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

Effects of clozapine and olanzapine on cortical thickness in childhood-onset schizophrenia

BACKGROUND

Little is known about the effects of antipsychotic medications on gray matter (GM) in schizophrenia. Although clozapine remains the most effective antipsychotic medication in treatment-refractory cases, it is unknown whether it has a differential effect on GM development.

METHODS

In an exploratory analysis, we used automated cortical thickness measurements and prospectively scanned childhood-onset schizophrenia (COS) patients who were maintained on one medication. Two atypical antipsychotic medications, clozapine (n=12, 37 scans) and olanzapine (n=12, 33 scans) were compared with respect to effects on cortical development, in contrast to GM trajectories of matched controls.

RESULTS

There were no significant differences in the trajectories of cortical thickness between the two treatment groups with the exception of a small circumscribed area in the right prefrontal cortex, where the olanzapine group showed thicker cortex. As expected, both groups showed thinner GM compared to matched controls.

CONCLUSIONS

Although these analyses do not rule out effects of antipsychotic medications on GM development in schizophrenia, they show no differential effect between clozapine and olanzapine on GM trajectory.

Cerebellar volume and cognitive functioning in children who experienced early deprivation

BACKGROUND

The cerebellum is a brain region recognized primarily in the coordination of movement and related accessory motor functions. In addition, emerging evidence implicates the cerebellum in cognitive processes and suggests that this brain region might be subject to experience-dependent changes in structure. Therefore, the aim of this study was to evaluate the role of early environmental deprivation in the maturation of the cerebellum and aspects of cognitive development.

METHODS

Structural magnetic resonance imaging volumes of 12 cerebellar sub-regions from 31 previously neglected and 30 typically developing children were compared with subjects' corresponding neuropsychological test scores.

RESULTS

Neglected children had smaller volume of the superior-posterior cerebellar lobes. Moreover, superior-posterior lobe volume was found to mediate neuropsychological test performance differences between groups, with larger volumes yielding better outcomes on tests of memory and planning.

CONCLUSIONS

These data support the importance of experience-dependent changes in cerebellar structure and highlight the role of the cerebellum in higher cognitive functions.

3-D brain MRI tissue classification on FPGAs

Many automatic algorithms have been proposed for analyzing magnetic resonance imaging (MRI) data sets. With the increasingly large data sets being used in brain mapping, there has been a significant rise in the need for accelerating these algorithms. Partial volume estimation (PVE), a brain tissue classification algorithm for MRI, was implemented on a field-programmable gate array (FPGA)-based high performance reconfigurable computer using the Mitrion-C high-level language (HLL). This work develops on prior work in which we conducted initial studies on accelerating the prior information estimation algorithm. In this paper, we extend the work to include probability density estimation and present new results and additional analysis. We used several simulated and real human brain MR images to evaluate the accuracy and performance improvement of the proposed algorithm. The FPGA-based probability density estimation and prior information estimation implementation achieved an average speedup over an Itanium 2 CPU of 2.5 x and 9.4 x , respectively. The overall performance improvement of the FPGA-based PVE algorithm was 5.1 x with four FPGAs.

Handedness, motor skills and maturation of the corticospinal tract in the adolescent brain

With anatomical magnetic resonance imaging, the signal intensity of the corticospinal tract (CST) at the level of the internal capsule is often paradoxically similar to that of grey matter. As shown previously in histological studies, this is likely due to the presence of very large axons. We measured the apparent grey-matter density (aGMd) of the putative CST (pCST) in a large cohort of adolescents (n = 409, aged 12-18 years). We tested the following hypotheses: (1) The aGMd in the pCST shows a hemispheric asymmetry that is, in turn, related to hand preference; (2) the maturation of the CST during adolescence differs between both sexes, due to the influence of testosterone; (3) variations in aGMd in the pCST reflect inter-individual differences in manual skills. We confirmed the first two predictions. Thus, we found a strong left > right hemispheric asymmetry in aGMd that was, on average, less marked in the 40 left-handed subjects. Apparent GMd in the pCST increased with age in adolescent males but not females, and this was particularly related to rising plasma levels of testosterone in male adolescents. This finding is compatible with the idea that testosterone influences axonal calibre rather than myelination. The third prediction, namely that of a relationship between age-related changes in manual skills and maturation of the pCST, was not confirmed. We conclude that the leftward asymmetry of the pCST may reflect an early established asymmetry in the number of large corticomotoneuronal fibres in the pCST.

MRI measures of Alzheimer's disease and the AddNeuroMed study

Here we describe the AddNeuroMed multicenter magnetic resonance imaging (MRI) study for longitudinal assessment in Alzheimer's disease (AD). The study is similar to a faux clinical trial and has been established to assess longitudinal MRI changes in AD, mild cognitive impairment (MCI), and healthy control subjects using an image acquisition protocol compatible with the Alzheimer's Disease Neuroimaging Initiative (ADNI). The approach consists of a harmonized MRI acquisition protocol across centers, rigorous quality control, a central data analysis hub, and an automated image analysis pipeline. Comprehensive quality control measures have been established throughout the study. An intelligent web-accessible database holds details on both the raw images and data processed using a sophisticated image analysis pipeline. A total of 378 subjects were recruited (130 AD, 131 MCI, 117 healthy controls) of which a high percentage (97.3%) of the T1-weighted volumes passed the quality control criteria. Measurements of normalized whole brain volume, whole brain cortical thickness, and point-by-point group-based cortical thickness measurements, demonstrating the power of the automated image analysis techniques employed, are reported.

