Abstract
Characterization of anisotropy via diffusion MRI reveals fiber crossings in a substantial portion of voxels within the white-matter (WM) regions of the human brain. A considerable number of such voxels could exhibit asymmetric features such as bends and junctions. However, widely employed reconstruction methods yield symmetric Orientation Distribution Functions (ODFs) even when the underlying geometry is asymmetric. In this paper, we employ inter-voxel directional filtering approaches through a cone model to reveal more information regarding the cytoarchitectural organization within the voxel. The cone model facilitates a sharpening of the ODFs in some directions while suppressing peaks in other directions, thus yielding an Asymmetric ODF (AODF) field. We also show that a scalar measure of AODF asymmetry can be employed to obtain new contrast within the human brain. The feasibility of the technique is demonstrated on in vivo data obtained from the MGH-USC Human Connectome Project (HCP) and Parkinson's Progression Markers Initiative (PPMI) Project database. Characterizing asymmetry in neural tissue cytoarchitecture could be important for localizing and quantitatively assessing specific neuronal pathways.
| Original language | English |
|---|---|
| Pages (from-to) | 145-158 |
| Number of pages | 14 |
| Journal | Magnetic Resonance Imaging |
| Volume | 49 |
| DOIs | |
| Publication status | Published - Jun 2018 |
Bibliographical note
Publisher Copyright:© 2018 Elsevier Inc.
Funding
HARDI data are obtained from two datasets: MGH-USC Human Connectome Project (HCP) ( https://ida.loni.usc.edu/login.jsp ) 1 1 Data were provided [in part] by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. and Parkinson's Progression Markers Initiative (PPMI) Project database ( http://www.ppmi-info.org ). HCP data are acquired from 288 gradient directions with 1.25 × 1.25 × 1.25 mm 3 voxel size whereas PPMI data are acquired from 64 gradient directions with 1.98 × 1.98 × 2 mm 3 voxel size. The ODF field for both data are created by the DOT method [7] . As a preprocessing operation, we inserted a sigmoid function on the ODF field to enhance very high components and suppress very low components, which are likely to be due to noise. To focus on fiber pathways that exhibit high curvature, we selected the corpus callosum (CC) and uncinate fasciculus (UF). It is well known that non-invasive extraction of the visual pathways including CC and UF through Diffusion MRI is challenging due to the strong bending, crossing and kissing geometric patterns in the relevant anatomy. For the MRI data experiments, AODFs reconstructed by the steerable filter-based ODF regularization are utilized. In the proposed method, the radius parameter of the cone intuitively corresponds to the radius or thickness of the fiber bundles of interest. The parameters for r and h are selected as 4 mm depending on the average anatomical thickness of the bundles CC and UF [ 39 , 40 ]. shows the reconstructed AODFs for both the HCP and PPMI HARDI data for the CC fiber bundle. Fig. 14 3.3
| Funders | Funder number |
|---|---|
| NIH Institutes | |
| WU-Minn Consortium | 1U54MH091657 |
| NIH Blueprint for Neuroscience Research | |
| McDonnell Center for Systems Neuroscience |
Keywords
- Asymmetric fiber orientations
- Asymmetric ODF (AODF)
- Diffusion MRI
- Directional spatial filtering
- Fiber asymmetry measure
- HARDI
- ODF regularization
- Steerable filtering