic changes following auditory deprivation in individuals with profound sensorineural hearing loss (SNHL) have been well documented in previous literature. However, previous studies have shown very little evidence of structural brain changes in individuals with prelingually profound SNHL and no studies have reported significant differences of gray matter (GM) in deaf subjects. Therefore, it is essential to employ a more specific and sensitive technique to detect subtle structural brain differences in deaf individuals. The objective of our study was to investigate neuroanatomical differences in children and adolescents with profound SNHL by cortical thickness analysis and optimized voxel-based morphometry (VBM). T1-weighted volumetric images of 16 children and adolescents with prelingually profound SNHL and 16 hearing controls were analyzed. The ANCOVA analysis revealed a statistically significant decreased average cortical thickness of the whole brain. As to vertex-based analysis, cortical thickness of the deaf subjects showed significant thinning in the left precentral gyrus, right postcentral gyrus, the left superior occipital gyrus and the left fusiform gyrus compared with the hearing subjects. VBM revealed statistically significant focal reduction of white matter (WM) volume in the left middle frontal gyrus and the right inferior occipital gyrus in deaf subjects without statistically significant differences in GM volume between the two groups. These findings demonstrated that structural changes happened not only in the WM but also in the GM of the subjects with prelingually profound SNHL, which have never been reported before in any previous literature. Our results also implicated the potential neuroplastic changes associated with crossmodal reorganization in the brain after auditory deprivation in the early deafness.

Common functional polymorphisms of DISC1 and cortical maturation in typically developing children and adolescents

Disrupted-in-schizophrenia-1 (DISC1), contains two common non-synonymous single-nucleotide polymorphisms (SNPs)--Leu607Phe and Ser704Cys--that modulate (i) facets of DISC1 molecular functioning important for cortical development, (ii) fronto-temporal cortical anatomy in adults and (iii) risk for diverse psychiatric phenotypes that often emerge during childhood and adolescence, and are associated with altered fronto-temporal cortical development. It remains unknown, however, if Leu607Phe and Ser704Cys influence cortical maturation before adulthood, and whether each SNP shows unique or overlapping effects. Therefore, we related genotype at Leu607Phe and Ser704Cys to cortical thickness (CT) in 255 typically developing individuals aged 9-22 years on whom 598 magnetic resonance imaging brain scans had been acquired longitudinally. Rate of cortical thinning varied with DISC1 genotype. Specifically, the rate of cortical thinning was attenuated in Phe-carrier compared with Leu-homozygous groups (in bilateral superior frontal and left angular gyri) and accelerated in Ser-homozygous compared with Cys-carrier groups (in left anterior cingulate and temporal cortices). Both SNPs additively predicted fixed differences in right lateral temporal CT, which were maximal between Phe-carrier/Ser-homozygous (thinnest) vs Leu-homozygous/Cys-carrier (thickest) groups. Leu607Phe and Ser704Cys genotype interacted to predict the rate of cortical thinning in right orbitofrontal, middle temporal and superior parietal cortices, wherein a significantly reduced rate of CT loss was observed in Phe-carrier/Cys-carrier participants only. Our findings argue for further examination of Leu607Phe and Ser704Cys interactions at a molecular level, and suggest that these SNPs might operate (in concert with other genetic and environmental factors) to shape risk for diverse phenotypes by impacting on the early maturation of fronto-temporal cortices.

Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex

Cortical thickness correlation across individuals has been observed. So far, it remains unclear to what extent such a correlation in thickness is a reflection of underlying fiber connection. Here we explicitly compared the patterns of cortical thickness correlation and diffusion-based fiber connection across the entire cerebral cortex, in 95 normal adults. Interregional thickness correlations were extracted by using computational neuroanatomy algorithms based on structural MRI, and diffusion connections were detected by using diffusion probabilistic tractography. Approximately 35-40% of thickness correlations showed convergent diffusion connections across the cerebral cortex. Intriguingly, the observed convergences between thickness correlation and diffusion connection are mostly focused on the positive thickness correlations, while almost all of the negative correlations (>90%) did not have a matched diffusion connection, suggesting different mechanisms behind the positive and negative thickness correlations, the latter not being mediated by a direct fiber pathway. Furthermore, graph theoretic analysis reveals that the thickness correlation network has a more randomized overall topology, whereas the nodal characteristics of cortical regions in these two networks are statistically correlated. These findings indicate that thickness correlations partly reflect underlying fiber connections but they contains exclusive information, and therefore should not be simply taken as a proxy measure for fiber connections.

Brain tissue volumes by APOE genotype and leisure activity-the AGES-Reykjavik Study

This study investigates the association of the APOE ε4 allele and leisure activity with brain tissue volumes, including white matter hyperintensities (WMH), in a population-based cohort of 4303 nondemented individuals, aged 66-96 years. APOE ε4 carriers were shown to have greater WMH and cerebrospinal fluid (CSF) volumes than noncarriers but smaller gray matter (GM) volumes. There was no significant difference in white matter (WM) and total brain parenchymal (TBP) volumes between APOE ε4 carriers and noncarriers. Tests for linear trend showed that individuals with lower leisure activity levels had greater WMH and CSF volumes, smaller TBP, WM and GM volumes than those with the highest levels of participation. The significant positive trend of the leisure activity with the brain tissue volumes was observed in the APOE ε4 carriers as well as in noncarriers after adjustment for demographic and health factors. These cross-sectional data suggest leisure activity is associated with tissue volumes in the brain irrespective of the APOE ε4 risk allele status.

A mutual information-based metric for evaluation of fMRI data-processing approaches

We propose a novel approach for evaluating the performance of activation detection in real (experimental) datasets using a new mutual information (MI)-based metric and compare its sensitivity to several existing performance metrics in both simulated and real datasets. The proposed approach is based on measuring the approximate MI between the fMRI time-series of a validation dataset and a calculated activation map (thresholded label map or continuous map) from an independent training dataset. The MI metric is used to measure the amount of information preserved during the extraction of an activation map from experimentally related fMRI time-series. The processing method that preserves maximal information between the maps and related time-series is proposed to be superior. The results on simulation datasets for multiple analysis models are consistent with the results of ROC curves, but are shown to have lower information content than for real datasets, limiting their generalizability. In real datasets for group analyses using the general linear model (GLM; FSL4 and SPM5), we show that MI values are (1) larger for groups of 15 versus 10 subjects and (2) more sensitive measures than reproducibility (for continuous maps) or Jaccard overlap metrics (for thresholded maps). We also show that (1) for an increasing fraction of nominally active voxels, both MI and false discovery rate (FDR) increase, and (2) at a fixed FDR, GLM using FSL4 tends to extract more voxels and more information than SPM5 using the default processing techniques in each package.

Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosis

We present a new automatic method for segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. The method performs tissue classification using a model of intensities of the normal appearing brain tissues. In order to estimate the model, a trimmed likelihood estimator is initialized with a hierarchical random approach in order to be robust to MS lesions and other outliers present in real images. The algorithm is first evaluated with simulated images to assess the importance of the robust estimator in presence of outliers. The method is then validated using clinical data in which MS lesions were delineated manually by several experts. Our method obtains an average Dice similarity coefficient (DSC) of 0.65, which is close to the average DSC obtained by raters (0.66).

The ZNF804A gene: characterization of a novel neural risk mechanism for the major psychoses

Schizophrenia and bipolar disorder share genetic risk, brain vulnerability, and clinical symptoms. The ZNF804A risk variant, rs1344706, confers susceptibility for both disorders. This study aimed to identify neural mechanisms common to both schizophrenia and bipolar disorder through this variant's potential effects on cortical thickness, white matter tract integrity, and cognitive function. Imaging, genetics, and cognitive measures were ascertained in 62 healthy adults aged between 18 and 59 years. High-resolution multimodal MRI/DTI imaging was used to measure cortical thickness and major frontotemporal and interhemispheric white matter tracts. The general linear model was used to examine the influence of the ZNF804A rs1344706 risk variant on cortical thickness, white matter tract integrity, and cognitive measures. Individuals homozygous for the risk variant ('A' allele) demonstrated reduced cortical gray matter thickness in the superior temporal gyrus, and in the anterior and posterior cingulate cortices compared with C-allele carriers. No effect of the risk variant on microstructural integrity of white matter tracts was found. Reduced attention control was found in risk allele homozygotes, aligning with findings in the anterior cingulate cortex. Our data provide a novel, genetically based neural risk mechanism for the major psychoses by effects of the ZNF804A risk variant on neural structures and cognitive function susceptible in both disorders. Our findings link genetic, imaging, and cognitive susceptibility relevant to both schizophrenia and bipolar disorder.

Effective treatment of chronic low back pain in humans reverses abnormal brain anatomy and function

Chronic pain is associated with reduced brain gray matter and impaired cognitive ability. In this longitudinal study, we assessed whether neuroanatomical and functional abnormalities were reversible and dependent on treatment outcomes. We acquired MRI scans from chronic low back pain (CLBP) patients before (n = 18) and 6 months after (spine surgery or facet joint injections; n = 14) treatment. In addition, we scanned 16 healthy controls, 10 of which returned 6 months after the first visit. We performed cortical thickness analysis on structural MRI scans, and subjects performed a cognitive task during the functional MRI. We compared patients and controls, as well as patients before versus after treatment. After treatment, patients had increased cortical thickness in the left dorsolateral prefrontal cortex (DLPFC), which was thinner before treatment compared with controls. Increased DLPFC thickness correlated with the reduction of both pain and physical disability. Additionally, increased thickness in primary motor cortex was associated specifically with reduced physical disability, and right anterior insula was associated specifically with reduced pain. Left DLPFC activity during an attention-demanding cognitive task was abnormal before treatment, but normalized following treatment. These data indicate that functional and structural brain abnormalities-specifically in the left DLPFC-are reversible, suggesting that treating chronic pain can restore normal brain function in humans.

Normalization of cortical gray matter deficits in nonpsychotic siblings of patients with childhood-onset schizophrenia

OBJECTIVE

Cortical gray matter (GM) abnormalities in patients with childhood-onset schizophrenia (COS) progress during adolescence ultimately localizing to prefrontal and temporal cortices by early adult age. A previous study of 52 nonpsychotic siblings of COS probands had significant prefrontal and temporal GM deficits that appeared to "normalize" by age 17 years. Here we present a replication with nonoverlapping groups of healthy full siblings and healthy controls.

METHOD

Using an automated measure and prospectively acquired anatomical brain magnetic resonance images, we mapped cortical GM thickness in nonpsychotic full siblings (n = 43, 68 scans; ages 5 through 26 years) of patients with COS, contrasting them with age-, gender-, and scan interval-matched healthy controls (n = 86, 136 scans). The false-discovery rate procedure was used to control for type I errors due to multiple comparisons.

RESULTS

As in our previous study, young nonpsychotic siblings (<17 years) showed significant GM deficits in bilateral prefrontal and left temporal cortices and, in addition, smaller deficits in the parietal and right inferior temporal cortices. These deficits in nonpsychotic siblings normalized with age with minimal abnormalities remaining by age 17.

CONCLUSIONS

Our results support previous findings showing nonpsychotic siblings of COS probands to have early GM deficits that ameliorate with time. At early ages, prefrontal and/or temporal loss may serve as a familial/trait marker for COS. Late adolescence appears to be a critical period for greatest localization of deficits in probands or normalization in nonpsychotic siblings.

Neuroanatomy of childhood disruptive behavior disorders

Our aims were to (1) examine possible neuroanatomical abnormalities associated with the Disruptive Behavior Disorders (DBDs) as a group and (2) assess neuroanatomical anomalies specific to each DBD (i.e., conduct disorder [CD] and oppositional defiant disorder). Cortical thickness analysis and voxel-based morphometry were analyzed in 47 8-year-old boys (22 DBDs with and without CD and/or ODD and 25 healthy controls) from Magnetic Resonance Imaging brain scans. DBD symptoms were assessed using the Dominic-R. In DBD subjects relative to controls, we found (1) a decreased overall mean cortical thickness; (2) thinning of the cingulate, prefrontal and insular cortices; and (3) decreased gray matter density (GMd) in the same brain regions. We also found that scores on the Dominic-R were negatively correlated with GMd in the prefrontal and precuneus/superior temporal regions. There was a subdiagnostic main effect for CD, related to thinning of the middle/medial frontal, and for ODD in the left rectal/orbitofrontal. Findings suggest that thinning and decreased GMd of the insula disorganizes prefrontal circuits, diminishing the inhibitory influence of the prefrontal cortex on anger, aggression, cruelty, and impulsivity, and increasing a person's likelihood of aggressive behavior. These findings have implications for pathophysiologic models of the DBDs, their diagnostic classification system, and for designing more effective intervention programs.

Semi-automatic segmentation of multiple mouse embryos in MR images

BACKGROUND

The motivation behind this paper is to aid the automatic phenotyping of mouse embryos, wherein multiple embryos embedded within a single tube were scanned using Magnetic Resonance Imaging (MRI).

RESULTS

Our algorithm, a modified version of the simplex deformable model of Delingette, addresses various issues with deformable models including initialization and inability to adapt to boundary concavities. In addition, it proposes a novel technique for automatic collision detection of multiple objects which are being segmented simultaneously, hence avoiding major leaks into adjacent neighbouring structures. We address the initialization problem by introducing balloon forces which expand the initial spherical models close to the true boundaries of the embryos. This results in models which are less sensitive to initial minimum of two fold after each stage of deformation. To determine collision during segmentation, our unique collision detection algorithm finds the intersection between binary masks created from the deformed models after every few iterations of the deformation and modifies the segmentation parameters accordingly hence avoiding collision.We have segmented six tubes of three dimensional MR images of multiple mouse embryos using our modified deformable model algorithm. We have then validated the results of the our semi-automatic segmentation versus manual segmentation of the same embryos. Our Validation shows that except paws and tails we have been able to segment the mouse embryos with minor error.