Are there differences in brain morphometry between twins and unrelated singletons? A pediatric MRI study

Twins provide a unique capacity to explore relative genetic and environmental contributions to brain development, but results are applicable to non-twin populations only to the extent that twin and singleton brains are alike. A reason to suspect differences is that as a group twins are more likely than singletons to experience adverse prenatal and perinatal events that may affect brain development. We sought to assess whether this increased risk leads to differences in child or adolescent brain anatomy in twins who do not experience behavioral or neurological sequelae during the perinatal period. Brain MRI scans of 185 healthy pediatric twins (mean age = 11.0, SD = 3.6) were compared to scans of 167 age- and sex-matched unrelated singletons on brain structures measured, which included gray and white matter lobar volumes, ventricular volume, and area of the corpus callosum. There were no significant differences between groups for any structure, despite sufficient power for low type II (i.e. false negative) error. The implications of these results are twofold: (1) within this age range and for these measures, it is appropriate to include healthy twins in studies of typical brain development, and (2) findings regarding heritability of brain structures obtained from twin studies can be generalized to non-twin populations.

General absence of abnormal cortical asymmetry in childhood-onset schizophrenia: a longitudinal study

BACKGROUND

Childhood-onset schizophrenia (COS) is a rare, severe form of the adult-onset illness, with more salient neurobiological causes. Previous cross-sectional structural neuroimaging research has suggested that normal cortical asymmetry patterns [(R-L)/(R+L)] may be altered in adult schizophrenia, although these findings were not well replicated. Recent studies show dynamic changes in brain asymmetry during childhood and adolescence. We hypothesized that COS patients would show a lack of normal development of asymmetry and decreased overall asymmetry.

METHODS

Prospective structural magnetic resonance scans were obtained at baseline and at two-year follow-up visits in 49 right-handed COS patients (mean baseline age: 14.72+/-2.63, 117 scans) and 50 age and sex-matched, right-handed healthy controls (mean baseline age: 15.15+/-3.37, 125 scans). Cortical thickness was calculated at 40,962 homologous points across each cerebral hemisphere using a fully automated, validated method. Differences in developmental asymmetry patterns across the cortical surface were analyzed using a linear mixed effects regression model.

RESULTS

No significant asymmetry differences were found either for cross-sectional comparisons of COS and healthy controls across the lateral and medial cortical surfaces or with respect to timing of developmental changes in asymmetry.

CONCLUSIONS

The present findings do not support asymmetry differences for this severe, early form of schizophrenia.

Multiple indicators of age-related differences in cerebral white matter and the modifying effects of hypertension

We investigated differences associated with age and hypertension, a common risk factor for vascular disease, in three aspects of white matter integrity--gross regional volumes of the white matter, volume of the white matter hyperintensities (WMH) and diffusion properties. We acquired MRI scans on 93 adult volunteers (age 50-77 years; 36 with diagnosis of hypertension or elevated blood pressure), and obtained all measures in seven brain regions: frontal, temporal, parietal and occipital white matter, and the genu, body and splenium of the corpus callosum. The results demonstrated robust age-related differences in diffusion-based indices of cerebral white matter integrity and age-related increase in the WMH volume, but no age differences in the gross regional volumes of the white matter. Hypertension was associated with decline in fractional anisotropy, and exacerbated age differences in fractional anisotropy more than those in the volume of WMH. These findings indicate that of all examined measures, diffusion-based indices of white matter integrity may be the most sensitive indicators of global and regional declines and vascular damage in the aging brain.

A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions

We describe a new fully automatic method for the segmentation of brain images that contain multiple sclerosis white matter lesions. Multichannel magnetic resonance images are used to delineate multiple sclerosis lesions while segmenting the brain into its major structures. The method is an atlas-based segmentation technique employing a topological atlas as well as a statistical atlas. An advantage of this approach is that all segmented structures are topologically constrained, thereby allowing subsequent processing such as cortical unfolding or diffeomorphic shape analysis techniques. Evaluation with both simulated and real data sets demonstrates that the method has an accuracy competitive with state-of-the-art MS lesion segmentation methods, while simultaneously segmenting the whole brain.

Multiple sclerosis lesion detection using constrained GMM and curve evolution

This paper focuses on the detection and segmentation of Multiple Sclerosis (MS) lesions in magnetic resonance (MRI) brain images. To capture the complex tissue spatial layout, a probabilistic model termed Constrained Gaussian Mixture Model (CGMM) is proposed based on a mixture of multiple spatially oriented Gaussians per tissue. The intensity of a tissue is considered a global parameter and is constrained, by a parameter-tying scheme, to be the same value for the entire set of Gaussians that are related to the same tissue. MS lesions are identified as outlier Gaussian components and are grouped to form a new class in addition to the healthy tissue classes. A probability-based curve evolution technique is used to refine the delineation of lesion boundaries. The proposed CGMM-CE algorithm is used to segment 3D MRI brain images with an arbitrary number of channels. The CGMM-CE algorithm is automated and does not require an atlas for initialization or parameter learning. Experimental results on both standard brain MRI simulation data and real data indicate that the proposed method outperforms previously suggested approaches, especially for highly noisy data.

