Daily Brain Research: Use automatic fiber beam segmentation to study local white matter abnormalities in Parkinson's disease.

The absence of the white matter (WM) structure is associated with the progression of Parkinson's disease (PD).
most current methods are based on the area of the cortex of interest (ROIS) to identify key WM regions.
However, this type of ROI method may be challenged by the spread of anisotropy near grey matter (GM), which may lead to reduced sensitivity to beam recognition.
this paper, an automatic WM decomposition method to locate abnormal WM in PD is proposed to improve the accuracy of WM beam recognition.
the authors believe that in the beam beam, all equidistant positions along each fiber are beam-like cross-sections.
all points of the beam section are nodes, and the fiber properties of the beam can be represented by vectors, which are marked as contours.
method: (1) data preprocessing, (2) whole-brain beam tracing (3) whole-brain fiber segmentation (4) abnormal fiber removal (5) in the family of interest to calculate fiber characteristics and (6) statistical analysis (1) pre-treatment of artifacts.
(2) performs an all-brain contrast on the basis of each suitable WM voractin, using the UKF-angiography algorithm. The WM cluster map established by
(3) collected 800 clusters of the whole brain fibers of each subject and randomly selected the displayed clusters from a sample of the subjects.
(4) remove seisves (5) of the outlier fibers that deviate significantly from the average position of the beam for statistical testing of the calculated characteristics (6) in each cluster to identify significant difference slots and clusters.
use Pearson to study the relationship between clinical indicators and specific fiber clusters.
result: A method for sensitively identifying abnormal WM beams in PD from the omni-cerebrovascular angiography was proposed.
results are consistent with recent results.
identify the exception regions at the clustering level and comment on these clusters.
finally, the authors found that 13 hemismeclusters and 8 clusters varied significantly in local regions in specific clusters, including multifibre beams (CB, EC, IoFF, SLF, TF, UF, and CC).
also identified two groups related to cognitive function, six groups related to motor function, and two groups related to depression.
original link: Wang, J., et al., TheR of The matter of the local white matterity in Parkinson's disease by the use of an tract tract parcellation. Reebrain Research, 2020. 394: p. 112805.MedSci Original Source: MedSci Original, !-- Content Presentation Ends - !-- Determine Signed-Up Ends.