Meng Yuguang, Li Chun-Xia, Zhang Xiaodong
EPC Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, GA, 30329.
Division of Neurological Neuropharmacology and Neurologic Diseases, Emory National Primate Research Center, Emory University, Atlanta, GA, 30329.
Investig Magn Reson Imaging. 2022 Dec;26(4):265-274. doi: 10.13104/imri.2022.26.4.265. Epub 2022 Dec 31.
BACKGROUND: 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. 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/mm, 30 diffusion directions) at 6, 48, and 96 hours post stroke. CST fibers were reconstructed with DTI and CFARI-based tractography and evaluated. A two-way repeated MANOVA was used to determine significances of changes in DTI indices, tract number, and volumes of the CST between hemispheres or post-stroke time points. RESULTS: CFARI algorithm revealed substantially more fibers originated from the ventral premotor cortex in healthy and stroke monkey brains than DTI tractography. In addition, CFARI showed better sensitivity in detecting CST abnormality than 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.
背景:皮质脊髓束(CST)是运动功能的主要传导束。它可能因中风而受损。其退变与中风预后相关。扩散张量成像(DTI)纤维束成像在评估纤维束完整性方面发挥着重要作用。然而,它在检测大脑中的交叉纤维方面存在局限性。体素内结构交叉纤维角分辨率(CFARI)算法显示出解析大脑中复杂纤维的潜力。本研究的目的是改善在传统DTI扫描的猴脑中CST通路的描绘。 方法:对健康恒河猴进行具有128个扩散编码方向的扩散MRI扫描,以评估CFARI算法。还对4只缺血性闭塞的猴子在中风后6小时、48小时和96小时进行DTI(b = 1000 s/mm²,30个扩散方向)扫描。用DTI和基于CFARI的纤维束成像重建CST纤维并进行评估。采用双向重复多变量方差分析来确定半球间或中风后时间点之间DTI指数、纤维束数量和CST体积变化的显著性。 结果:与DTI纤维束成像相比,CFARI算法在健康和中风猴脑中显示出更多起源于腹侧运动前皮层的纤维。此外,在中风后,CFARI在检测CST异常方面比DTI纤维束成像具有更高的灵敏度。 结论:CFARI显著改善了在具有30个梯度方向的DTI扫描的大脑中CST的描绘。它在检测中风后CST异常方面显示出更高的灵敏度。初步结果表明,CFARI有助于预测中风后的功能结局。
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