title: Abnormalities in MRI traits of corpus callosum in autism subtype.
abstract: A number of studies have documented that autism has a neurobiological basis, but the anatomical extent of these neurobiological abnormalities is largely unknown. In this paper, we apply advanced computational techniques to extract 3D models of the corpus callosum (CC) and subsequently analyze the volumetric deficit of the total CC and its five sub-regions in a homogeneous group of autistic children. Moreover, we explore new MRI traits based on the oriented bounding rectangle of the CC, which are the length, width and aspect ratio of the bounding rectangle. These measurements as well as the volumes are compared between patients and controls using t-tests. The results reveal significant reduction in all sub-regions of the CC and some MRI traits in the patients.
authors.affiliation: Department of Computer Science, University of Missouri-Columbia, MO 65211, USA. qhgb2@mizzou.edu
authors.forename: Qing
authors.initials: Q
authors.lastname: He
authors.forename: Kevin
authors.initials: K
authors.lastname: Karsch
authors.forename: Ye
authors.initials: Y
authors.lastname: Duan
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001321:Autistic Disorder / Q000175:diagnosis* / Q000503:physiopathology*; D001921:Brain / Q000033:anatomy & histology; D001931:Brain Mapping / Q000379:methods*; D002648:Child; D002675:Child, Preschool; D003337:Corpus Callosum / Q000033:anatomy & histology / Q000473:pathology / Q000503:physiopathology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods / Q000706:statistics & numerical data; D008297:Male; D012016:Reference Values