CONCLUSIONS

This paper describes our novel multiple object segmentation technique with collision detection using a modified deformable model algorithm. Further, it presents the results of segmenting magnetic resonance images of up to 32 mouse embryos stacked in one gel filled test tube and creating 32 individual masks.

Neurexin-1 and frontal lobe white matter: an overlapping intermediate phenotype for schizophrenia and autism spectrum disorders

Background

Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1 gene variation may be related to brain morphology to confer risk for ASD or schizophrenia is unknown.

Method/Principal Findings

53 healthy individuals between 18–59 years of age were genotyped at 11 single nucleotide polymorphisms of the NRXN1 gene. All subjects received structural MRI scans, which were processed to determine cortical gray and white matter lobar volumes, and volumes of striatal and thalamic structures. Each subject's sensorimotor function was also assessed. The general linear model was used to calculate the influence of genetic variation on neural and cognitive phenotypes. Finally, in silico analysis was conducted to assess potential functional relevance of any polymorphisms associated with brain measures. A polymorphism located in the 3′ untranslated region of NRXN1 significantly influenced white matter volumes in whole brain and frontal lobes after correcting for total brain volume, age and multiple comparisons. Follow-up in silico analysis revealed that this SNP is a putative microRNA binding site that may be of functional significance in regulating NRXN1 expression. This variant also influenced sensorimotor performance, a neurocognitive function impaired in both ASD and schizophrenia.

Conclusions

Our findings demonstrate that the NRXN1 gene, a vulnerability gene for SCZ and ASD, influences brain structure and cognitive function susceptible in both disorders. In conjunction with our in silico results, our findings provide evidence for a neural and cognitive susceptibility mechanism by which the NRXN1 gene confers risk for both schizophrenia and ASD.

Cortical thickness is associated with poor insight in first-episode psychosis

Through conceptualizing poor insight in psychotic disorders as a form of anosognosia (neurological deficit), frontal lobe dysfunction is often ascribed a vital role in its pathogenesis. Whether non-frontal brain regions are important for insight remains to be investigated. We used a multi-method approach to examine the neural morphometry of all cortical regions for insight in first-episode psychosis. Insight was rated in 79 people with a first-episode psychosis with the awareness of illness and awareness of treatment need and efficacy items of the Scale for assessment of Unawareness of Mental Disorder. Participants were assessed with magnetic resonance imaging. Cortical thickness analysis and voxel-based morphometry were utilized to identify the possible neuroanatomical basis of insight. Cortical thickness technique revealed that poorer awareness of illness was associated with regional thinning in left middle frontal and inferior temporal gyri. Poorer awareness of treatment need and efficacy was associated with cortical thinning in left medial frontal gyrus, precuneus and temporal gyri. No significant associations emerged between any insight measure and gray matter density using voxel-based morphometry. The results confirm predictions derived from the anosognosia/neuropsychology account and assert that regional thickness in frontal cortex is associated with awareness of illness in the early phase of psychosis. The fact that prominent thickness reductions emerged in non-frontal regions of the brain in parietal and temporal cortices for both awareness of illness and awareness of treatment need and efficacy suggests that the neural signature of insight involves a network of brain structures, and not only the frontal lobes as previously suggested.

Segmentation of multiple sclerosis lesions in MR images: a review

INTRODUCTION

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease.

METHODS

For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past.

RESULTS

This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques.

CONCLUSIONS

Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels.

Segmentation of multiple sclerosis lesions in MR images: a review

INTRODUCTION

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease.

METHODS

For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past.

RESULTS

This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques.

CONCLUSIONS

Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels.

Catechol-o-methyl transferase (COMT) val158met polymorphism and adolescent cortical development in patients with childhood-onset schizophrenia, their non-psychotic siblings, and healthy controls

Non-psychotic individuals at increased risk for schizophrenia show alterations in fronto-striatal dopamine signaling and cortical gray matter maturation reminiscent of those seen in schizophrenia. It remains unclear however if variations in dopamine signaling influence rates of structural cortical maturation in typically developing individuals, and whether such influences are disrupted in patients with schizophrenia and their non-psychotic siblings. We sought to address these issues by relating a functional Val→Met polymorphism within the gene encoding catechol-o-methyltransferase (COMT)-a key enzymatic regulator of cortical dopamine levels-to longitudinal structural neuroimaging measures of cortical gray matter thickness. We included a total of 792 magnetic resonance imaging brain scans, acquired between ages 9 and 22 years from patients with childhood-onset schizophrenia (COS), their non-psychotic full siblings, and matched healthy controls. Whereas greater Val allele dose (which confers enhanced dopamine catabolism and is proposed to aggravate cortical deficits in schizophrenia) accelerated adolescent cortical thinning in both schizophrenia probands and their siblings, it attenuated cortical thinning in healthy controls. This similarity between COS patients and their siblings was accompanied by differences between the two groups in the timing and spatial distribution of disrupted COMT influences on cortical maturation. Consequently, whereas greater Val "dose" conferred persistent dorsolateral prefrontal cortical deficits amongst affected probands by adulthood, cortical thickness differences associated with varying Val dose in non-psychotic siblings resolved over the age-range studied. These findings suggest that cortical abnormalities in pedigrees affected by schizophrenia may be contributed to by a disruption of dopaminergic infleunces on cortical maturation.

Genetic and environmental influences on structural variability of the brain in pediatric twin: deformation based morphometry

Twin studies are one of the most powerful study designs for estimating the relative contribution of genetic and environmental influences on phenotypic variation inhuman brain morphology. In this study, we applied deformation based morphometry, a technique that provides a voxel-wise index of local tissue growth or atrophy relative to a template brain, combined with univariate ACE model, to investigate the genetic and environmental effects on the human brain structural variations in a cohort of homogeneously aged healthy pediatric twins. In addition, anatomical regions of interest (ROIs) were defined in order to explore global and regional genetic effects. ROI results showed that the influence of genetic factors on cerebrum (h(2)=0.70), total gray matter (0.67), and total white matter (0.73) volumes were significant. In particular, structural variability of left-side lobar volumes showed a significant heritability. Several subcortical structures such as putamen (h(ROI)(2)=0.79/0.77(L/R),h(MAX)(2)=0.82/0.79) and globus pallidus (0.81/0.76, 0.88/0.82) were also significantly heritable in both voxel-wise and ROI-based results. In the voxel-wise results, lateral parts of right cerebellum (c(2)=0.68) and the posterior portion of the corpus callosum (0.63) were rather environmentally determined, but it failed to reach statistical significance. Pediatric twin studies are important because they can discriminate several influences on developmental brain trajectories and identify relationships between gene and behavior. Several brain structures showed significant genetic effects and might therefore serve as biological markers for inherited traits, or as targets for genetic linkage and association studies.

