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Spatial normalization and segmentation of infant brain MRI data based on adult or pediatric reference data may not be appropriate due to the developmental differences between the infant input data and the reference data. In this study we have constructed infant templates and a priori brain tissue probability maps based on the MR brain image data from 76 infants ranging in age from 9 to 15 months. We employed two processing strategies to construct the infant template and a priori data: one processed with and one without using a priori data in the segmentation step. Using the templates we constructed, comparisons between the adult templates and the new infant templates are presented. Tissue distribution differences are apparent between the infant and adult template, particularly in the gray matter (GM) maps. The infant a priori information classifies brain tissue as GM with higher probability than adult data, at the cost of white matter (WM), which presents with lower probability when compared to adult data. The differences are more pronounced in the frontal regions and in the cingulate gyrus. Similar differences are also observed when the infant data is compared to a pediatric (age 5 to 18) template. The two-pass segmentation approach taken here for infant T1W brain images has provided high quality tissue probability maps for GM, WM, and CSF, in infant brain images. These templates may be used as prior probability distributions for segmentation and normalization; a key to improving the accuracy of these procedures in special populations.
Pubmed ID: 18761410 RIS Download
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Brain imaging data collected from a large population of normal, healthy children that have been used to construct pediatric brain templates, which can be used within statistical parametric mapping for spatial normalization, tissue segmentation and visualization of imaging study results. The data has been processed and compiled in various ways to accommodate a wide range of possible research approaches. The templates are made available free of charge to all interested parties for research purposes only. When processing imaging data from children, it is important to take into account the fact that the pediatric brain differs significantly from the adult brain. Therefore, optimized processing requires appropriate reference data be used because adult reference data will introduce a systematic bias into the results. We have shown that, in the in the case of spatial normalization, the amount of non-linear deformation is dramatically less when a pediatric template is used (left, see also HBM 2002; 17:48-60). We could also show that tissue composition is substantially different between adults and children, and more so the younger the children are (right, see also MRM 2003; 50:749-757). We thus believe that the use of pediatric reference data might be more appropriate.
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