Brain Volume Imaging Research Articles

Magnetic Resonance Imaging and Head Circumference Study of Brain Size in Autism

While the neuroanatomical basis of autism is not yet known, evidence suggests that brain enlargement may be characteristic of this disorder. Inferences about the timing of brain enlargement have recently come from studies of head circumference (HC). To examine brain volume and HC in individuals with autism as compared with control individuals. A cross-sectional study of brain volume was conducted at the first time point in an ongoing longitudinal magnetic resonance imaging study of brain development in autism. Retrospective longitudinal HC measurements were gathered from medical records on a larger sample of individuals with autism and local control individuals. Clinical research center. The magnetic resonance imaging study included 51 children with autism and 25 control children between 18 and 35 months of age (the latter included both developmentally delayed and typically developing children). Retrospective, longitudinal HC data were examined from birth to age 3 years in 113 children with autism and 189 local control children. Cerebral cortical (including cortical lobes) and cerebellar gray and white matter magnetic resonance imaging brain volumes as well as retrospective HC data from medical records were studied. Significant enlargement was detected in cerebral cortical volumes but not cerebellar volumes in individuals with autism. Enlargement was present in both white and gray matter, and it was generalized throughout the cerebral cortex. Head circumference appears normal at birth, with a significantly increased rate of HC growth appearing to begin around 12 months of age. Generalized enlargement of gray and white matter cerebral volumes, but not cerebellar volumes, are present at 2 years of age in autism. Indirect evidence suggests that this increased rate of brain growth in autism may have its onset postnatally in the latter part of the first year of life.

Cerebellar dysfunction in neuroleptic naive schizophrenia patients: clinical, cognitive, and neuroanatomic correlates of cerebellar neurologic signs

BackgroundThere is increasing evidence that, aside from motor coordination, the cerebellum also plays an important role in cognition and psychiatric disorders. Our previous studies support the hypothesis that cerebellar dysfunction may disrupt the cortico-cerebellar-thalamic-cortical circuit and, in turn, lead to cognitive dysmetria in schizophrenia. The goal of this study was to investigate cerebellar dysfunction in schizophrenia by examining the clinical, cognitive, and neuroanatomic correlates of cerebellar neurologic signs in schizophrenia patients. MethodsWe compared the prevalence of cerebellar neurologic signs in 155 neuroleptic-naive schizophrenia patients against 155 age- and gender-matched healthy control subjects. Differences in clinical characteristics, standardized neuropsychologic performance, and magnetic resonance imaging brain volumes between patients with and without cerebellar signs were also examined. ResultsPatients had significantly higher rates of cerebellar signs than control subjects, with coordination of gait and stance being the most common abnormalities. Patients with lifetime alcohol abuse or dependence were no more likely than those without alcoholism to have cerebellar signs. Presence of cerebellar signs in patients was associated with poorer premorbid adjustment, more severe negative symptoms, poorer cognitive performance, and smaller cerebellar tissue volumes. ConclusionsThese findings lend further support for cerebellar dysfunction in schizophrenia.

Extensive individual differences in brain activations associated with episodic retrieval are reliable over time.

The localization of brain functions using neuroimaging techniques is commonly dependent on statistical analyses of groups of subjects in order to identify sites of activation, particularly in studies of episodic memory. Exclusive reliance on group analysis may be to the detriment of understanding the true underlying cognitive nature of brain activations. In the present study, we found that the patterns of brain activity associated with episodic retrieval are very distinct for individual subjects from the patterns of brain activity at the group level. These differences go beyond the relatively small variations due to cyctoarchitectonic differences or spatial normalization. We quantify this individual variability by cross-correlating volumes of brain images. We demonstrate that individual patterns of brain activity are reliable over time despite their extensive variability. We suggest that varied but reliable individual patterns of significant brain activity may be indicative of different cognitive strategies used to produce a recognition response. We believe that individual analysis in conjunction with group analysis may be critical to fully understanding the relationship between retrieval processes and underlying brain regions.

Functional magnetic resonance imaging of the human brain: data acquisition and analysis.