Age-related alterations in the modular organization of structural cortical network by using cortical thickness from MRI

Normal aging is accompanied by various cognitive functional declines. Recent studies have revealed disruptions in the coordination of large-scale functional brain networks such as the default mode network in advanced aging. However, organizational alterations of the structural brain network at the system level in aging are still poorly understood. Here, using cortical thickness, we investigated the modular organization of the cortical structural networks in 102 young and 97 normal aging adults. Brain networks for both cohorts displayed a modular organization overlapping with functional domains such as executive and auditory/language processing. However, compared with the modular organization of young adults, the aging group demonstrated a significantly reduced modularity that might be indicative of reduced functional segregation in the aging brain. More importantly, the aging brain network exhibited reduced intra-/inter-module connectivity in modules corresponding to the executive function and the default mode network of young adults, which might be associated with the decline of cognitive functions in aging. Finally, we observed age-associated alterations in the regional characterization in terms of their intra/inter-module connectivity. Our results indicate that aging is associated with an altered modular organization in the structural brain networks and provide new evidence for disrupted integrity in the large-scale brain networks that underlie cognition.

Age differences in speed of processing are partially mediated by differences in axonal integrity

Advanced age is associated with declines in brain structure and in cognitive performance, but it is unclear which aspects of brain aging mediate cognitive declines. We inquired if individual differences in white matter integrity contribute to age differences in two cognitive domains with established vulnerability to aging: executive functioning and speed of processing. The participants were healthy volunteers aged 50-81, some of whom had elevated blood pressure, a known vascular risk factor. Using latent variable analyses, we examined whether age differences in regional white matter integrity mediated age-related differences in executive functions and speed of processing. Although diffusion-related latent variables showed stronger age differences than white matter volumes and white matter hyperintensity volumes, only one of them was significantly associated with cognitive performance. Smaller linear anisotropy partially mediated age-related reduction in speed of processing. The effect was significant in posterior (temporal-parietal-occipital) but not anterior (frontal) region, and appeared stronger for cognitive rather than reaction time measures of processing speed. The presence of hypertensive participants did not affect the results. We conclude that in healthy adults, deterioration of axonal integrity and ensuing breech of connectivity may underpin age-related slowing of information processing.

Cannabis use and progressive cortical thickness loss in areas rich in CB1 receptors during the first five years of schizophrenia

Cerebral grey matter volume reductions are progressive in schizophrenia, with larger grey matter volume decreases associated with cannabis use. It is unknown whether this grey matter loss is globally distributed over the entire brain or more pronounced in specific cortical brain regions. Fifty-one patients with recent-onset schizophrenia and 31 matched healthy subjects were included. For all subjects, magnetic resonance imaging scans were obtained at inclusion and at 5-year follow-up. Nineteen patients (ab-)used cannabis but no other illicit drugs; 32 patients and the healthy comparison subjects did not use any drugs during the 5-year follow-up. At follow-up, clinical outcome was measured. To evaluate the local differences in cortical thickness change over five years between the two groups regression analysis was carried out over the cortical surface. At inclusion cortical thickness did not differ between patients and controls and between cannabis-using and non-using patients. Over the follow-up period we found excessive thinning of the right supplementary motor cortex, inferior frontal cortex, superior temporal gyrus, angular gyrus, occipital and parietal lobe in patients relative to controls after controlling for cannabis use. Patients who used cannabis showed additional thinning in the left dorsolateral prefrontal cortex (DLPFC), left anterior cingulate cortex (ACC) and left occipital lobe as compared to those patients that did not use cannabis during the scan interval. First-episode schizophrenia patients who use cannabis show a more pronounced cortical thinning than non-using patients in areas known for their high density of CB1 receptors, such as the ACC and the DLPFC.

A generative model for image segmentation based on label fusion

We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inference algorithms rely on pairwise registrations between the test image and individual training images. The training labels are then transferred to the test image and fused to compute the final segmentation of the test subject. Such label fusion methods have been shown to yield accurate segmentation, since the use of multiple registrations captures greater inter-subject anatomical variability and improves robustness against occasional registration failures. To the best of our knowledge, this manuscript presents the first comprehensive probabilistic framework that rigorously motivates label fusion as a segmentation approach. The proposed framework allows us to compare different label fusion algorithms theoretically and practically. In particular, recent label fusion or multiatlas segmentation algorithms are interpreted as special cases of our framework. We conduct two sets of experiments to validate the proposed methods. In the first set of experiments, we use 39 brain MRI scans-with manually segmented white matter, cerebral cortex, ventricles and subcortical structures-to compare different label fusion algorithms and the widely-used FreeSurfer whole-brain segmentation tool. Our results indicate that the proposed framework yields more accurate segmentation than FreeSurfer and previous label fusion algorithms. In a second experiment, we use brain MRI scans of 282 subjects to demonstrate that the proposed segmentation tool is sufficiently sensitive to robustly detect hippocampal volume changes in a study of aging and Alzheimer's Disease.

Longitudinally mapping the influence of sex and androgen signaling on the dynamics of human cortical maturation in adolescence

Humans have systematic sex differences in brain-related behavior, cognition, and pattern of mental illness risk. Many of these differences emerge during adolescence, a developmental period of intense neurostructural and endocrine change. Here, by creating "movies" of sexually dimorphic brain development using longitudinal in vivo structural neuroimaging, we show regionally specific sex differences in development of the cerebral cortex during adolescence. Within cortical subsystems known to underpin domains of cognitive behavioral sex difference, structural change is faster in the sex that tends to perform less well within the domain in question. By stratifying participants through molecular analysis of the androgen receptor gene, we show that possession of an allele conferring more efficient functioning of this sex steroid receptor is associated with "masculinization" of adolescent cortical maturation. Our findings extend models first established in rodents, and suggest that in humans too, sex and sex steroids shape brain development in a spatiotemporally specific manner, within neural systems known to underpin sexually dimorphic behaviors.

Multivariate analysis of MRI data for Alzheimer's disease, mild cognitive impairment and healthy controls

We have used multivariate data analysis, more specifically orthogonal partial least squares to latent structures (OPLS) analysis, to discriminate between Alzheimer's disease (AD), mild cognitive impairment (MCI) and elderly control subjects combining both regional and global magnetic resonance imaging (MRI) volumetric measures. In this study, 117 AD patients, 122 MCI patients and 112 control subjects (from the AddNeuroMed study) were included. High-resolution sagittal 3D MP-RAGE datasets were acquired from each subject. Automated regional segmentation and manual outlining of the hippocampus were performed for each image. Altogether this yielded volumes of 24 different anatomically defined structures which were used for OPLS analysis. 17 randomly selected AD patients, 12 randomly selected control subjects and the 22 MCI subjects who converted to AD at 1-year follow up were excluded from the initial OPLS analysis to provide a small external test set for model validation. Comparing AD with controls we found a sensitivity of 87% and a specificity of 90% using hippocampal measures alone. Combining both global and regional measures resulted in a sensitivity of 90% and a specificity of 94%. This increase in sensitivity and specificity resulted in an increase of the positive likelihood ratio from 9 to 15. From the external test set, the model predicted 82% of the AD patients and 83% of the control subjects correctly. Finally, 73% of the MCI subjects which converted to AD at 1 year follow-up were shown to resemble AD patients more closely than controls. This method shows potential for distinguishing between different patient groups. Combining the different MRI measures together resulted in a significantly better classification than using them separately. OPLS also shows potential for predicting conversion from MCI to AD.

