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Children with autism spectrum disorder (ASD) exhibit characteristic cognitive and behavioral differences, but no systematic pattern of neuroanatomical differences has been consistently found. Recent neurodevelopmental models posit an abnormal early surge in subcortical white matter growth in at least some autistic children, perhaps normalizing by adulthood, but other studies report subcortical white matter deficits. To investigate the profile of these alterations in 3D, we mapped brain volumetric differences using a relatively new method, tensor-based morphometry. 3D T1-weighted brain MRIs of 24 male children with ASD (age: 9.5 years +/- 3.2 SD) and 26 age-matched healthy controls (age: 10.3 +/- 2.4 SD) were fluidly registered to match a common anatomical template. Autistic children had significantly enlarged frontal lobes (by 3.6% on the left and 5.1% on the right), and all other lobes of the brain were enlarged significantly, or at trend level. By analyzing the applied deformations statistically point-by-point, we detected significant gray matter volume deficits in bilateral parietal, left temporal and left occipital lobes (P = 0.038, corrected), trend-level cerebral white matter volume excesses, and volume deficits in the cerebellar vermis, adjacent to volume excesses in other cerebellar regions. This profile of excesses and deficits in adjacent regions may (1) indicate impaired neuronal connectivity, resulting from aberrant myelination and/or an inflammatory process, and (2) help to understand inconsistent findings of regional brain tissue excesses and deficits in autism.
Pubmed ID: 19554561 RIS Download
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A Java application that allows images to be displayed in three dimensions. The tool allows anatomic structures to be traced and the tracings to be saved in a format that facilitates review and revision. It supports NIfTI-1.1 format float, double and signed and unsigned byte, short, and integer formats and provides legacy support for Analyze 7.5 8 and 16 bit images. It provides image display, editing, delineation of structure boundaries, export of traced contours and generation of masked volumes. Images are displayed in 3 orthogonal views. Time series can be displayed as averaged or contrast images and time courses can be visualized graphically. Version 2 provides enhancements to the original MultiTracer feature set.
View all literature mentionsSuite of image analysis tools designed to process magnetic resonance images (MRI) of the human head. BrainSuite provides an automatic sequence to extract genus-zero cortical surface mesh models from the MRI. It also provides a set of viewing tools for exploring image and surface data. The latest release includes graphical user interface and command line versions of the tools. BrainSuite was specifically designed to guide its users through the process of cortical surface extraction. NITRC has written the software to require minimal user interaction and with the goal of completing the entire process of extracting a topologically spherical cortical surface from a raw MR volume within several minutes on a modern workstation. The individual components of BrainSuite may also be used for soft tissue, skull and scalp segmentation and for surface analysis and visualization. BrainSuite was written in Microsoft Visual C using the Microsoft Foundation Classes for its graphical user interface and the OpenGL library for rendering. BrainSuite runs under the Windows 2000 and Windows XP Professional operating systems. BrainSuite features include: * Sophisticated visualization tools, such as MRI visualization in 3 orthogonal views (either separately or in 3D view), and overlayed surface visualization of cortex, skull, and scalp * Cortical surface extraction, using a multi-stage user friendly approach. * Tools including brain surface extraction, bias field correction, voxel classification, cerebellum removal, and surface generation * Topological correction of cortical surfaces, which uses a graph-based approach to remove topological defects (handles and holes) and ensure a tessellation with spherical topology * Parameterization of generated cortical surfaces, minimizing a harmonic energy functional in the p-norm * Skull and scalp surface extraction
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