Diffusion tensor imaging (DTI) is amongst the simplest mathematical models available for diffusion magnetic resonance imaging, yet still by far the most used one. Despite the success of DTI as an imaging tool for white matter fibers, its anatomical underpinnings on a microstructural basis remain unclear. In this study, we used 65 myelin-stained sections of human premotor cortex to validate modeled fiber orientations and oft used microstructure-sensitive scalar measures of DTI on the level of individual voxels. We performed this validation on high spatial resolution diffusion MRI acquisitions investigating both white and gray matter. We found a very good agreement between DTI and myelin orientations with the majority of voxels showing angular differences less than 10°. The agreement was strongest in white matter, particularly in unidirectional fiber pathways. In gray matter, the agreement was good in the deeper layers highlighting radial fiber directions even at lower fractional anisotropy (FA) compared to white matter. This result has potentially important implications for tractography algorithms applied to high resolution diffusion MRI data if the aim is to move across the gray/white matter boundary. We found strong relationships between myelin microstructure and DTI-based microstructure-sensitive measures. High FA values were linked to high myelin density and a sharply tuned histological orientation profile. Conversely, high values of mean diffusivity (MD) were linked to bimodal or diffuse orientation distributions and low myelin density. At high spatial resolution, DTI-based measures can be highly sensitive to white and gray matter microstructure despite being relatively unspecific to concrete microarchitectural aspects.@en

Very preterm infants, < 32 weeks gestation, are at high risk for brain injury. Cognitive deficits are often diagnosed at a later stage, since there are no available predictive biomarkers in the neonatal period. The maturation of specific white matter (WM) brain structures is considered a promising early-stage biomarker. With Diffusion Tensor Imaging (DTI) tractography, an in vivo and non-invasive evaluation of these anatomical structures is possible. We developed an automatic tractography segmentation pipeline, which allows for maturation assessment of the different segmented WM structures. Our segmentation pipeline is atlas-based, specifically designed for premature neonates at term equivalent age. In order to better make use of global information from tractography, all processing is done in the fiber domain. Segmented fiber bundles are further automatically quantified with respect to volume and anisotropy. Of the 24 automatically segmented neonatal tractographies, only three contained more than 30% mislabeled fibers. Results show no dependency to WM pathology. By automatically segmenting WM, we reduced the user-dependency and bias characteristic of manual methods. This study assesses the structure of the neonatal brain based on an automatic WM segmentation in the fiber domain method using DTI tractography data.@en