Regional gray matter density changes in brains of patients with irritable bowel syndrome

BACKGROUND & AIMS

Several studies have examined structural brain changes associated with chronic pain syndromes, including irritable bowel syndrome (IBS), but study sample sizes have been small and heterogeneous.

METHODS

We used magnetic resonance imaging-based techniques, voxel-based morphometry, and cortical thickness analysis to examine brain anatomical differences in a relatively large, tightly screened sample of IBS patients (n = 55); we compared data with that from healthy persons (controls; n = 48).

RESULTS

IBS was associated with decreased gray matter density (GMD) in widespread areas of the brain, including medial prefrontal and ventrolateral prefrontal cortex, posterior parietal cortex, ventral striatum, and thalamus. Compared with controls, we observed increased GMD in patients with IBS in the pregenual anterior cingulate cortex and the orbitofrontal cortex, as well as trends in the posterior insula/secondary somatosensory cortex, (para)hippocampus, and left dorsolateral prefrontal cortex. In accounting for anxiety and depression, we found that several of the regions involved in affective processing no longer differed between patients with IBS and controls, whereas the differences in prefrontal and posterior parietal cortices remained. The areas of decreased GMD associated with IBS were largely consistent across clinical subgroups, based on predominant bowel habit and pain predominance of symptoms. No overall or regional differences were observed in cortical thickness between patients with IBS and controls.

CONCLUSIONS

Changes in density of gray matter among regions involved in cognitive/evaluative functions are specifically observed in patients with IBS, whereas changes in other areas of the brain can be explained by levels of anxiety and depression.

Cortical structure predicts success in performing musical transformation judgments

Recognizing melodies by their interval structure, or "relative pitch," is a fundamental aspect of musical perception. By using relative pitch, we are able to recognize tunes regardless of the key in which they are played. We sought to determine the cortical areas important for relative pitch processing using two morphometric techniques. Cortical differences have been reported in musicians within right auditory cortex (AC), a region considered important for pitch-based processing, and we have previously reported a functional correlation between relative pitch processing in the anterior intraparietal sulcus (IPS). We addressed the hypothesis that regional variation of cortical structure within AC and IPS is related to relative pitch ability using two anatomical techniques, cortical thickness (CT) analysis and voxel-based morphometry (VBM) of magnetic resonance imaging data. Persons with variable amounts of formal musical training were tested on a melody transposition task, as well as two musical control tasks and a speech control task. We found that gray matter concentration and cortical thickness in right Heschl's sulcus and bilateral IPS both predicted relative pitch task performance and correlated to a lesser extent with performance on the two musical control tasks. After factoring out variance explained by musical training, only relative pitch performance was predicted by cortical structure in these regions. These results directly demonstrate the functional relevance of previously reported anatomical differences in the auditory cortex of musicians. The findings in the IPS provide further support for the existence of a multimodal network for systematic transformation of stimulus information in this region.

Neuroanatomical differences in brain areas implicated in perceptual and other core features of autism revealed by cortical thickness analysis and voxel-based morphometry

Autism spectrum disorder is a complex neurodevelopmental variant thought to affect 1 in 166 [Fombonne (2003): J Autism Dev Disord 33:365-382]. Individuals with autism demonstrate atypical social interaction, communication, and repetitive behaviors, but can also present enhanced abilities, particularly in auditory and visual perception and nonverbal reasoning. Structural brain differences have been reported in autism, in terms of increased total brain volume (particularly in young children with autism), and regional gray/white matter differences in both adults and children with autism, but the reports are inconsistent [Amaral et al. (2008): Trends Neurosci 31:137-145]. These inconsistencies may be due to differences in diagnostic/inclusion criteria, and age and Intelligence Quotient of participants. Here, for the first time, we used two complementary magnetic resonance imaging techniques, cortical thickness analyses, and voxel-based morphometry (VBM), to investigate the neuroanatomical differences between a homogenous group of young adults with autism of average intelligence but delayed or atypical language development (often referred to as "high-functioning autism"), relative to a closely matched group of typically developing controls. The cortical thickness and VBM techniques both revealed regional structural brain differences (mostly in terms of gray matter increases) in brain areas implicated in social cognition, communication, and repetitive behaviors, and thus in each of the core atypical features of autism. Gray matter increases were also found in auditory and visual primary and associative perceptual areas. We interpret these results as the first structural brain correlates of atypical auditory and visual perception in autism, in support of the enhanced perceptual functioning model [Mottron et al. (2006): J Autism Dev Disord 36:27-43].

Decreased cerebral cortical serotonin transporter binding in ecstasy users: a positron emission tomography/[(11)C]DASB and structural brain imaging study

Animal data indicate that the recreational drug ecstasy (3,4-methylenedioxymethamphetamine) can damage brain serotonin neurons. However, human neuroimaging measurements of serotonin transporter binding, a serotonin neuron marker, remain contradictory, especially regarding brain areas affected; and the possibility that structural brain differences might account for serotonin transporter binding changes has not been explored. We measured brain serotonin transporter binding using [(11)C] N,N-dimethyl-2-(2-amino-4-cyanophenylthio) benzylamine in 50 control subjects and in 49 chronic (mean 4 years) ecstasy users (typically one to two tablets bi-monthly) withdrawn from the drug (mean 45 days). A magnetic resonance image for positron emission tomography image co-registration and structural analyses was acquired. Hair toxicology confirmed group allocation but also indicated use of other psychoactive drugs in most users. Serotonin transporter binding in ecstasy users was significantly decreased throughout all cerebral cortices (range -19 to -46%) and hippocampus (-21%) and related to the extent of drug use (years, maximum dose), but was normal in basal ganglia and midbrain. Substantial overlap was observed between control and user values except for insular cortex, in which 51% of ecstasy user values fell below the lower limit of the control range. Voxel-based analyses confirmed a caudorostral gradient of cortical serotonin transporter binding loss with occipital cortex most severely affected. Magnetic resonance image measurement revealed no overall regional volume differences between groups; however, a slight left-hemispheric biased cortical thinning was detected in methamphetamine-using ecstasy users. The serotonin transporter binding loss was not related to structural changes or partial volume effect, use of other stimulant drugs, blood testosterone or oestradiol levels, major serotonin transporter gene promoter polymorphisms, gender, psychiatric status, or self-reported hyperthermia or tolerance. The ecstasy group, although 'grossly behaviourally normal', reported subnormal mood and demonstrated generally modest deficits on some tests of attention, executive function and memory, with the latter associated with serotonin transporter decrease. Our findings suggest that the 'typical'/low dose (one to two tablets/session) chronic ecstasy-polydrug user might display a highly selective mild to marked loss of serotonin transporter in cerebral cortex/hippocampus in the range of that observed in Parkinson's disease, which is not gender-specific or completely accounted for by structural brain changes, recent use of other drugs (as assessed by hair analyses) or other potential confounds that we could address. The striking sparing of serotonin transporter-rich striatum (although possibly affected in 'heavier' users) suggests that serotonergic neurons innervating cerebral cortex are more susceptible, for unknown reasons, to ecstasy than those innervating subcortical regions and that behavioural problems in some ecstasy users during abstinence might be related to serotonin transporter changes limited to cortical regions.

