Use of the Slicer3 Toolkit to Produce Regional Cortical Thickness Measurement of Pediatric MRI Data

Background: The data analysis of neuroimaging data from pediatric populations presents several challenges.  There are normal variations in brain shape from infancy to adulthood and normal developmental changes related to tissue maturation (i.e., myelination of white matter) that create problems in the direct application of tools designed for adult brain. 

Objectives: Our team has created a computer processing tool to produce regional cortical thickness maps appropriate for pediatric MRI data, and is developing a similar pipeline to perform local cortical thickness measures.  This application has been integrated into the Slicer3 toolkit.  Slicer3 is a cross-platform application for analyzing and visualizing medical images.   It is an open source application and is funded by a number of large-scale NIH supported efforts, including the National Alliance for Medical Image Computing (NA-MIC). 

Methods: We have used a pediatric dataset containing 90 cases of 2-4 year olds with typical development, autism, and developmental delay.  This data was input into our regional cortical thickness pipeline, which involves input from T1-weighted MRI data, and produces tissue segmentation, followed by regional atlas deformable registration, to
compute a lobar cortical thickness for each case.

Results: Validation tests of this tool have been computed on a small dataset of 20 2-4 year old scans.

Conclusions: The Slicer3 toolkit provides an accessible and versatile platform to conduct image processing of pediatric MRI data, in this case, regional cortical thickness data.