Glycemic status and brain injury in older individuals: the age gene/environment susceptibility-Reykjavik study

OBJECTIVE

To examine the association of glycemic status to magnetic resonance imaging indicators of brain pathological changes.

RESEARCH DESIGN AND METHODS

This was a cross-sectional, population-based study of 4,415 men and women without dementia (mean age 76 years) participating in the Age Gene/Environment Susceptibility-Reykjavik Study. Glycemic status groups included the following: type 2 diabetes (self-report of diabetes, use of diabetes medications, or fasting blood glucose > or =7.0 mmol/l [11.1%]); impaired fasting glucose (IFG) (fasting blood glucose 5.6-6.9 mmol/l [36.2%]); and normoglycemic (52.7%). Outcomes were total brain volume, white and gray matter volume, white matter lesion (WML) volume, and presence of cerebral infarcts.

RESULTS

After adjustment for demographic and cardiovascular risk factors, participants with type 2 diabetes had significantly lower total brain volume (72.2 vs. 71.5%; P < 0.001) and lower gray and white matter volumes (45.1 vs. 44.9%, P < 0.01 and 25.7 vs. 25.3%, P < 0.001, respectively) and were more likely to have single (odds ratio 1.45 [95% CI 1.14-1.85]) or multiple (2.27 [1.60-3.23]) cerebral infarcts compared with normoglycemic participants. Longer duration of type 2 diabetes was associated with lower total brain volume and gray and white matter volume, higher WML volume (all P(trend) < 0.05), and a greater likelihood of single and multiple cerebral infarcts (all P(trend) < 0.01).

CONCLUSIONS

Type 2 diabetic participants have more pronounced brain atrophy and are more likely to have cerebral infarcts. Duration of type 2 diabetes is associated with brain changes, suggesting that type 2 diabetes has a cumulative effect on the brain.

Cerebellum development during childhood and adolescence: a longitudinal morphometric MRI study

In addition to its well-established role in balance, coordination, and other motor skills, the cerebellum is increasingly recognized as a prominent contributor to a wide array of cognitive and emotional functions. Many of these capacities undergo dramatic changes during childhood and adolescence. However, accurate characterization of co-occurring anatomical changes has been hindered by lack of longitudinal data and methodologic challenges in quantifying subdivisions of the cerebellum. In this study we apply an innovative image analysis technique to quantify total cerebellar volume and 11 subdivisions (i.e. anterior, superior posterior, and inferior posterior lobes, corpus medullare, and three vermal regions) from anatomic brain MRI scans from 25 healthy females and 25 healthy males aged 5-24 years, each of whom was scanned at least three times at approximately 2-year intervals. Total cerebellum volume followed an inverted U shaped developmental trajectory peaking at age 11.8 years in females and 15.6 years in males. Cerebellar volume was 10% to 13% larger in males depending on the age of comparison and the sexual dimorphism remained significant after covarying for total brain volume. Subdivisions of the cerebellum had distinctive developmental trajectories with more phylogenetically recent regions maturing particularly late. The cerebellum's unique protracted developmental trajectories, sexual dimorphism, preferential vulnerability to environmental influences, and frequent implication in childhood onset disorders such as autism and ADHD make it a prime target for pediatric neuroimaging investigations.

Development of cortical asymmetry in typically developing children and its disruption in attention-deficit/hyperactivity disorder

CONTEXT

Just as typical development of anatomical asymmetries in the human brain has been linked with normal lateralization of motor and cognitive functions, disruption of asymmetry has been implicated in the pathogenesis of neurodevelopmental disorders such as attention-deficit/hyperactivity disorder (ADHD). No study has examined the development of cortical asymmetry using longitudinal neuroanatomical data.

OBJECTIVE

To delineate the development of cortical asymmetry in children with and without ADHD.

DESIGN

Longitudinal study.

SETTING

Government Clinical Research Institute.

PARTICIPANTS

A total of 218 children with ADHD and 358 typically developing children, from whom 1133 neuroanatomical magnetic resonance images were acquired prospectively.

MAIN OUTCOME MEASURES

Cortical thickness was estimated at 40 962 homologous points in the left and right hemispheres, and the trajectory of change in asymmetry was defined using mixed-model regression.

RESULTS

In right-handed typically developing individuals, a mean (SE) increase in the relative thickness of the right orbitofrontal and inferior frontal cortex with age of 0.011 (0.0018) mm per year (t(337) = 6.2, P < .001) was balanced against a relative left-hemispheric increase in the occipital cortical regions of 0.013 (0.0015) mm per year (t(337) = 8.1, P < .001). Age-related change in asymmetry in non-right-handed typically developing individuals was less extensive and was localized to different cortical regions. In ADHD, the posterior component of this evolving asymmetry was intact, but the prefrontal component was lost.