Coronary artery calcium, brain function and structure: the AGES-Reykjavik Study

BACKGROUND AND PURPOSE

Several cardiovascular risk factors are associated with cognitive disorders in older persons. Little is known about the association of the burden of coronary atherosclerosis with brain structure and function.

METHODS

This is a cross-sectional analysis of data from the Age, Gene, Environment Susceptibility (AGES)-Reykjavik Study cohort of men and women born 1907 to 1935. Coronary artery calcification (CAC), a marker of atherosclerotic burden, was measured with CT. Memory, speed of processing, and executive function composites were calculated from a cognitive test battery. Dementia was assessed in a multistep procedure and diagnosed according to international guidelines. Quantitative data on total intracranial and tissue volumes (total, gray matter volume, white matter volume, and white matter lesion volume), cerebral infarcts, and cerebral microbleeds were obtained with brain MRI. The association of CAC with dementia (n=165 cases) and cognitive function in nondemented subjects (n=4085), and separately with MRI outcomes, was examined in multivariate models adjusting for demographic and vascular risk factors. Analyses tested whether brain structure mediated the associations of CAC to cognitive function.

RESULTS

Subjects with higher CAC were more likely to have dementia and lower cognitive scores, more likely to have lower white matter volume, gray matter volume, and total brain tissue, and to have more cerebral infarcts, cerebral microbleeds, and white matter lesions. The relations of cognitive performance and dementia to CAC were significantly attenuated when the models were adjusted for brain lesions and volumes.

CONCLUSIONS

In a population-based sample, increasing atherosclerotic load assessed by CAC is associated with poorer cognitive performance and dementia, and these relations are mediated by evidence of brain pathology.

A time-saving and facilitating approach for segmentation of anatomically defined cortical regions: MRI volumetry

In this study, we present an accurate, reliable, robust, and time-efficient technique for a semi-automatic segmentation of neuroanatomically defined cortical structures in Magnetic Resonance Imaging (MRI) scans. It involves manual drawing of the border of a region of interest (ROI), supported by three-dimensional (3D) visualization techniques (rendering), and a subsequent automatic tracing of the gray matter voxels inside the ROI by means of an automatic tissue classifier. The approach has been evaluated on a set of MRI scans of 75 participants selected from the Maastricht Aging Study (MAAS) and applied to cortical brain structures for both the left and right hemispheres, viz., the inferior prefrontal cortex (PFC); the orbital PFC; the dorsolateral PFC; the anterior cingulate cortex; and the posterior cingulate cortex. The use of a 3D surface-rendered brain can be rotated in any direction was invaluable in identifying anatomical landmarks on the basis of gyral and sulcal topography. This resulted in a high accuracy (anatomical correctness) and reliability: the intra-rater intra-class correlation coefficient (ICC) was between 0.96 and 0.99. Furthermore, the obtained time savings were substantial, i.e., up to a factor of 7.5 compared with fully manual segmentations.

Patterns of cortical degeneration in an elderly cohort with cerebral small vessel disease

Emerging noninvasive neuroimaging techniques allow for the morphometric analysis of patterns of gray and white matter degeneration in vivo, which may help explain and predict the occurrence of cognitive impairment and Alzheimer's disease. A single center prospective follow-up study (Radboud University Nijmegen Diffusion tensor and Magnetic resonance imaging Cohort study (RUN DMC)) was performed involving 503 nondemented elderly individuals (50-85 years) with a history of symptomatic cerebral small vessel disease (SVD). Age was associated with a global reduction in cortical thickness, and this relationship was strongest for ventrolateral prefrontal cortex, auditory cortex, Wernicke's area, superior temporal lobe, and primary visual cortex. Right and left hemispheres differed in the thickness of language-related areas. White matter (WM) lesions were generally negatively correlated with cortical thickness, primarily in individuals over the age of 60, with the notable exception of Brodmann areas 4 and 5, which were positively correlated in age groups 50-60 and 60-70, respectively. The observed pattern of age-related decline may explain problems in memory and executive functions, which are already well documented in individuals with SVD. The additional gray matter loss affecting visual and auditory cortex, and specifically the head region of primary motor cortex, may indicate morphological correlates of impaired sensory and motor functions. The paradoxical positive relationship between WM lesion volume and cortical thickness in some areas may reflect early compensatory hypertrophy. This study raises a further interest in the mechanisms underlying cerebral gray and white matter degeneration in association with SVD, which will require further investigation with diffusion weighted and longitudinal MR studies.

Anatomical phenotyping in a mouse model of fragile X syndrome with magnetic resonance imaging

Fragile X Syndrome (FXS) is the most common single gene cause of inherited mental impairment, and cognitive deficits can range from simple learning disabilities to mental retardation. Human FXS is caused by a loss of the Fragile X Mental Retardation Protein (FMRP). The fragile X knockout (FX KO) mouse also shows a loss of FMRP, as well as many of the physical and behavioural characteristics of human FXS. This work aims to characterize the anatomical changes between the FX KO and a corresponding wild type mouse. Significant volume decreases were found in two regions within the deep cerebellar nuclei, namely the nucleus interpositus and the fastigial nucleus, which may be caused by a loss of neurons as indicated by histological analysis. Well-known links between these nuclei and previously established behavioural and physical characteristics of FXS are discussed. The loss of FMRP has a significant effect on these two nuclei, and future studies of FXS should evaluate the biochemical, physiological, and behavioral consequences of alterations in these key nuclei.

Effects of sex chromosome aneuploidies on brain development: evidence from neuroimaging studies

Variation in the number of sex chromosomes is a relatively common genetic condition, affecting as many as 1/400 individuals. The sex chromosome aneuploidies (SCAs) are associated with characteristic behavioral and cognitive phenotypes, although the degree to which specific individuals are affected can fall within a wide range. Understanding the effects of different dosages of sex chromosome genes on brain development may help to understand the basis for functional differences in affected individuals. It may also be informative regarding how sex chromosomes contribute to typical sexual differentiation. Studies of 47,XXY males make up the bulk of the current literature of neuroimaging studies in individuals with supernumerary sex chromosomes, with a few small studies or case reports of the other SCAs. Findings in 47,XXY males typically include decreased gray and white matter volumes, with most pronounced effects in the frontal and temporal lobes. Functional studies have shown evidence of decreased lateralization. Although the hypogonadism typically found in 47,XXY males may contribute to the decreased brain volume, the observation that 47,XXX females also show decreased brain volume in the presence of normal pubertal maturation suggests a possible direct dosage effect of X chromosome genes. Additional X chromosomes, such as in 49,XXXXY males, are associated with more markedly decreased brain volume and increased incidence of white matter hyperintensities. The limited data regarding effects of having two Y chromosomes (47,XYY) do not find significant differences in brain volume, although there are some reports of increased head size.

