Subcortical Brain Development in Autism and Fragile X Syndrome: Evidence for Dynamic, Age- and Disorder-Specific Trajectories in Infancy.

OBJECTIVE: Previous research has demonstrated that the amygdala is enlarged in children with autism spectrum disorder (ASD). However, the precise onset of this enlargement during infancy, how it relates to later diagnostic behaviors, whether the timing of enlargement in infancy is specific to the amygdala, and whether it is specific to ASD (or present in other neurodevelopmental disorders, such as fragile X syndrome) are all unknown. METHODS: Longitudinal MRIs were acquired at 6-24 months of age in 29 infants with fragile X syndrome, 58 infants at high likelihood for ASD who were later diagnosed with ASD, 212 high-likelihood infants not diagnosed with ASD, and 109 control infants (1,099 total scans). RESULTS: Infants who developed ASD had typically sized amygdala volumes at 6 months, but exhibited significantly faster amygdala growth between 6 and 24 months, such that by 12 months the ASD group had significantly larger amygdala volume (Cohen's d=0.56) compared with all other groups. Amygdala growth rate between 6 and 12 months was significantly associated with greater social deficits at 24 months when the infants were diagnosed with ASD. Infants with fragile X syndrome had a persistent and significantly enlarged caudate volume at all ages between 6 and 24 months (d=2.12), compared with all other groups, which was significantly associated with greater repetitive behaviors. CONCLUSIONS: This is the first MRI study comparing fragile X syndrome and ASD in infancy, demonstrating strikingly different patterns of brain and behavior development. Fragile X syndrome-related changes were present from 6 months of age, whereas ASD-related changes unfolded over the first 2 years of life, starting with no detectable group differences at 6 months. Increased amygdala growth rate between 6 and 12 months occurs prior to social deficits and well before diagnosis. This gradual onset of brain and behavior changes in ASD, but not fragile X syndrome, suggests an age- and disorder-specific pattern of cascading brain changes preceding autism diagnosis.

Adaptive prior probability and spatial temporal intensity change estimation for segmentation of the one-year-old human brain.

The degree of white matter (WM) myelination is rather inhomogeneous across the brain. White matter appears differently across the cortical lobes in MR images acquired during early postnatal development. Specifically at 1-year of age, the gray/white matter contrast of MR T1 and T2 weighted images in prefrontal and temporal lobes is reduced as compared to the rest of the brain, and thus, tissue segmentation results commonly show lower accuracy in these lobes. In this novel work, we propose the use of spatial intensity growth maps (IGM) for T1 and T2 weighted images to compensate for local appearance inhomogeneity. The IGM captures expected intensity changes from 1 to 2 years of age, as appearance homogeneity is greatly improved by the age of 24 months. The IGM was computed as the coefficient of a voxel-wise linear regression model between corresponding intensities at 1 and 2 years. The proposed IGM method revealed low regression values of 1-10% in GM and CSF regions, as well as in WM regions at maturation stage of myelination at 1 year. However, in the prefrontal and temporal lobes we observed regression values of 20-25%, indicating that the IGM appropriately captures the expected large intensity change in these lobes mainly due to myelination. The IGM is applied to cross-sectional MRI datasets of 1-year-old subjects via registration, correction and tissue segmentation of the IGM-corrected dataset. We validated our approach in a small leave-one-out study of images with known, manual 'ground truth' segmentations.

Asymmetric bias in user guided segmentations of brain structures.

Brain morphometric studies often incorporate comparative hemispheric asymmetry analyses of segmented brain structures. In this work, we present evidence that common user guided structural segmentation techniques exhibit strong left-right asymmetric biases and thus fundamentally influence any left-right asymmetry analyses. In this study, MRI scans from ten pediatric subjects were employed for studying segmentations of amygdala, globus pallidus, putamen, caudate, and lateral ventricle. Additionally, two pediatric and three adult scans were used for studying hippocampus segmentation. Segmentations of the sub-cortical structures were performed by skilled raters using standard manual and semi-automated methods. The left-right mirrored versions of each image were included in the data and segmented in a random order to assess potential left-right asymmetric bias. Using shape analysis we further assessed whether the asymmetric bias is consistent across subjects and raters with the focus on the hippocampus. The user guided segmentation techniques on the sub-cortical structures exhibited left-right asymmetric volume bias with the hippocampus displaying the most significant asymmetry values (p<<0.01). The hippocampal shape analysis revealed the bias to be strongest on the lateral side of the body and medial side of the head and tail. The origin of this asymmetric bias is considered to be based in laterality of visual perception; therefore segmentations with any degree of user interaction contain an asymmetric bias. The aim of our study is to raise awareness in the neuroimaging community regarding the presence of the asymmetric bias and its influence on any left-right hemispheric analyses. We also recommend reexamining previous research results in the light of this new finding.