Software for the Analysis and Visualization of High Angular Resolution DTI Data

用于高角分辨率 DTI 数据分析和可视化的软件

• 批准号: 7123677
• 负责人: LAWRENCE R FRANK
• 金额: $ 24.33万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7123677
• 关键词: bioimaging /biomedical imaging; biotechnology; brain mapping; brain morphology; clinical research; computer program /software; computer system design /evaluation; diffusion magnetic resonance imaging; fluorescence polarization; human data; human subject; image enhancement; mathematical model; neuroimaging; white matter

DESCRIPTION (provided by applicant): The diffusion anisotropy (DA) in the brain measured by diffusion tensor imaging (DTI) is related to white matter (WM) structure and is thus an indicator for changes associated with degenerative WM diseases. Estimation of DA is also a necessary precursor to fiber tract mapping (FTM), which holds the potential for understanding brain connectivity. In DTI, signal variations as a function of encoding direction are related to the local tissue diffusion (LTD) from which DA is estimated. In standard DTI, DA is based upon a simplified LTD model requiring only a few encoding directions. But recent work has shown that LTD complexity may not be well fit by the standard model and high angular resolution diffusion (HARD) and multiple diffusion weightings (q-space) are needed to better characterize LTD. This poses three major problems: 1) Analysis and display of HARD and q-space data, and DA and FTM results, is complicated; 2) FTM with HARD data is no longer possible by simple "streamline" methods, and 3) Quantitation of errors in DA and FTM methods is difficult. We have recently developed a DTI analysis plugin to the program AFNI (Analysis of Functional Neurolmages). The primary goal of the current proposal is to further develop this software to address these problems to provide a DTI analysis and visualization platform accessible to all neuroscientists. Our first specific aim is to fully integrate, document, and "productize" our plugin, for dissemination in the AFNI distribution. Also, we have generalized DTI to the spherical harmonic decomposition (SHD), to incorporate more complex LTD models. The second specific aim is to develop rapid, accurate computation and display of the SHD, and our extension to q-space, the spherical wave decomposition (SWD), to produce more accurate DA maps. Our third specific aim is to develop FTM routines based on partial differential equation (PDE) diffusion equation solutions, augmented with prior information, with user-defined "seed" locations, and display within high-resolution anatomical data using advanced visualization methods. The fourth specific aim is to quantitate and display errors in DA and FTM. Motivated by our ongoing work showing changes in WM DA in alcohol abuse patients, and our recent work in fetal alcohol syndrome, Alzheimer's, and language disorders, our ultimate long term goal is to produce a quantitative DTI analysis and visualization tool to aid neuroscientists in their ongoing assessment of degenerate white matter diseases.

描述（由申请人提供）：通过扩散张量成像（DTI）测量的大脑中的扩散各向异性（DA）与白质（WM）结构有关，因此是与退行性WM疾病相关的变化的指标。 DA的估计也是纤维道映射（FTM）的必要先驱，它具有理解大脑连通性的潜力。在DTI中，信号变化是编码方向的函数，与估计DA的局部组织扩散（LTD）有关。在标准DTI中，DA基于一个简化的LTD模型，仅需要少数编码说明。但是最近的工作表明，标准模型可能不太适合LTD的复杂性，并且需要高角度分辨率扩散（硬）和多个扩散权重（Q-Space）来更好地表征LTD。这构成了三个主要问题：1）硬性和Q空间数据的分析和显示以及DA和FTM结果是复杂的； 2）通过简单的“流线”方法不再可能使用硬数据，而3）很难定量DA和FTM方法中的错误。我们最近为AFNI程序开发了DTI分析插件（功能神经元分析）。当前建议的主要目标是进一步开发此软件，以解决这些问题，以提供所有神经科学家均可访问的DTI分析和可视化平台。我们的第一个具体目的是完全集成，文档和“生产”我们的插件，以在AFNI分布中传播。此外，我们将广义的DTI与球形谐波分解（SHD）相结合，以结合更复杂的LTD模型。第二个具体目的是开发SHD的快速，准确的计算和显示，以及我们向Q-Space（SWD）的Q空间扩展，以产生更准确的DA映射。我们的第三个具体目的是基于偏微分方程（PDE）扩散方程解决方案开发FTM例程，并具有先验信息，并使用用户定义的“种子”位置增强，并使用先进的可视化方法在高分辨率解剖数据中显示。第四个特定目的是在DA和FTM中定量和显示错误。通过我们正在进行的工作，显示了酗酒患者WM DA的变化，以及我们最近在胎儿酒精综合症，阿尔茨海默氏症和语言障碍方面的工作，我们的最终长期目标是生产定量的DTI分析和可视化工具，以帮助神经科学家对持续的白质疾病进行评估。