Multi-level bootstrap analysis of stable clusters in resting-state fMRI

A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such resting-state networks (RSNs), which was implemented with k-means clustering. The core of the method consists in bootstrapping the available datasets to replicate the clustering process a large number of times and quantify the stable features across all replications. This bootstrap analysis of stable clusters (BASC) has several benefits: (1) it can be implemented in a multi-level fashion to investigate stable RSNs at the level of individual subjects and at the level of a group; (2) it provides a principled measure of RSN stability; and (3) the maximization of the stability measure can be used as a natural criterion to select the number of RSNs. A simulation study validated the good performance of the multi-level BASC on purely synthetic data. Stable networks were also derived from a real resting-state study for 43 subjects. At the group level, seven RSNs were identified which exhibited a good agreement with the previous findings from the literature. The comparison between the individual and group-level stability maps demonstrated the capacity of BASC to establish successful correspondences between these two levels of analysis and at the same time retain some interesting subject-specific characteristics, e.g. the specific involvement of subcortical regions in the visual and fronto-parietal networks for some subjects.

Cortical gray matter in attention-deficit/hyperactivity disorder: a structural magnetic resonance imaging study

OBJECTIVE

Previous studies have shown smaller brain volume and less gray matter in children with attention-deficit/hyperactivity disorder (ADHD). Relatively few morphological studies have examined structures thought to subserve inhibitory control, one of the diagnostic features of ADHD. We examined one such region, the pars opercularis, predicting a thinner cortex of the inferior frontal gyrus (IFG) in children with ADHD.

METHOD

Structural images were obtained from 49 children (24 control; 25 ADHD combined subtype) aged 9 though 15 years. Images were processed using a volumetric pipeline to provide a fully automated estimate of regional volumes of gray and white matter. A further analysis using FreeSurfer provided measures of cortical thickness for each lobe, and for 13 regions in the frontal lobe.

RESULTS

Relative to controls, children with ADHD had smaller whole brain volume and lower gray matter, but not white matter, volumes in all lobes. An analysis of frontal regions showed a significant interaction of group by region. Planned contrasts showed bilateral thinner cortex in the pars opercularis in children with ADHD.

CONCLUSIONS

Children with ADHD showed both diffuse and regional gray matter abnormalities. Consistent with its putative role in response inhibition, the cortex of the pars opercularis was thinner in children with ADHD who, as expected, had significantly poorer inhibitory performance on a Go/No-go task. These differences held for both hemispheres raising the possibility that a developmental abnormality of IFG might drive development of inhibition difficulties.

A twin study of intracerebral volumetric relationships

Using high resolution magnetic resonance imaging data, we examined the interrelationships between eight cerebral lobar volumetric measures via both exploratory and confirmatory factor analyses in a large sample (N = 484) of pediatric twins and singletons. These analyses suggest the presence of strong genetic correlations between cerebral structures, particularly between regions of like tissue type or in spatial proximity. Structural modeling estimated that most of the variance in all structures is associated with highly correlated lobar latent factors, with differences in genetic covariance and heritability driven by a common genetic factor that influenced gray and white matter differently. Reanalysis including total brain volume as a covariate dramatically reduced the total residual variance and disproportionately influenced the additive genetic variance in all regions of interest.

Cortical anatomy in human X monosomy

Turner syndrome (TS) is a model for X chromosome influences on neurodevelopment because it is most commonly caused by absence of one X chromosome and associated with altered brain structure and function. However, all prior in vivo magnetic resonance imaging studies of the brain in TS have either used manual approaches or voxel-based morphometry (VBM) to measure cortical volume (CV). These methods, unlike surface-based morphometry (SBM), cannot measure the two neurobiologically distinct determinants of CV- cortical thickness (CT) and surface area (SA) - which have differing genetic determinants and may be independently altered. Therefore, in 24 adults with X monosomy and 19 healthy female controls, we used SBM to compare (i) lobar CV, CT and SA; (ii) an index of hemispheric gyrification; (iii) CT throughout the cortical sheet; and (iv) CT correlation between cortical regions. Compared to controls, females with TS had (i) significantly increased CT and decreased SA in parietal and occipital lobes (resulting in no significant difference in lobar CV); (ii) reduced hemispheric gyrification bilaterally; (iii) foci of significantly increased CT involving inferior temporal, lateral occipital, intraparietal sulcus (IPS), cingulate and orbitofrontal cortices; and (iv) significantly reduced CT correlation between the left IPS and cortical regions including supramarginal and lateral occipital gyri. Our findings suggest that females with TS have complex, sometimes "opposing", abnormalities in SA/gyrification (decreased) and CT (increased), which can result in no overall detectable differences in CV. Thus, haploinsufficiency of X chromosome genes, may differentially impact the distinct mechanisms shaping SA (e.g. cortical folding) and CT (e.g. dendritic arborization/pruning). CT disruptions are maximal within and between cortical regions previously implicated in the TS cognitive phenotype.

Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load

White matter tracts, which play a crucial role in the coordination of information flow between different regions of grey matter, are particularly vulnerable to multiple sclerosis. Many studies have shown that the white matter lesions in multiple sclerosis are associated with focal abnormalities of grey matter, but little is known about the alterations in the coordinated patterns of cortical morphology among regions in the disease. Here, we used cortical thickness measurements from structural magnetic resonance imaging to investigate the relationship between the white matter lesion load and the topological efficiency of structural cortical networks in multiple sclerosis. Network efficiency was defined using a 'small-world' network model that quantifies the effectiveness of information transfer within brain networks. In this study, we first classified patients (n = 330) into six subgroups according to their total white matter lesion loads, and identified structural brain networks for each multiple sclerosis group by thresholding the corresponding inter-regional cortical thickness correlation matrix, followed by a network efficiency analysis with graph theoretical approaches. The structural cortical networks in multiple sclerosis demonstrated efficient small-world architecture regardless of the lesion load, an organization that maximizes the information processing at a relatively low wiring cost. However, we found that the overall small-world network efficiency in multiple sclerosis was significantly disrupted in a manner proportional to the extent of total white matter lesions. Moreover, regional efficiency was also significantly decreased in specific brain regions, including the insula and precentral gyrus as well as regions of prefrontal and temporal association cortices. Finally, we showed that the lesions also altered many cortical thickness correlations in the frontal, temporal and parietal lobes. Our results suggest that the white matter lesions in multiple sclerosis might be associated with aberrant neuronal connectivity among widely distributed brain regions, and provide structural (morphological) evidence for the notion of multiple sclerosis as a disconnection syndrome.

