Diffusion Tensor Based White Matter Tract Atlases for Pediatric Populations

Abstract

Diffusion Tensor Imaging (DTI) is a non-invasive neuroimaging method that has become the most widely employed MRI modality for investigations of white matter fiber pathways. DTI has proven especially valuable for improving our understanding of normative white matter maturation across the life span and has also been used to index clinical pathology and cognitive function. Despite its increasing popularity, especially in pediatric research, the majority of existing studies examining infant white matter maturation depend on regional or white matter skeleton-based approaches. These methods generally lack the sensitivity and spatial specificity of more advanced functional analysis options that provide information about microstructural properties of white matter along fiber bundles. DTI studies of early postnatal brain development show that profound microstructural and maturational changes take place during the first two years of life. The pattern and rate of these changes vary greatly throughout the brain during this time compared to the rest of the life span. For this reason, appropriate image processing of infant MR imaging requires the use of age-specific reference atlases. This article provides an overview of the pre-processing, atlas building, and the fiber tractography procedures used to generate two atlas resources, one for neonates and one for 1- to 2-year-old populations. Via the UNC-NAMIC DTI Fiber Analysis Framework, our pediatric atlases provide the computational templates necessary for the fully automatic analysis of infant DTI data. To the best of our knowledge, these atlases are the first comprehensive population diffusion fiber atlases in early pediatric ages that are publicly available.

Keywords: DTI; MRI; computational atlas; infant; neuroimaging; pediatric; white matter tracts.

FIGURE 1

A summarized overview of the UNC Utah NAMIC framework. The figure outlines the framework from quality control steps to statistical analysis of white matter tracts.

FIGURE 2

Commonly observed diffusion MRI artifacts, particularly in infant scans. Our diffusion MRI preprocessing with DTIPrep removes all these artifacts, indicated with arrows, from the scans prior to further processing.

FIGURE 3

itk-SNAP allows users to visualize brain masks as a binary label image overlaying the b0 or FA image to perform manual editing. The main purpose of this step is to remove parts of the brain mask that cover any noisy, high-intensity voxels near the skull.

FIGURE 4

3D Slicer enables users to clean initial fiber bundles Via tract selection and editing modules. Additionally, it provides an interactive 3D viewing experience, which aids users to quality control white matter tracts that are being manually edited.

FIGURE 5

FiberViewerLight’s Cutter tool is useful when cropping certain regions of white matter tracts. We used this tool to crop the regions of the fornix that were determined to be artifactual streamlines.

FIGURE 6

White matter tracts of the neonatal atlas. (Left top and bottom) Corpus callosum (CC); orbital frontal cortex (OFC); prefrontal cortex (PFC); premotor cortex (PMC); motor cortex (MC); parietal cortex (PC); occipital cortex (OC); tapetum (TC). (Top right) Blue = Inferior frontooccipital fasciculus (IFOF), purple = Cingulum superior part (CGC), yellow = Uncinate fasciculus (UNC), red = Fornix (Fx), green = Inferior longitudinal fascicles (ILF). (Bottom right) Green = Superior longitudinal fasciculus II (SLF), yellow = Arcuate fasciculus frontoparietal (AF-fp), red = Arcuate fasciculus temporoparietal (AF-tp), blue = Arcuate fasciculus frontotemporal (AF-ft). The underlying visualization image is a 3D volume rendering of the atlas FA map.

FIGURE 7

White matter tracts of the pediatric atlas. (Left top and bottom) Corpus callosum (CC); orbital frontal cortex (OFC); prefrontal cortex (PFC); premotor cortex (PMC); motor cortex (MC); parietal cortex (PC); occipital cortex (OC); tapetum (TC). (Top right) Blue = Inferior frontooccipital fasciculus (IFOF), purple = Cingulum superior part (CGC), yellow = Uncinate fasciculus (UNC), red = Fornix (Fx), green = Inferior longitudinal fascicles (ILF). (Bottom right) Green = Superior longitudinal fasciculus II (SLF), yellow = Arcuate fasciculus frontoparietal (AF-fp), red = Arcuate fasciculus temporoparietal (AF-tp), blue = Arcuate fasciculus frontotemporal (AF-ft). The underlying visualization image is a 3D volume rendering of the atlas FA map.

FIGURE 8

Comparing the EBDS neonatal and pediatric atlases. The images are the color-encoded orientation FA maps in axial, sagittal, and coronal slices. The top images are the neonatal atlas, and the bottom images are the pediatric atlas. From the sagittal view, we can observe that the cingulum (CGC) has higher FA due to the greater degree of myelination in the pediatric atlas. Furthermore, given the significantly lower SNR in the neonate DTI, its atlas appears less sharp than the pediatric DTI atlas. Spheres next to the axial view of atlases represent color coding for directional information.

FIGURE 9

A 3D model of white matter tracts that were generated from the EBDS pediatric atlas for educational use.