High-angular resolution diffusion MRI for identifying br

弥散张量成像(DTI)作为一种非侵入性的研究脑结构的工具显示出了良好的前景。作为DTI的一种应用，“纤维跟踪”技术已被证明具有描绘大脑中的神经元路径和神经疾病中的连接(及其中断)的潜力。然而，现有的DTI和纤维跟踪技术存在一些挑战，如纤维交叉造成的问题，即多个纤维间隔共存于一个图像体素中。在这种情况下，张量分量的估计可能会严重偏差，从而阻止光纤跟踪算法跟踪附近的实际光纤连通性。为了克服这一问题，一个超越传统DTI的扩散模型是必不可少的，它能够提供更多的体素内信息。 我们开发了一种新的方法来绘制白质的体素内结构，特别是纤维交叉点，使用基于高角分辨率的表观扩散系数(ADC)的圆谱分解。该方法的基本前提是确定扩散张量的主特征向量和中值特征向量所跨越的单位圆上的体素ADC值，然后对该圆进行一维傅立叶变换。圆谱的0、2、4阶谐分量分别提供了平均扩散系数、线性光纤和正交光纤交叉扩散的有效指标。为新的扩散成像技术建立了理论框架。在数字体模上的模拟验证了该技术识别纤维交叉口的有效性。对正常受试者的活体实验表明，高四级成分(纤维交叉)可以在许多大脑区域观察到，包括脑桥、延髓和胼胝体周围区域。这项新技术为绘制大脑内的纤维交叉提供了一种创新的工具。从这项技术中获得的信息将被用于改进纤维跟踪技术，并在正常和病理条件下更好地描绘神经元路径。

Diffusion tensor imaging (DTI) has shown promise as a noninvasive tool to investigate brain structures. As an application of DTI, "fiber tracking" techniques have been demonstrated to have the potential to delineate neuronal pathways in the brain and connectivity (and its disruption) in neurological disorders. However, there are challenges in existing DTI and fiber-tracking techniques, such as the problem caused by fiber crossing, in which multiple fiber compartments coexist in an image voxel. In this case, the estimation of the tensor components can be seriously biased, preventing fiber-tracking algorithms from following the actual fiber connectivity in the vicinity. A diffusion model beyond conventional DTI and capable of providing more intravoxel information is essential to overcome this problem. We have developed a new method to map intravoxel structures of white matter, especially fiber crossings, using circular spectrum decomposition based on high-angular resolution measurements of apparent diffusion coefficients (ADC). The basic premise of our method is to determine the ADC values voxelwise on the unit circle spanned by the major and median eigenvectors of the diffusion tensor, and then apply a 1D Fourier-transform onto this circle. The 0th, 2nd, and 4th order harmonic components of the circular spectrum provide effective indices for mean diffusivity, linear fiber, and orthogonal fiber crossing diffusion respectively. A theoretical frame work has been established for the novel diffusion imaging technique. Simulations on a digital phantom demonstrated the effectiveness of the technique to identify fiber intersections. In vivo experiments on normal subjects showed that high 4th-order components (fiber crossings) can be observed in a number of brain regions, including pons, medulla, and areas around corpus callosum. This new technique provides an innovative tool for mapping fiber crossings inside the brain. Information obtained from this technique would be used for improving fiber-tracking techniques and for better delineating neuronal pathways under normal and pathological conditions.