A bivariate twin study of regional brain volumes and verbal and nonverbal intellectual skills during childhood and adolescence

Twin studies indicate that both intelligence and brain structure are moderately to highly heritable. Recent bivariate studies of adult twins also suggest that intelligence and brain morphometry are influenced by shared genetic factors. The current study examines shared genetic and environmental factors between brain morphometry and intelligence in a sample of children and adolescents (twins, twin siblings, and singletons; n = 649, ages 4-19). To extend previous studies, brain morphometric data were parsed into subregions (lobar gray/white matter volumes, caudate nucleus, lateral ventricles) and intelligence into verbal and nonverbal skills (Wechsler Vocabulary and Block Design subtests). Phenotypic relationships between brain volumes and intelligence were small. Verbal skills shared unique environmental effects with gray matter volumes while nonverbal skills shared genetic effects with both global and regional gray and white matter. These results suggest that distinct mechanisms contribute to the small phenotypic relationships between brain volumes and verbal versus nonverbal intelligence.

Surface area and cortical thickness descriptors reveal different attributes of the structural human brain networks

Recently, a related morphometry-based connection concept has been introduced using local mean cortical thickness and volume to study the underlying complex architecture of the brain networks. In this article, the surface area is employed as a morphometric descriptor to study the concurrent changes between brain structures and to build binarized connectivity graphs. The statistical similarity in surface area between pair of regions was measured by computing the partial correlation coefficient across 186 normal subjects of the Cuban Human Brain Mapping Project. We demonstrated that connectivity matrices obtained follow a small-world behavior for two different parcellations of the brain gray matter. The properties of the connectivity matrices were compared to the matrices obtained using the mean cortical thickness for the same cortical parcellations. The topology of the cortical thickness and surface area networks were statistically different, demonstrating that both capture distinct properties of the interaction or different aspects of the same interaction (mechanical, anatomical, chemical, etc.) between brain structures. This finding could be explained by the fact that each descriptor is driven by distinct cellular mechanisms as result of a distinct genetic origin. To our knowledge, this is the first time that surface area is used to study the morphological connectivity of brain networks.

Lateralized genetic and environmental influences on human brain morphology of 8-year-old twins

It has been increasing rapidly interest in understanding genetic effects on brain structure and function in recent years. In this study, we examined the genetic and environmental influences on the variation in cortical thickness and specific tissue volumes in a large cohort of 8-year-old healthy twins. The present study can provide a better estimation of the genetic and environmental effects by virtue of the homogeneously aged pediatric twin pairs with a similar growing environment. We found that common environmental factors contributed significantly to the variations of the right lateral ventricle (36%) and corpus callosum (36%) volumes while genetic factors accounted for most of the phenotypic variance in other brain tissue volumes. In the case of cortical thickness, several regions in the left hemisphere showed statistically significant additive genetic factors, including the middle and inferior frontal gyri, lateral fronto-orbital and occipitotemporal gyri, pars opercularis, planum temporale, precentral and parahippocampal gyri and the medial region of the primary somatosensory cortex. Relatively high common environmental influence (>50%) was observed in the right anterior cingulate cortex and insula. Our findings indicate that the genetic and common environmental influences on individual human brain structural differences are lateralized, with the language-dominant left cerebral cortex under stronger genetic control than the right.

Computer input devices: neutral party or source of significant error in manual lesion segmentation?

Lesion segmentation involves outlining the contour of an abnormality on an image to distinguish boundaries between normal and abnormal tissue and is essential to track malignant and benign disease in medical imaging for clinical, research, and treatment purposes. A laser optical mouse and a graphics tablet were used by radiologists to segment 12 simulated reference lesions per subject in two groups (one group comprised three lesion morphologies in two sizes, one for each input device for each device two sets of six, composed of three morphologies in two sizes each). Time for segmentation was recorded. Subjects completed an opinion survey following segmentation. Error in contour segmentation was calculated using root mean square error. Error in area of segmentation was calculated compared to the reference lesion. 11 radiologists segmented a total of 132 simulated lesions. Overall error in contour segmentation was less with the graphics tablet than with the mouse (P < 0.0001). Error in area of segmentation was not significantly different between the tablet and the mouse (P = 0.62). Time for segmentation was less with the tablet than the mouse (P = 0.011). All subjects preferred the graphics tablet for future segmentation (P = 0.011) and felt subjectively that the tablet was faster, easier, and more accurate (P = 0.0005). For purposes in which accuracy in contour of lesion segmentation is of the greater importance, the graphics tablet is superior to the mouse in accuracy with a small speed benefit. For purposes in which accuracy of area of lesion segmentation is of greater importance, the graphics tablet and mouse are equally accurate.

Sexual dimorphism in the adolescent brain: Role of testosterone and androgen receptor in global and local volumes of grey and white matter

Here we examined sex differences in the volumes of grey and white matter, and in grey-matter "density," in a group of typically developing adolescents participating in the Saguenay Youth Study (n=419; 12-18 years). In male adolescents, we also investigated the role of a functional polymorphism in androgen-receptor gene (AR) in moderating the effect of testosterone on volumes of grey and white matter and grey-matter density. Overall, both absolute and relative volumes of white matter were larger in male vs. females adolescents. The relative grey-matter volumes were slightly larger in female than male adolescents and so was the grey-matter density in a large number of cortical regions. In male adolescents, functional polymorphism of AR moderated the effect of testosterone on relative white- and grey-matter volumes. Following a discussion of several methodological and interpretational issues, we outline future directions in investigating brain-behavior relationships vis-à-vis psychopathology.

MR CONTRAST SYNTHESIS FOR LESION SEGMENTATION

The magnetic resonance contrast of a neuroimaging data set has strong impact on the utility of the data in image analysis tasks, such as registration and segmentation. Lengthy acquisition times often prevent routine acquisition of multiple MR contrast images, and opportunities for detailed analysis using these data would seem to be irrevocably lost. This paper describes an example based approach which uses patch matching from a multiple contrast atlas with the intended goal of generating an alternate MR contrast image, thus effectively simulating alternative pulse sequences from one another. In this paper, we deal specifically with Fluid Attenuated Inversion Recovery (FLAIR) sequence generation from T1 and T2 pulse sequences. The applicability of this synthetic FLAIR for estimating white matter lesions segmentation is demonstrated.

Segmentation of cortical MS lesions on MRI using automated laminar profile shape analysis

Cortical multiple sclerosis lesions are difficult to detect in magnetic resonance images due to poor contrast with surrounding grey matter, spatial variation in healthy grey matter and partial volume effects. We propose using an observer-independent laminar profile-based parcellation method to detect cortical lesions. Following cortical surface extraction, profiles are extended from the white matter surface to the grey matter surface. The cortex is parcellated according to profile intensity and shape features using a k-means classifier. The method is applied to a high-resolution quantitative magnetic resonance data set from a fixed post mortem multiple sclerosis brain, and validated using histology.