Abstract
Diffusion tensor imaging (DTI) tractography provides noninvasive measures of structural cortico-cortical connectivity of the brain. However, the agreement between DTI-tractography-based measures and histological ‘ground truth’ has not been quantified. In this study, we reconstructed the 3D density distribution maps (DDM) of fibers labeled with an anatomical tracer, biotinylated dextran amine (BDA), as well as DTI tractography-derived streamlines connecting the primary motor (M1) cortex to other cortical regions in the squirrel monkey brain. We evaluated the agreement in M1-cortical connectivity between the fibers labeled in the brain tissue and DTI streamlines on a regional and voxel-by-voxel basis. We found that DTI tractography is capable of providing inter-regional connectivity comparable to the neuroanatomical connectivity, but is less reliable measuring voxel-to-voxel variations within regions.
Highlights
Diffusion Tensor Imaging (DTI) is a noninvasive method to characterize the microstructure of biological tissue [1]
This paper aims to assess the accuracy of DTI tractography as a measure of cortico-cortical connectivity
The white-gray matter (WGM) boundary was estimated by fitting a series of manually-placed markers on 46 micrographs covering a specific regions of interest (ROIs)
Summary
Diffusion Tensor Imaging (DTI) is a noninvasive method to characterize the microstructure of biological tissue [1] It is based on measurements of the mean squared displacement of water molecules along predetermined directions, estimated from the signal decay in a pulsed gradient spin echo acquisition [2]. Deterministic tracking algorithms [5,6,7,8,9] construct a unique path from each seed point whereas probabilistic algorithms [10,11,12,13,14] generate multiple possible paths from each seed point Both families of tractography algorithms have become valuable research tools for the in vivo study of neuronal tissue morphology, pathway location, and other properties which directly relate to neuropsychiatric/neurologic disorders [15], brain organization and development [16,17]
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