CONCLUSIONS

These findings explain the way that, in typical development, the increased dimensions of the right frontal and left occipital cortical regions emerge in adulthood from the reversed pattern of childhood cortical asymmetries. Loss of the prefrontal component of this evolving asymmetry in ADHD is compatible with disruption of prefrontal function in the disorder and demonstrates the way that disruption of typical processes of asymmetry can inform our understanding of neurodevelopmental disorders.

Encoding probabilistic brain atlases using Bayesian inference

This paper addresses the problem of creating probabilistic brain atlases from manually labeled training data. Probabilistic atlases are typically constructed by counting the relative frequency of occurrence of labels in corresponding locations across the training images. However, such an "averaging" approach generalizes poorly to unseen cases when the number of training images is limited, and provides no principled way of aligning the training datasets using deformable registration. In this paper, we generalize the generative image model implicitly underlying standard "average" atlases, using mesh-based representations endowed with an explicit deformation model. Bayesian inference is used to infer the optimal model parameters from the training data, leading to a simultaneous group-wise registration and atlas estimation scheme that encompasses standard averaging as a special case. We also use Bayesian inference to compare alternative atlas models in light of the training data, and show how this leads to a data compression problem that is intuitive to interpret and computationally feasible. Using this technique, we automatically determine the optimal amount of spatial blurring, the best deformation field flexibility, and the most compact mesh representation. We demonstrate, using 2-D training datasets, that the resulting models are better at capturing the structure in the training data than conventional probabilistic atlases. We also present experiments of the proposed atlas construction technique in 3-D, and show the resulting atlases' potential in fully-automated, pulse sequence-adaptive segmentation of 36 neuroanatomical structures in brain MRI scans.

Positional and surface area asymmetry of the human cerebral cortex

Previous studies of cortical asymmetry have relied mainly on voxel-based morphometry (VBM), or manual segmentation of regions of interest. This study uses fully automated, surface-based techniques to analyse position and surface area asymmetry for the mid-surfaces of 112 right-handed subjects' cortical hemispheres from a cohort of young adults. Native space measurements of local surface area asymmetry and vertex position asymmetry were calculated from surfaces registered to a previously validated hemisphere-unbiased surface-based template. Our analysis confirms previously identified hemispheric asymmetries (Yakovlevian torque, frontal and occipital petalia) in enhanced detail. It does not support previous findings of gender/asymmetry interactions or rightward planum parietale areal increase. It reveals several new findings, including a striking leftward increase in surface area of the supramarginal gyrus (peak effect 18%), compared with a smaller areal increase in the left Heschl's gyrus and planum temporale region (peak effect 8%). A second finding was rightward increase in surface area (peak effect 10%) in a band around the medial junction between the occipital lobe, and parietal and temporal lobes. By clearly separating out the effects of structural translocation and surface area change from those of thickness and curvature, this study resolves the confound of these variables inherent in VBM studies.

Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds

Neuroimaging studies, using various modalities, have evidenced a link between the general intelligence factor (g) and regional brain function and structure in several multimodal association areas. While in the last few years, developments in computational neuroanatomy have made possible the in vivo quantification of cortical thickness, the relationship between cortical thickness and psychometric intelligence has been little studied. Recently, cortical thickness estimations have been improved by the use of an iterative hemisphere-specific template registration algorithm which provides a better between-subject alignment of brain surfaces. Using this improvement, we aimed to further characterize brain regions where cortical thickness was associated with cognitive ability differences and to test the hypothesis that these regions are mostly located in multimodal association areas. We report associations between a general cognitive ability factor (as an estimate of g) derived from the four subtests of the Wechsler Abbreviated Scale of Intelligence and cortical thickness adjusted for age, gender, and scanner in a large sample of healthy children and adolescents (ages 6-18, N=216) representative of the US population. Significant positive associations were evidenced between the cognitive ability factor and cortical thickness in most multimodal association areas. Results are consistent with a distributed model of intelligence.

Computational anatomy with the SPM software

An overview of computational procedures for examining neuroanatomical variability is presented. The review focuses on approaches that can be applied using the SPM software package, beginning by explaining briefly how statistical parametric mapping is usually applied to functional imaging data. The review then proceeds to discuss volumetry, with an emphasis on voxel-based morphometry, and the pre-processing steps involved using the SPM software. Most volumetric studies involve univariate approaches, with a correction for some global measure, such as total brain volume. In contrast, the overall form of the brain may be more accurately modeled using multivariate approaches. Such models of anatomical variability may prove accurate enough for computer assisted diagnoses.

Sex differences in the growth of white matter during adolescence

The purpose of this study was to examine sex differences in the maturation of white matter during adolescence (12 to 18 years of age). We measured lobular volumes of white matter and white-matter "density" throughout the brain using T1-weighted images, and estimated the myelination index using magnetisation-transfer ratio (MTR). In male adolescents, we observed age-related increases in white-matter lobular volumes accompanied by decreases in the lobular values of white-matter MTR. White-matter density in the putative cortico-spinal tract (pCST) decreased with age. In female adolescents, on the other hand, we found only small age-related increase in white-matter volumes and no age-related changes in white-matter MTR, with the exception of the frontal lobe where MTR increased. White-matter density in the pCST also increased with age. These results suggest that sex-specific mechanisms may underlie the growth of white matter during adolescence. We speculate that these mechanisms involve primarily age-related increases in axonal calibre in males and increased myelination in females.

