High-angular resolution diffusion MRI for identifying br

用于识别 br 的高角分辨率扩散 MRI

• 批准号: 6828414
• 负责人: Yihong Yang
• 金额: --
• 依托单位: NATIONAL INSTITUTE ON DRUG ABUSE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6828414
• 关键词: bioimaging /biomedical imaging; brain imaging /visualization /scanning; clinical research; corpus callosums; human subject; magnetic resonance imaging; medulla oblongata; method development; noninvasive diagnosis; pons

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.

扩散张量成像（DTI）已显示出作为一种无创工具来研究大脑结构的前景。作为DTI的一种应用，“纤维追踪”技术已被证明具有描绘脑中神经元通路和神经系统疾病中的连接（及其中断）的潜力。然而，现有的DTI和纤维跟踪技术存在挑战，例如由纤维交叉引起的问题，其中多个纤维室共存于图像体素中。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接。一个超越传统DTI的扩散模型，并能够提供更多的体素内信息是必不可少的，以克服这个问题。 我们已经开发了一种新的方法来映射的白色物质，特别是纤维交叉，使用圆谱分解的基础上的高角分辨率测量的表观扩散系数（ADC）的体素内结构。我们的方法的基本前提是确定ADC值的扩散张量的主要和中值特征向量所跨越的单位圆上的voxelwise，然后应用1D傅立叶变换到这个圆上。圆谱的0阶、2阶和4阶谐波分量分别为平均扩散率、线性纤维和正交纤维交叉扩散提供有效指标。建立了扩散成像新技术的理论框架。在数字体模上的模拟证明了该技术识别纤维交叉点的有效性。对正常受试者的体内实验表明，在许多脑区，包括脑桥，髓质和胼胝体周围的区域，可以观察到高四阶成分（纤维交叉）。这项新技术为绘制大脑内部的纤维交叉点提供了一种创新工具。从这项技术中获得的信息将用于改善纤维跟踪技术，并更好地描绘正常和病理条件下的神经通路。