High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity

Abstract

Magnetic resonance (MR) diffusion tensor imaging (DTI) can resolve the white matter fiber orientation within a voxel provided that the fibers are strongly aligned. However, a given voxel may contain a distribution of fiber orientations due to, for example, intravoxel fiber crossing. The present study sought to test whether a geodesic, high b-value diffusion gradient sampling scheme could resolve multiple fiber orientations within a single voxel. In regions of fiber crossing the diffusion signal exhibited multiple local maxima/minima as a function of diffusion gradient orientation, indicating the presence of multiple intravoxel fiber orientations. The multimodality of the observed diffusion signal precluded the standard tensor reconstruction, so instead the diffusion signal was modeled as arising from a discrete mixture of Gaussian diffusion processes in slow exchange, and the underlying mixture of tensors was solved for using a gradient descent scheme. The multitensor reconstruction resolved multiple intravoxel fiber populations corresponding to known fiber anatomy.Magn Key words: diffusion; diffusion-weighted MRI (DWI); diffusion tensor imaging (DTI); white matter; tractographyTissues with regularly ordered microstructure, such as skeletal muscle, spine, tongue, heart, and cerebral white matter, exhibit anisotropic water diffusion due to the alignment of the diffusion compartments in the tissue (1-7). The direction of preferred diffusion, and hence the direction of preferred orientation in the tissue, can be resolved with a method called magnetic resonance (MR) diffusion tensor imaging (DTI) (7), which measures the apparent water self-diffusion tensor under the assumption of Gaussian diffusion. Based on the eigenstructure of the measured diffusion tensor, it is possible to infer the orientation of the diffusion compartments within the voxel so that, for example, the major eigenvector of the diffusion tensor parallels the mean fiber orientation (7), and the minor eigenvector parallels the normal to the mean plane of fiber dispersion (8).The tensor model is incapable, however, of resolving multiple fiber orientations within an individual voxel. This shortcoming of the tensor model stems from the fact that the tensor possesses only a single orientational maximum, i.e., the major eigenvalue of the diffusion tensor (9,10). At the millimeter-scale resolution typical of DTI, the volume of cerebral white matter containing such intravoxel orientational heterogeneity (IVOH) may be considerable given the widespread divergence and convergence of fascicles (11-13). The abundance of IVOH at the millimeter scale can be further appreciated by considering the ubiquity of oblate (pancake-shaped) diffusion tensors in DTI, a hypothesized indicator of IVOH (3,4,8).Given the obstacle that IVOH (particularly fiber crossing (14 -16)) poses to white matter tractography algorithms (14 -20), we sought to determine whether high angular resolution, high b-value diffusion gradient sampling could resolve such intravoxel heterogeneity (9). H...

MR connectomics: Principles and challenges

“…Diffusion Tensor Imaging and tractography was born. However relatively quickly people realized that major tract reconstruction artifacts were difficult to overcome (Tuch et al, 2002;Wiegell et al, 2000). These were related to the fact that DTI was unable to resolve multiple fiber bundle orientation inside an imaging voxel, and these crossing configurations appeared to be ubiquitous in the brain .…”

“…Therefore most connectional studies up to now have been conducted with DTI schemes despite its recognized limitations. Somewhat in-between solutions, known as single-shell High Angular Resolution Diffusion Imaging (HARDI) techniques became quite popular since through some assumptions they were able to overcome the "fiber-crossing problem" without having to compromise to much scan time and without major hardware requirements (Jansons and Alexander, 2003;Seunarine and Alexander, 2009;Tournier et al, 2004;Tuch et al, 2002Tuch et al, , 2003. In our experience, there is a steady increase in performance from DTI to HARDI techniques and finally DSI when performed with the appropriate hardware, pulse sequence and post-processing (Gigandet, 2009;Wedeen et al, 2008), but this is not a broadly accepted fact.…”

High‐angular resolution diffusion imaging tractography of cerebellar pathways from newborns to young adults

“…High‐angular resolution diffusion MR imaging (HARDI) tractography enables identification of complex crossing tissue coherence in the brain (Tuch et al., 2002), even in immature fetal brains (Takahashi, Folkerth, Galaburda, & Grant, 2012; Takahashi et al., 2011), which are typically more challenging to segment due to a surplus of unmyelinated fibers. This technique theoretically provides an advantage over traditional diffusion tensor imaging (DTI) in the study of intertwined and crossing fiber tracts (Frank, 2002; Tournier, Calamante, & Connelly, 2007; Tournier, Calamante, Gadian, & Connelly, 2004) which are common among cerebellar peduncular tracts.…”

“…In this work, we study the cerebellar peduncle pathways in a population of pediatric and young adult subject, with normal brain MRI reports, using high‐angular resolution diffusion imaging (HARDI) (Tournier et al., 2008; Tuch et al., 2002). Our aim is to improve the knowledge of development of these pathways and to create an initial framework for future studies of normal and pathologic development of these tracts.…”

Topographic separation of fornical fibers associated with the anterior and posterior hippocampus in the human brain: An MRI‐diffusion study

“…This study, therefore, employed the damped Richardson‐Lucy algorithm (Dell'acqua et al., 2010) for deterministic tractography on high angular resolution diffusion imaging data (HARDI) (Tuch et al., 2002) to visualize those axons linked, respectively, to the anterior hippocampus and to the posterior hippocampus. The extent of overlap between the reconstructions was then determined quantitatively.…”