Imaging studies of early brain development get increasing attention as improved modeling of the pattern of normal development might lead to a better understanding of origin, timing and nature of morphologic differences in neurodevelopmental disorders. A main goal is the modeling of the trajectory of early brain development using structural MRI and diffusion tensor imaging (DTI) and statistical analysis of growth trajectory differences in psychiatric disorders. Studying this age group involves two major challenges, successful MRI scanning of non-sedated infants and image analysis methods designed to describe the trajectory of early growth. The talk will discuss work in progress towards longitudinal modeling of early brain growth via structural MRI and DTI but will also highlight open issues and the need for advanced image analysis concepts. Key components are the building of cross-sectional unbiased atlases per age group and its extension to spatio-temporal 4-D longitudinal atlases. A framework for population-based statistical analysis of diffusion properties of fiber tracts of interest parameterized by arc-length will be presented. Joint modeling of DTI and multi-contrast MRI reveals the importance of a statistical framework for multi-variate analysis to fully capture the pattern of early structuring of brain tissue and changes due to pathology.
Preliminary results from clinical longitudinal neuroimaging studies (infants at risk for mental illness, autism study) conducted at UNC will be shown. New analytic methods show excellent potential to contribute to a better understanding of origin, timing and nature of morphologic differences in neurodevelopmental disorders.
Audio (MP3 File, Podcast Ready)
Copyright. All Rights Reserved.