Cerebral infarcts and cognitive performance: importance of location and number of infarcts

BACKGROUND AND PURPOSE

Cerebral infarcts increase the risk for cognitive impairment. The relevance of location and number of infarcts with respect to cognitive function is less clear.

METHODS

We studied the cross-sectional association between number and location of infarcts and cognitive performance in 4030 nondemented participants of the Age Gene/Environment Susceptibility-Reykjavik Study. Composite scores for memory, processing speed, and executive function were created from a neuropsychological battery. Subcortical, cortical, and cerebellar infarcts were identified on brain MRI. We performed linear regression analyses adjusted for demographic and vascular risk factors, depression, white matter lesions, and atrophy.

RESULTS

Compared to participants with no infarcts, those with infarcts in multiple locations (n=287, 7%) had slower processing speed (beta=-0.19; P<0.001) and poorer memory (beta=-0.16; P<0.001) and executive function (beta=-0.12; P=0.003). Compared to no infarcts, the presence of either subcortical infarcts only (n=275; beta=-0.12; P=0.016) or cortical infarcts only (n=215; beta=-0.17; P=0.001) was associated with poorer memory performance. Compared to no infarcts, a combination of cortical and subcortical infarcts (n=45) was associated with slower processing speed (beta=-0.38; P<0.001) and poorer executive function (beta=-0.22; P=0.02), whereas a combination of cerebellar and subcortical infarcts (n=89) was associated with slower processing speed (beta=-0.15; P=0.04). Infarcts in all 3 locations was associated with slower processing speed (beta=-0.33; P=0.002).

CONCLUSIONS

Having infarcts in >1 location is associated with poor performance in memory, processing speed, and executive function, independent of cardiovascular comorbidities, white matter lesions, and brain atrophy, suggesting that both the number and the distribution of infarcts jointly contribute to cognitive impairment.

The effect of template choice on morphometric analysis of pediatric brain data

The present study investigated the "template effect" on the morphometric analysis of a pediatric brain MRI database obtained from 8-year-old children through various measures of surface and volumetric morphologies. We first constructed an age-appropriate template from an independent set of pediatric brain images and then compared it with a well-known adult brain template, the ICBM152, in terms of the morphometric features that resulted from our pediatric database. The individual cortical surface acquired based on the pediatric template exhibited, on average, a significantly thinner cortex (-1.66+/-1.60%, t=-15.18), larger cortical surface areas (0.31+/-0.70%, t=6.52), and a higher degree of cortical folding (0.08+/-0.13%, t=8.72) while compared with those based on the adult template. We also found a significant increase in the cerebrospinal fluid volume (-2.63+/-4.84) for the adult template based brains and the cortical gray matter (GM) volume (6.10+/-7.81) for the pediatric template based brains. The cross-correlation of pediatric template based individual brain data (0.95 without brain mask) was significantly higher than those of adult template based (0.88) and the amount of deformation during non-linear spatial normalization was significantly reduced when using the pediatric template (average magnitude of deformation in the cortical GM class: 1.71 mm vs. 2.23 mm, t=12.39). In addition, an "internal" pediatric template, taken from the study subjects themselves, was generated and compared with the "external" pediatric template for reference. There was no significant difference between these two pediatric brain templates and associated tissue probability maps. The results show that it is necessary to be cautious when interpreting results from pediatric imaging studies based on adult reference data.

Psychostimulant treatment and the developing cortex in attention deficit hyperactivity disorder

OBJECTIVE

While there has been considerable concern over possible adverse effects of psychostimulants on brain development, this issue has not been examined in a prospective study. The authors sought to determine prospectively whether psychostimulant treatment for attention deficit hyperactivity disorder (ADHD) was associated with differences in the development of the cerebral cortex during adolescence.

METHOD

Change in cortical thickness was estimated from two neuroanatomic MRI scans in 43 youths with ADHD. The mean age at the first scan was 12.5 years, and at the second scan, 16.4 years. Nineteen patients not treated with psychostimulants between the scans were compared with an age-matched group of 24 patients who were treated with psychostimulants. Further comparison was made against a template derived from 620 scans of 294 typically developing youths without ADHD.

RESULTS

Adolescents taking psychostimulants differed from those not taking psychostimulants in the rate of change of the cortical thickness in the right motor strip, the left middle/inferior frontal gyrus, and the right parieto-occipital region. The group difference was due to more rapid cortical thinning in the group not taking psychostimulants (mean cortical thinning of 0.16 mm/year [SD=0.17], compared with 0.03 mm/year [SD=0.11] in the group taking psychostimulants). Comparison against the typically developing cohort without ADHD showed that cortical thinning in the group not taking psychostimulants was in excess of age-appropriate rates. The treatment groups did not differ in clinical outcome, however.