It is now feasible to create spatial maps of activity in the human brain completely non-invasively using magnetic resonance imaging. Magnetic resonance imaging (MRI) images in which the spin magnetization is refocussed by gradient switching are sensitive to local changes in magnetic susceptibility, which can occur when the oxygenation state of blood changes. Cortical neural activity causes increases in blood flow, which usually result in changes in blood oxygenation. Hence changes of image intensity can be observed, given rise to the so-called Blood Oxygenation Level Dependent (BOLD) contrast technique. Use of echo-planar imaging methods (EPI) allows the monitoring over the entire brain of such changes in real time. A temporal resolution of 1-3 s, and a spatial resolution of 2 mm in-plane, can thus be obtained. Generally in a brain mapping experiment hundred of brain image volumes are acquired at repeat times of 1-6 s, while brain tasks are performed. The data are transformed into statistical maps of image difference, using the technique known as statistical parametric mapping (SPM). This method, based on robust multilinear regression techniques, has become the method of reference for analysis of positron emission tomography (PET) image data. The special characteristics of functional MRI data require some modification of SPM algorithms and strategies, and the MRI data must be gaussianized in time and space to conform to the assumptions of the statistics of Gaussian random fields. The steps of analysis comprise: removal of head movement effects, spatial smoothing, and statistical interference, which includes temporal smoothing and removal by fitting of temporal variations slower than the experimental paradigm. By these means, activation maps can be generated with great flexibility and statistical power, giving probability estimates for activated brain regions based on intensity or spatial extent, or both combined. Recent studies have shown that patterns of activation obtained in human brain for a given stimulus are independent of the order and spatial orientation with which MRI images are acquired, and hence that inflow effects are not important for EPI data with a TR much longer than T1.

Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space

In both diagnostic and research applications, the interpretation of MR images of the human brain is facilitated when different data sets can be compared by visual inspection of equivalent anatomical planes. Quantitative analysis with predefined atlas templates often requires the initial alignment of atlas and image planes. Unfortunately, the axial planes acquired during separate scanning sessions are often different in their relative position and orientation, and these slices are not coplanar with those in the atlas. We have developed a completely automatic method to register a given volumetric data set with Talairach stereotaxic coordinate system. The registration method is based on multi-scale, three-dimensional (3D) cross-correlation with an average (n > 300) MR brain image volume aligned with the Talariach stereotaxic space. Once the data set is re-sampled by the transformation recovered by the algorithm, atlas slices can be directly superimposed on the corresponding slices of the re-sampled volume. the use of such a standardized space also allows the direct comparison, voxel to voxel, of two or more data sets brought into stereotaxic space. With use of a two-tailed Student t test for paired samples, there was no significant difference in the transformation parameters recovered by the automatic algorithm when compared with two manual landmark-based methods (p > 0.1 for all parameters except y-scale, where p > 0.05). Using root-mean-square difference between normalized voxel intensities as an unbiased measure of registration, we show that when estimated and averaged over 60 volumetric MR images in standard space, this measure was 30% lower for the automatic technique than the manual method, indicating better registrations. Likewise, the automatic method showed a 57% reduction in standard deviation, implying a more stable technique. The algorithm is able to recover the transformation even when data are missing from the top or bottom of the volume. We present a fully automatic registration method to map volumetric data into stereotaxic space that yields results comparable with those of manually based techniques. The method requires no manual identification of points or contours and therefore does not suffer the drawbacks involved in user intervention such as reproducibility and interobserver variability.

Elastically deforming 3D atlas to match anatomical brain images.

To evaluate our system for elastically deforming a three-dimensional atlas to match anatomical brain images, six deformed versions of an atlas were generated. The deformed atlases were created by elastically mapping an anatomical brain atlas onto different MR brain image volumes. The mapping matches the edges of the ventricles and the surface of the brain; the resultant deformations are propagated through the atlas volume, deforming the remainder of the structures in the process. The atlas was then elastically matched to its deformed versions. The accuracy of the resultant matches was evaluated by determining the correspondence of 32 cortical and subcortical structures. The system on average matched the centroid of a structure to within 1 mm of its true position and fit a structure to within 11% of its true volume. The overlap between the matched and true structures, defined by the ratio between the volume of their intersection and the volume of their union, averaged 66%. When the gray-white interface was included for matching, the mean overlap improved to 78%; each structure was matched to within 0.6 mm of its true position and fit to within 6% of its true volume. Preliminary studies were also made to determine the effect of the compliance of the atlas on the resultant match.