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）：通过弥散张量成像（DTI）测量的脑中弥散各向异性（DA）与白色物质（WM）结构相关，因此是退行性WM疾病相关变化的指标。DA的估计也是纤维束映射（FTM）的必要前提，FTM具有了解大脑连接的潜力。在DTI中，作为编码方向的函数的信号变化与估计DA的局部组织扩散（LTD）相关。在标准DTI中，DA基于简化的LTD模型，仅需要几个编码方向。但近年来的研究表明，标准模型不能很好地描述LTD的复杂性，需要高角分辨率扩散（HARD）和多重扩散加权（q空间）来更好地描述LTD。这就带来了三个主要问题：1）HARD和q空间数据以及DA和FTM结果的分析和显示复杂; 2）使用HARD数据的FTM不再可能通过简单的“流线型”方法，3）DA和FTM方法中的误差的定量是困难的。我们最近开发了一个DTI分析插件程序AFNI（功能性神经影像分析）。当前提案的主要目标是进一步开发该软件以解决这些问题，为所有神经科学家提供一个可访问的DTI分析和可视化平台。我们的第一个具体目标是完全集成，文档化和“产品化”我们的插件，以便在AFNI发行版中传播。此外，我们已经将DTI推广到球谐分解（SHD），以纳入更复杂的LTD模型。第二个具体目标是开发快速，准确的计算和显示的SHD，我们的扩展到q空间，球面波分解（SWD），以产生更准确的DA地图。我们的第三个具体目标是开发基于偏微分方程（PDE）扩散方程解的FTM例程，增强先验信息，用户定义的“种子”位置，并使用高级可视化方法在高分辨率解剖数据中显示。第四个具体目标是量化和显示DA和FTM中的错误。我们正在进行的工作，显示在酒精滥用患者的WM DA的变化，我们最近的工作在胎儿酒精综合征，阿尔茨海默氏症和语言障碍的动机，我们的最终长期目标是产生一个定量的DTI分析和可视化工具，以帮助神经科学家在他们正在进行的评估退化白色物质疾病。