CONCLUSIONS

These findings show no evidence that psychostimulants were associated with slowing of overall growth of the cortical mantle.

Differences in genetic and environmental influences on the human cerebral cortex associated with development during childhood and adolescence

In this report, we present the first regional quantitative analysis of age-related differences in the heritability of cortical thickness using anatomic MRI with a large pediatric sample of twins, twin siblings, and singletons (n = 600, mean age 11.1 years, range 5-19). Regions of primary sensory and motor cortex, which develop earlier, both phylogenetically and ontologically, show relatively greater genetic effects earlier in childhood. Later developing regions within the dorsal prefrontal cortex and temporal lobes conversely show increasingly prominent genetic effects with maturation. The observation that regions associated with complex cognitive processes such as language, tool use, and executive function are more heritable in adolescents than children is consistent with previous studies showing that IQ becomes increasingly heritable with maturity(Plomin et al. 1997: Psychol Sci 8:442-447). These results suggest that both the specific cortical region and the age of the population should be taken into account when using cortical thickness as an intermediate phenotype to link genes, environment, and behavior.

Measuring brain lesion progression with a supervised tissue classification system

Brain lesions, especially White Matter Lesions (WMLs), are associated with cardiac and vascular disease, but also with normal aging. Quantitative analysis of WML in large clinical trials is becoming more and more important. In this paper, we present a computer-assisted WML segmentation method, based on local features extracted from conventional multi-parametric Magnetic Resonance Imaging (MRI) sequences. A framework for preprocessing the temporal data by jointly equalizing histograms reduces the spatial and temporal variance of data, thereby improving the longitudinal stability of such measurements and hence the estimate of lesion progression. A Support Vector Machine (SVM) classifier trained on expert-defined WML's is applied for lesion segmentation on each scan using the AdaBoost algorithm. Validation on a population of 23 patients from 3 different imaging sites with follow-up studies and WMLs of varying sizes, shapes and locations tests the robustness and accuracy of the proposed segmentation method, compared to the manual segmentation results from an experienced neuroradiologist. The results show that our CAD-system achieves consistent lesion segmentation in the 4D data facilitating the disease monitoring.

Brain imaging in drug R&D

Magnetic resonance imaging (MRI), used as a clinical diagnostic tool since the early 1980s, is rapidly gaining traction as an integral part of the drug development process. Brain imaging research spans a wide area, covering both structure and function, and ranging from the physics and physiology associated with novel acquisition techniques, to the development of sophisticated image processing algorithms. This paper briefly describes two methods on either end of this spectrum: the "pipeline" framework for the fully automated morphometric analysis of brain imaging data, and molecular MRI, which holds promise for the non-invasive detection of molecular targets of new pharmacological compounds. The potential use of these technologies is illustrated by examples of their applications in multiple sclerosis, Alzheimer's disease, and oncology.

Depth potential function for folding pattern representation, registration and analysis

Some surfaces present folding patterns formed by juxtapositions of ridges and valleys as, for example, the cortical surface of the human brain. The fundamental problem with ridges is to find a correspondence among and analyze the variability among them. Many techniques to achieve these goals exist but use scalar functions. Depth maps are used to efficiently project the geometry of folds into a scalar function in the case where a natural projection plane exists. However, in most cases of curved surfaces, there is no natural projection plane to represent folding patterns. This paper studies the problem of shape matching and analysis of folding patterns by extending the notion of depth maps when no natural projection plane exists. The novel depth measure is called a depth potential function. The depth potential function integrates the information known from the curvature of the surface into a point-of-view invariant representation. The main advantage of the depth potential function is that it is computed by solving a time independent Poisson equation. The Poisson equation endows our surface representation with a significant computational advantage that makes it orders of magnitude faster to compute compared with other available surface representations. The method described in this paper was validated using both synthetic surfaces and cortical surfaces of human brain acquired by magnetic resonance imaging. On average, the improvement in shape matching when using the depth potential was of 11%, which is considerable.

Remission status and cortical thickness in childhood-onset schizophrenia

OBJECTIVE

Few studies have examined prediction of schizophrenia outcome in relation to brain magnetic resonance imaging measures. In this study, remission status at the time of discharge was examined in relation to admission cortical thickness for childhood-onset schizophrenia probands. We hypothesized that total, frontal, temporal, and parietal gray matter thickness would be greater in patients who subsequently remit.

METHOD

The relation between admission cortical brain thickness on magnetic resonance imaging and remission status at the time of discharge an average of 3 months later was examined for 56 individuals (32 males) ages 6 to 19 diagnosed with childhood-onset schizophrenia. Cortical thickness was measured across the cerebral hemispheres at admission. Discharge remission criteria were adapted from the 2005 Remission in Schizophrenia Working Group criteria.

RESULTS

Patients remitted at discharge (n = 16 [29%]) had thicker regional cortex in left orbitofrontal, left superior, and middle temporal gyri and bilateral postcentral and angular gyri (p < or = .008).

CONCLUSIONS

Our results provide neuroanatomic correlates of clinical remission in schizophrenia and evidence that response to treatment may be mediated by these cortical brain regions.

