de Almeida Martins João P, Tax Chantal M W, Szczepankiewicz Filip, Jones Derek K, Westin Carl-Fredrik, Topgaard Daniel
Division of Physical Chemistry, Department of Chemistry, Lund University, Lund, Sweden.
Random Walk Imaging AB, Lund, Sweden.
Magn Reson (Gott). 2020 Feb 28;1(1):27-43. doi: 10.5194/mr-1-27-2020. eCollection 2020.
Magnetic resonance imaging (MRI) is the primary method for noninvasive investigations of the human brain in health, disease, and development but yields data that are difficult to interpret whenever the millimeter-scale voxels contain multiple microscopic tissue environments with different chemical and structural properties. We propose a novel MRI framework to quantify the microscopic heterogeneity of the living human brain as spatially resolved five-dimensional relaxation-diffusion distributions by augmenting a conventional diffusion-weighted imaging sequence with signal encoding principles from multidimensional solid-state nuclear magnetic resonance (NMR) spectroscopy, relaxation-diffusion correlation methods from Laplace NMR of porous media, and Monte Carlo data inversion. The high dimensionality of the distribution space allows resolution of multiple microscopic environments within each heterogeneous voxel as well as their individual characterization with novel statistical measures that combine the chemical sensitivity of the relaxation rates with the link between microstructure and the anisotropic diffusivity of tissue water. The proposed framework is demonstrated on a healthy volunteer using both exhaustive and clinically viable acquisition protocols.
磁共振成像（MRI）是对健康、患病和发育中的人类大脑进行无创研究的主要方法，但每当毫米级体素包含具有不同化学和结构特性的多个微观组织环境时，所产生的数据就难以解释。我们提出了一种新颖的MRI框架，通过将传统的扩散加权成像序列与多维固态核磁共振（NMR）光谱的信号编码原理、多孔介质拉普拉斯NMR的弛豫-扩散相关方法以及蒙特卡罗数据反演相结合，将活体人类大脑的微观异质性量化为空间分辨的五维弛豫-扩散分布。分布空间的高维性允许解析每个异质体素内的多个微观环境，以及使用新颖的统计量对它们进行单独表征，这些统计量将弛豫率的化学敏感性与微观结构和组织水的各向异性扩散率之间的联系结合起来。使用详尽的和临床上可行的采集方案，在一名健康志愿者身上展示了所提出的框架。
