International Meeting for Autism Research: An Examination of Brain Size in Infants at High Risk for Autism: Preliminary Findings From the Infant Brain Imaging Study

An Examination of Brain Size in Infants at High Risk for Autism: Preliminary Findings From the Infant Brain Imaging Study

Saturday, May 22, 2010: 10:00 AM
Grand Ballroom E Level 5 (Philadelphia Marriott Downtown)
9:45 AM
H. C. Hazlett , Psychiatry, University of NC, Chapel Hill, NC
K. Botteron , Psychiatry and Radiology, Washington University, St. Louis, MO
H. Gu , Psychiatry, University of North Carolina, Chapel Hill, NC
R. McKinstry , Radiology, Washington University in St. Louis, St. Louis, MO
S. Paterson , Center for Autism Research, University of Pennsylvania and Children's Hosptial of Philadelphia, Philadelphia, PA
M. Styner , Psychiatry, Computer Science, UNC, Chapel Hill, NC
J. Piven , Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC

The Infant Brain Imaging Study (IBIS) Network is an NIH funded Autism Center of Excellence and consists of a consortium of 7 universities in the U.S. and Canada.  The IBIS study involves the national recruitment of infants at high-risk for autism (based on having an older sibling diagnosed with autism) and a control group of typically-developing infants.  Infants are assessed longitudinally at ages 6, 12 and 24 months.  Measures include MRI and DTI scans in addition to a battery of behavioral and developmental tests.  This longitudinal study is currently ongoing, but we are reporting on preliminary findings from the cross-sectional data obtained on 100 high-risk infants at age 6 months.


Brain enlargement has been observed in individuals with autism as early as age 2.  Studies of head size using head circumference measurements suggest that the period of brain enlargement is a postnatal event and may occur between 6-12 months of age.  In this report, we examined the cross-sectional data from 6 month olds at high risk for autism and typically-developing controls participating in the longitudinal study. 


Four clinical sites participated in the data collection:  University of North Carolina, Washington University, Children’s Hospital of Philadelphia, and the University of Washington.  All the brain MRI scans were completed on a 3T Siemens scanner during natural sleep.  Measures of brain volumes were obtained using an automated atlas-based pipeline for the tissue segmentation (ITK-EMS, AutoSeg) and/or semi-automated image processing tools (ITK-SNAP, HeadCirc). 


Group based comparisons for the high-risk infants compared to controls were completed for the selected brain volumes.  Brain volumes examined include intracranial volume (ICV), total brain volume (TBV), cerebrum, cerebellum, cortical lobe volumes, lateral ventricles, and head circumference.  Statistical analyses included important covariates such as gender, site, body size, and age at scan.  We are currently completing the planned statistical analyses for the 6 month dataset, and are unable to include our findings in this abstract.  However, these analyses will be completed well before the conference.  


The results from this preliminary cross-sectional analysis will provide new information regarding early brain size in infants at high-risk for autism.  This study represents the largest known examination of brain volume in an at-risk population. 

*IBIS Network:  The IBIS (Infant Brain Imaging Study) Network is an NIH funded Autism Center of Excellence (HDO55741) and consists of a consortium of 7 Universities in the U.S. and Canada.   Clinical Sites: University of North Carolina: J. Piven (IBIS Network PI), H.C. Hazlett, C. Chappell;  University of Washington: S. Dager, A. Estes; Washington University: K. Botteron, R. McKinstry, J. Contstantino, L. Flake ; Children’s Hospital of Philadelphia:  R. Schultz, S. Paterson; University of Alberta: L. Zwaigenbaum.  Data Coordinating CenterMontreal Neurological Institute: A. Evans, L. Collins, B. Pike, R. Aleong, S. Das.  Image Processing Core:  University of Utah: G. Gerig; University of North Carolina: M. Styner.  Statistical Analysis CoreUniversity of North Carolina: H. Gu.  Genetics Analysis CoreUniversity of North Carolina: P. Sullivan, F. Wright.

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