Investig Magn Reson Imaging.  2022 Dec;26(4):265-274. 10.13104/imri.2022.26.4.265.

Improving Delineation of the Corticospinal Tract in the Monkey Brain Scanned With Conventional Diffusion Tensor Imaging by Using a Compressed Sensing Based Algorithm

• Meng Y
• Li CX
• Zhang X

• KMID: 2538313
• DOI: http://doi.org/10.13104/imri.2022.26.4.265

Abstract

Purpose
The corticospinal tract (CST) is a major tract for motor function. It can be impaired by stroke. Its degeneration is associated with stroke outcome. Diffusion tensor imaging (DTI) tractography plays an important role in assessing fiber bundle integrity. However, it is limited in detecting crossing fibers in the brain. The crossing fiber angular resolution of intra-voxel structure (CFARI) algorithm shows potential to resolve complex fibers in the brain. The objective of the present study was to improve delineation of CST pathways in monkey brains scanned by conventional DTI.
Materials and Methods
Healthy rhesus monkeys were scanned by diffusion MRI with 128 diffusion encoding directions to evaluate the CFARI algorithm. Four monkeys with ischemic occlusion were also scanned with DTI (b = 1000 s/mm², 30 diffusion directions) at 6, 48, and 96 hours poststroke. CST fibers were reconstructed with DTI and CFARI-based tractography and evaluated. A two-way repeated multivariate analysis of covariance was used to determine significances of changes in DTI indices, tract number, and volumes of the CST between hemispheres or poststroke time points.
Results
CFARI algorithm revealed substantially more fibers originated from the ventral premotor cortex in healthy and stroke monkey brains than conventional DTI tractography. In addition, CFARI improved sensitivity in detecting CST abnormality compared to DTI tractography following stroke.
Conclusion
CFARI significantly improved delineation of the CST in the brain scanned by DTI with 30 gradient directions. It showed better sensitivity in detecting abnormity of the CST following stroke. Preliminary results suggest that CFARI could facilitate prediction of function outcomes after stroke.

Keyword

Diffusion tensor imaging; Nonhuman primate; Fiber tracking; CFARI; Compressed sensing; Stroke