Department of Neuroimaging, King's College London, Institute of Psychiatry, United Kingdom; NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, King's College London, United Kingdom.
Hum Brain Mapp. 2013 Oct;34(10):2464-83. doi: 10.1002/hbm.22080. Epub 2012 Apr 5.
Diffusion tensor imaging (DTI) methods are widely used to reconstruct white matter trajectories and to quantify tissue changes using the average diffusion properties of each brain voxel. Spherical deconvolution (SD) methods have been developed to overcome the limitations of the diffusion tensor model in resolving crossing fibers and to improve tractography reconstructions. However, the use of SD methods to obtain quantitative indices of white matter integrity has not been extensively explored. In this study, we show that the hindrance modulated orientational anisotropy (HMOA) index, defined as the absolute amplitude of each lobe of the fiber orientation distribution, can be used as a compact measure to characterize the diffusion properties along each fiber orientation in white matter regions with complex organization. We demonstrate that the HMOA is highly sensitive to changes in fiber diffusivity (e.g., myelination processes or axonal loss) and to differences in the microstructural organization of white matter like axonal diameter and fiber dispersion. Using simulations to describe diffusivity changes observed in normal brain development and disorders, we observed that the HMOA is able to identify white matter changes that are not detectable with conventional DTI indices. We also show that the HMOA index can be used as an effective threshold for in vivo data to improve tractography reconstructions and to better map white matter complexity inside the brain. In conclusion, the HMOA represents a true tract-specific and sensitive index and provides a compact characterization of white matter diffusion properties with potential for widespread application in normal and clinical populations.
弥散张量成像（DTI）方法广泛用于重建白质轨迹，并使用每个脑体素的平均扩散特性来量化组织变化。球分解（SD）方法已经被开发出来，以克服扩散张量模型在解析交叉纤维方面的局限性，并改善轨迹重建。然而，SD 方法在获得白质完整性的定量指标方面的应用尚未得到广泛探索。在这项研究中，我们表明，作为一种紧凑的测量方法，可以使用作为纤维方向分布的每个叶的绝对值定义的阻碍调制各向异性（HMOA）指数来表征白质区域中沿每个纤维方向的扩散特性，该白质区域具有复杂的组织。我们证明 HMOA 对纤维扩散性的变化（例如，髓鞘形成过程或轴突损失）高度敏感，并且对像轴突直径和纤维分散这样的白质微观结构组织的差异也很敏感。使用模拟来描述正常大脑发育和疾病中观察到的扩散率变化，我们观察到 HMOA 能够识别用常规 DTI 指数无法检测到的白质变化。我们还表明，HMOA 指数可作为体内数据的有效阈值，以改善轨迹重建并更好地映射大脑内白质的复杂性。总之，HMOA 代表一种真正的束特异性和敏感指数，并为白质扩散特性提供了紧凑的特征描述，具有在正常和临床人群中广泛应用的潜力。
