Bao Lijun, Xiong Congcong, Wei Wenping, Chen Zhong, van Zijl Peter C M, Li Xu
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China.
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China.
Med Image Anal. 2021 Jan;67:101827. doi: 10.1016/j.media.2020.101827. Epub 2020 Oct 20.
Susceptibility tensor imaging (STI) has been proposed as an alternative to diffusion tensor imaging (DTI) for non-invasive in vivo characterization of brain tissue microstructure and white matter fiber architecture, potentially benefitting from its high spatial resolution. In spite of different biophysical mechanisms, animal studies have demonstrated white matter fiber directions measured using STI to be reasonably consistent with those from diffusion tensor imaging (DTI). However, human brain STI is hampered by its requirement of acquiring data at more than 10 head rotations and a complicated processing pipeline. In this paper, we propose a diffusion-regularized STI method (DRSTI) that employs a tensor spectral decomposition constraint to regularize the STI solution using the fiber directions estimated by DTI as a priori. We then explore the high-resolution DRSTI with MR phase images acquired at only 6 head orientations. Compared to other STI approaches, the DRSTI generated susceptibility tensor components, mean magnetic susceptibility (MMS), magnetic susceptibility anisotropy (MSA) and fiber direction maps with fewer artifacts, especially in regions with large susceptibility variations, and with less erroneous quantifications. In addition, the DRSTI method allows us to distinguish more structural features that could not be identified in DTI, especially in deep gray matters. DRSTI enables a more accurate susceptibility tensor estimation with a reduced number of sampling orientations, and achieves better tracking of fiber pathways than previous STI attempts on in vivo human brain.
敏感性张量成像（STI）已被提议作为扩散张量成像（DTI）的替代方法，用于在体无创表征脑组织微观结构和白质纤维结构，可能受益于其高空间分辨率。尽管生物物理机制不同，但动物研究表明，使用STI测量的白质纤维方向与扩散张量成像（DTI）测量的方向相当一致。然而，人脑STI受到其需要在超过10次头部旋转时采集数据以及复杂处理流程的阻碍。在本文中，我们提出了一种扩散正则化STI方法（DRSTI），该方法采用张量谱分解约束，以DTI估计的纤维方向为先验来正则化STI解。然后，我们利用仅在6个头部方向采集的磁共振相位图像探索高分辨率DRSTI。与其他STI方法相比，DRSTI生成的敏感性张量分量、平均磁化率（MMS）、磁化率各向异性（MSA）和纤维方向图伪影更少，尤其是在磁化率变化较大的区域，且量化误差更小。此外，DRSTI方法使我们能够区分更多在DTI中无法识别的结构特征，尤其是在深部灰质中。DRSTI能够在减少采样方向数量的情况下更准确地估计敏感性张量，并且在体内人脑上比以前的STI尝试实现更好的纤维束追踪。
