Department of Mathematics, Konkuk University, Neungdong-ro, Gwangjin-gu, Seoul, 05029, Republic of Korea.
Department of Mathematics, Central Michigan University, Mount Pleasant, MI, 48859, USA.
Neuroimage. 2018 Dec;183:836-846. doi: 10.1016/j.neuroimage.2018.08.072. Epub 2018 Sep 5.
Anisotropic diffusion MRI techniques using single-shell or multi-shell acquisitions have been proposed as a means to overcome some limitations imposed by diffusion tensor imaging (DTI), especially in complex models of fibre orientation distribution in voxels. A long acquisition time for the angular resolution of diffusion MRI is a major obstacle to practical clinical implementations. In this paper, we propose a novel method to improve angular resolution of diffusion MRI acquisition using given diffusion gradient (DG) directions. First, we define a local diffusion pattern map of diffusion MR signals on a single shell in given DG directions. Using the local diffusion pattern map, we design a prediction scheme to determine the best DG direction to be synthesized within a nearest neighborhood DG directions group. Second, the local diffusion pattern map and the spherical distance on the shell are combined to determine a synthesized diffusion signal in the new DG direction. Using the synthesized and measured diffusion signals on a single sphere, we estimate a spin orientation distribution function (SDF) with human brain data. Although the proposed method is applied to SDF, a basic idea is to increase the angular resolution using the measured diffusion signals in various DG directions. The method can be applicable to different acquired multi-shell data or diffusion spectroscopic imaging (DSI) data. We validate the proposed method by comparing the recovered SDFs using the angular resolution enhanced diffusion signals with the recovered SDF using the measured diffusion data. The developed method provides an enhanced SDF resolution and improved multiple fiber structure by incorporating synthesized signals. The proposed method was also applied neurite orientation dispersion and density imaging (NODDI) using multi-shell acquisitions.
基于单壳或多壳采集的各向异性扩散 MRI 技术已被提出作为克服扩散张量成像(DTI)限制的方法,尤其是在体素中纤维方向分布的复杂模型中。扩散 MRI 角分辨率的采集时间长是实际临床应用的主要障碍。在本文中,我们提出了一种使用给定扩散梯度(DG)方向来提高扩散 MRI 采集角分辨率的新方法。首先,我们定义了给定 DG 方向上单个壳上扩散 MR 信号的局部扩散模式图。使用局部扩散模式图,我们设计了一个预测方案,以确定在最近邻 DG 方向组内要合成的最佳 DG 方向。其次,将局部扩散模式图和壳上的球距离结合起来,以确定新 DG 方向上的合成扩散信号。使用单个球体上的合成和测量扩散信号,我们使用人脑数据估计了自旋取向分布函数(SDF)。虽然该方法应用于 SDF,但基本思想是使用各种 DG 方向的测量扩散信号来提高角分辨率。该方法可应用于不同采集的多壳数据或扩散光谱成像(DSI)数据。我们通过比较使用增强角分辨率的扩散信号恢复的 SDF 与使用测量扩散数据恢复的 SDF 来验证所提出的方法。所提出的方法通过结合合成信号来提供增强的 SDF 分辨率和改进的多纤维结构。该方法还应用于多壳采集的神经丝取向弥散和密度成像(NODDI)。