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基于磁共振的脑整体 g 比值成像(MWI)和神经丝取向分散和密度成像(NODDI)

Whole brain g-ratio mapping using myelin water imaging (MWI) and neurite orientation dispersion and density imaging (NODDI).

机构信息

Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea.

Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea.

出版信息

Neuroimage. 2018 Nov 15;182:379-388. doi: 10.1016/j.neuroimage.2017.09.053. Epub 2017 Sep 27.

Abstract

MR g-ratio, which measures the ratio of the aggregate volume of axons to that of fibers in a voxel, is a potential biomarker for white matter microstructures. In this study, a new approach for acquiring an in-vivo whole human brain g-ratio map is proposed. To estimate the g-ratio, myelin volume fraction and axonal volume fraction are acquired using multi-echo gradient echo myelin water imaging (GRE-MWI) and neurite orientation dispersion and density imaging (NODDI), respectively. In order to translate myelin water fraction measured in GRE-MWI into myelin volume fraction, a new scaling procedure is proposed and validated. This scaling approach utilizes geometric measures of myelin structure and, therefore, provides robustness over previous methods. The resulting g-ratio map reveals an expected range of g-ratios (0.71-0.85 in major fiber bundles) with a small inter-subject coefficient of variance (less than 2%). Additionally, a few fiber bundles (e.g. cortico-spinal tract and optic radiation) show different constituents of myelin volume fraction and axonal volume fraction, indicating potentials to utilize the measures for deciphering fiber tracking.

摘要

MR g-ratio 是衡量体素中轴突总容积与纤维总容积之比的指标,是一种潜在的白质微观结构生物标志物。本研究提出了一种新的获取活体全脑 g-ratio 图的方法。为了估计 g-ratio,使用多回波梯度回波髓鞘水成像(GRE-MWI)和神经丝取向分散和密度成像(NODDI)分别获取髓鞘体积分数和轴突体积分数。为了将 GRE-MWI 中测量的髓鞘水分数转换为髓鞘体积分数,提出并验证了一种新的标度程序。这种标度方法利用了髓鞘结构的几何测量,因此相对于以前的方法具有更强的鲁棒性。得到的 g-ratio 图显示了预期的 g-ratio 范围(主要纤维束中的 0.71-0.85),个体间的变异系数较小(小于 2%)。此外,一些纤维束(如皮质脊髓束和视辐射)显示出不同的髓鞘体积分数和轴突体积分数组成,表明有可能利用这些测量值来解析纤维追踪。

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