Automated quality control of brain MR images

PURPOSE

To present a novel fully automated method for assessing the quality of magnetic resonance imaging (MRI) data acquired in a clinical trials environment.

MATERIALS AND METHODS

This work was performed in the context of clinical trials for multiple sclerosis. Quality control (QC) procedures included were: (i) patient brain identity verification, (ii) alphanumeric parameter matching, (iii) signal-to-noise ratio estimation, (iv) gadolinium-enhancement verification, and (v) detection of ghosting due to head motion. Each QC procedure produces a quantitative measurement which is compared against an acceptance threshold that was determined based on receiver operating characteristic analysis of traditional manual and visual QC performed by trained experts.

RESULTS

The automated QC results have high sensitivity and specificity when compared with the visual QC.

CONCLUSION

Our automated objective QC procedure can replace many manual subjective procedures to provide increased data throughput while reducing reader variability.

Automatic image-driven segmentation of the ventricles in cardiac cine MRI

PURPOSE

To propose and to evaluate a novel method for the automatic segmentation of the heart's two ventricles from dynamic ("cine") short-axis "steady state free precession" (SSFP) MR images. This segmentation task is of significant clinical importance. Previously published automated methods have various disadvantages for routine clinical use.

MATERIALS AND METHODS

The proposed method is primarily image-driven: it exploits the spatiotemporal information provided by modern 3D+time SSFP cardiac MRI, and makes only few and plausible assumptions about the image acquisition and about the imaged heart. Specifically, the method does not require previously trained statistical shape models or gray-level appearance models, as often used by other methods.

RESULTS

The performance of the segmentation method was demonstrated through a qualitative visual validation on 32 clinical exams: no gross failures for the left-ventricle (right-ventricle) on 31 (29) of the exams were found. A validation of resulting quantitative cardiac functional parameters showed good agreement with a manual quantification of 19 clinical exams.

CONCLUSION

The proposed method is feasible, fast, and robust against anatomical variability and image contrast variations.

Advances in neuroimaging in patients with epilepsy

Intractable seizures can have a devastating effect on the development of a child. In children with intractable epilepsy that is refractory to medication, surgical treatment may be needed. Magnetic resonance imaging is an essential neuroimaging tool to assist in the identification of an epileptogenic substrate. The interpretation of MR images should be done in the context of clinical knowledge of the seizure symptomatology and electroencephalographic findings. Quantitative processing of structural MR data and advanced MR imaging such as diffusion tensor imaging and MR spectroscopy have the potential to identify subtle lesions that may otherwise have been missed. In addition to lesion localization, identification of eloquent cortex and white matter tracts are also an essential component of epilepsy surgery workup. Functional MR imaging maps the sensorimotor cortex and also lateralizes language. Diffusion tensor imaging tractography can be used to map the corticospinal tracts and the optic radiations. In addition to MR imaging, magnetoencephalography and nuclear medicine studies such as PET and SPECT scanning may be used to lateralize seizure focus when clinical, electrophysiological, and structural MR imaging findings are discordant.

Quantification of brain maturation and growth patterns in C57BL/6J mice via computational neuroanatomy of diffusion tensor images

Diffusion Tensor magnetic resonance imaging and computational neuroanatomy are used to quantify postnatal developmental patterns of C57BL/6J mouse brain. Changes in neuronal organization and myelination occurring as the brain matures into adulthood are examined, and a normative baseline is developed, against which transgenic mice may be compared in genotype-phenotype studies. In early postnatal days, gray matter-based cortical and hippocampal structures exhibit high water diffusion anisotropy, presumably reflecting the radial neuronal organization. Anisotropy drops rapidly within a week, indicating that the underlying brain tissue becomes more isotropic in orientation, possibly due to formation of a complex randomly intertwined web of dendrites. Gradual white matter anisotropy increase implies progressively more organized axonal pathways, likely reflecting the myelination of axons forming tightly packed fiber bundles. In contrast to the spatially complex pattern of tissue maturation, volumetric growth is somewhat uniform, with the cortex and the cerebellum exhibiting slightly more pronounced growth. Temporally, structural growth rates demonstrate an initial rapid volumetric increase in most structures, gradually tapering off to a steady state by about 20 days. Fiber maturation reaches steady state in about 10 days for the cortex, to 30-40 days for the corpus callosum, the hippocampus, and the internal and external capsules.

Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling

The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found that mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.

Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's disease

Recent research on Alzheimer's disease (AD) has shown that cognitive and memory decline in this disease is accompanied by disrupted changes in the coordination of large-scale brain functional networks. However, alterations in coordinated patterns of structural brain networks in AD are still poorly understood. Here, we used cortical thickness measurement from magnetic resonance imaging to investigate large-scale structural brain networks in 92 AD patients and 97 normal controls. Brain networks were constructed by thresholding cortical thickness correlation matrices of 54 regions and analyzed using graph theoretical approaches. Compared with controls, AD patients showed decreased cortical thickness intercorrelations between the bilateral parietal regions and increased intercorrelations in several selective regions involving the lateral temporal and parietal cortex as well as the cingulate and medial frontal cortex regions. Specially, AD patients showed abnormal small-world architecture in the structural cortical networks (increased clustering and shortest paths linking individual regions), implying a less optimal topological organization in AD. Moreover, AD patients were associated with reduced nodal centrality predominantly in the temporal and parietal heteromodal association cortex regions and increased nodal centrality in the occipital cortex regions. Finally, the brain networks of AD were about equally as robust to random failures as those of controls, but more vulnerable against targeted attacks, presumably because of the effects of pathological topological organization. Our findings suggest that the coordinated patterns of cortical morphology are widely altered in AD patients, thus providing structural evidence for disrupted integrity in large-scale brain networks that underlie cognition. This work has implications for our understanding of how functional deficits in patients are associated with their underlying structural (morphological) basis.

Neurodevelopmental trajectories of the human cerebral cortex

Understanding the organization of the cerebral cortex remains a central focus of neuroscience. Cortical maps have relied almost exclusively on the examination of postmortem tissue to construct structural, architectonic maps. These maps have invariably distinguished between areas with fewer discernable layers, which have a less complex overall pattern of lamination and lack an internal granular layer, and those with more complex laminar architecture. The former includes several agranular limbic areas, and the latter includes the homotypical and granular areas of association and sensory cortex. Here, we relate these traditional maps to developmental data from noninvasive neuroimaging. Changes in cortical thickness were determined in vivo from 764 neuroanatomic magnetic resonance images acquired longitudinally from 375 typically developing children and young adults. We find differing levels of complexity of cortical growth across the cerebrum, which align closely with established architectonic maps. Cortical regions with simple laminar architecture, including most limbic areas, predominantly show simpler growth trajectories. These areas have clearly identified homologues in all mammalian brains and thus likely evolved in early mammals. In contrast, polysensory and high-order association areas of cortex, the most complex areas in terms of their laminar architecture, also have the most complex developmental trajectories. Some of these areas are unique to, or dramatically expanded in primates, lending an evolutionary significance to the findings. Furthermore, by mapping a key characteristic of these development trajectories (the age of attaining peak cortical thickness) we document the dynamic, heterochronous maturation of the cerebral cortex through time lapse sequences ("movies").

Effect of memantine on CBF and CMRO2 in patients with early Parkinson's disease

OBJECTIVES

Parkinson's disease (PD) may be associated with increased energy metabolism in overactive regions of the basal ganglia. Therefore, we hypothesized that treatment with the N-methyl-d-aspartate receptor (NMDAR) antagonist memantine would decrease regional cerebral blood flow (rCBF) and oxygen metabolism in the basal ganglia of patients with early-stage PD.

METHODS

Quantitative positron emission tomography (PET) recordings were obtained with 15O]water and 15O]oxygen in 10 patients, scanned first in a baseline condition, and again 6 weeks after treatment with a daily dose of 20 mg memantine. Dynamic PET data were analyzed using volume of interest and voxel-based approaches.

RESULTS

The treatment evoked rCBF decreases in basal ganglia, and in several frontal cortical areas. The regional cerebral metabolic rate of oxygen (rCMRO2) did not decrease in any of the a priori defined regions, and consequently the oxygen extraction fraction was increased in these regions. Two peaks of significantly decreased rCMRO2 were detected near the frontal poles in both hemispheres, using a posteriori voxel-based analysis.

CONCLUSIONS

Although we did not find the predicted decrease in basal ganglia oxygen consumption, our data suggest that treatment with memantine actively modulates neuronal activity and/or hemodynamic response in basal ganglia of PD patients. This finding may be relevant to the putative neuroprotective properties of NMDAR antagonists.

An optimized blockwise nonlocal means denoising filter for 3-D magnetic resonance images

A critical issue in image restoration is the problem of noise removal while keeping the integrity of relevant image information. Denoising is a crucial step to increase image quality and to improve the performance of all the tasks needed for quantitative imaging analysis. The method proposed in this paper is based on a 3-D optimized blockwise version of the nonlocal (NL)-means filter (Buades, et al., 2005). The NL-means filter uses the redundancy of information in the image under study to remove the noise. The performance of the NL-means filter has been already demonstrated for 2-D images, but reducing the computational burden is a critical aspect to extend the method to 3-D images. To overcome this problem, we propose improvements to reduce the computational complexity. These different improvements allow to drastically divide the computational time while preserving the performances of the NL-means filter. A fully automated and optimized version of the NL-means filter is then presented. Our contributions to the NL-means filter are: 1) an automatic tuning of the smoothing parameter; 2) a selection of the most relevant voxels; 3) a blockwise implementation; and 4) a parallelized computation. Quantitative validation was carried out on synthetic datasets generated with BrainWeb (Collins, et al., 1998). The results show that our optimized NL-means filter outperforms the classical implementation of the NL-means filter, as well as two other classical denoising methods [anisotropic diffusion (Perona and Malik, 1990)] and total variation minimization process (Rudin, et al., 1992) in terms of accuracy (measured by the peak signal-to-noise ratio) with low computation time. Finally, qualitative results on real data are presented .