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）结构相关，因此是与退行性WM疾病相关的变化的指标。 DA 的估计也是纤维束绘图 (FTM) 的必要前提，它具有了解大脑连接的潜力。在 DTI 中，作为编码方向函数的信号变化与估计 DA 的局部组织扩散 (LTD) 有关。在标准 DTI 中，DA 基于仅需要几个编码方向的简化 LTD 模型。但最近的工作表明，LTD 复杂性可能不太适合标准模型，需要高角分辨率扩散 (HARD) 和多重扩散权重（q 空间）来更好地表征 LTD。这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) 通过简单的“流线型”方法不再能够使用 HARD 数据进行 FTM，并且 3) DA 和 FTM 方法中的误差定量很困难。我们最近为 AFNI（功能神经影像分析）程序开发了 DTI 分析插件。当前提案的主要目标是进一步开发该软件来解决这些问题，为所有神经科学家提供一个 DTI 分析和可视化平台。我们的第一个具体目标是完全集成、记录和“产品化”我们的插件，以便在 AFNI 发行版中传播。此外，我们还将 DTI 推广到球谐分解 (SHD)，以合并更复杂的 LTD 模型。第二个具体目标是开发 SHD 的快速、准确计算和显示，以及我们对 q 空间的扩展，即球面波分解 (SWD)，以生成更准确的 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，并使用先验信息和用户定义的“种子”位置进行增强，并使用先进的可视化方法在高分辨率解剖数据中显示。第四个具体目标是量化和显示 DA 和 FTM 中的错误。受我们正在进行的显示酒精滥用患者 WM DA 变化的工作以及我们最近在胎儿酒精综合症、阿尔茨海默病和语言障碍方面的工作的推动，我们的最终长期目标是生产一种定量 DTI 分析和可视化工具，以帮助神经科学家对退化白质疾病的持续评估。