Interoperability and Usability Enhancement to DTI ToolKit

描述（由申请人提供）：弥散张量成像（DTI）在协助临床和生物医学研究人员检查和识别可能导致各种脑部疾病的白色物质变化方面发挥着越来越重要的作用。 为了定位和量化这种变化，通常进行基于全脑体素的分析，这需要空间归一化步骤，该步骤用于将研究对象的共享解剖结构置于空间对准中。 目前可用的用于神经成像分析的软件中的标准化方法没有针对DTI数据的专门张量性质进行优化，因此，没有充分利用这些测量中编码的信息来更准确地对准脑白色物质束。 DTI-TK是一个多平台软件工具包，专门为解决这一限制而开发。 它由一套工具组成，这些工具实现了特定于DTI数据的图像操作算法，其中的关键是最先进的可变形图像配准工具，该工具在变换公式中使用显式张量重定向来优化全张量相似性度量。 总之，该工具包提供了最先进的，公开可用的空间归一化软件的DTI数据。 DTI-TK已被证明可以提高空间归一化的质量，并增强临床研究中统计推断的能力。 它可以在网上免费获得，并支持来自全国各地机构的越来越多的调查人员。 该提案的目的是通过改进其互操作性、可用性和文档，使DTI-TK能够被更广泛的神经影像学研究人员使用。 互操作性增强包括对NIfTI图像格式的全面支持，特别强调正确解释NIfTI标头中编码的图像空间和患者空间之间的转换，以及对其他流行DTI工具的兼容性支持。 拟议的可用性增强包括实现MATLAB工具箱，以支持在SPM 5工作流程中集成DTI-TK空间归一化例程。 建议对文档进行的改进包括对所有工具的详细使用说明进行系统编目，以及针对联合收割机DTI-TK与其他神经成像工具相结合的常见使用场景提供面向任务的教程。 为了增加其可访问性，DTI-TK将利用NIH神经影像信息学工具和资源交换所（NITRC）进行传播。 这项工作将有助于让更多用户接触该工具，并创建一个用户和开发人员可以高效交互的环境，从而对互操作性和可用性进行额外的高影响增强。 公共卫生相关性：拟议的项目旨在提高DTI-TK的互操作性、可用性和文档编制，DTI-TK是一个软件工具包，旨在支持和改进对使用扩散张量成像（DTI）获得的数据的分析，DTI是一种新型的磁共振成像方式，为健康和疾病中的脑白色物质的体内成像研究开辟了道路。 具体而言，该工具包将使研究人员能够使用最先进的DTI配准和标准化功能，包括构建人群特异性模板，这将显著提高白色物质变化的群体研究的灵敏度和特异性。 这将使每一个新用户都能使该项目的效果倍增，并对科学产出的质量和意义产生广泛影响。

DESCRIPTION (provided by applicant): Diffusion tensor imaging (DTI) is playing an increasingly important role in assisting clinical and biomedical investigators examine and identify white matter changes that may underly various brain disorders. To localize and quantify such changes, whole brain voxel-based analysis is typically performed, which requires a spatial normalization step that serves to place the shared anatomy of study subjects into spatial alignment. The normalization methods in currently available software for neuroimaging analysis are not optimized for the specialized tensorial nature of DTI data, and, consequently, do not take full advantage of the information encoded in these measurements for more accurate alignment of brain white matter tracts. DTI-TK is a multiplatform software toolkit that has been specifically developed to address this limitation. It consists of a suite of tools that implement image manipulation algorithms specific for DTI data, key among which is a state- of-the-art deformable image registration tool that optimizes full-tensor similarity metrics with explicit tensor reorientation in the transformation formulation. Together, the toolkit provides the most advanced, publicly available spatial normalization software specific for DTI data. DTI-TK has been demonstrated to improve the quality of spatial normalization and enhance the power of statistical inference in clinical studies. It is freely available online and supports a growing number of investigators from institutions across the country. The objective of this proposal is to make DTI-TK accessible to a much wider audience of neuroimaging researchers by making improvements to its interoperability, usability and documentation. Interoperability enhancements include comprehensive support for the NIfTI image format, with a special emphasis on correct interpretation of the transformations between image space and patient space encoded in NIfTI headers, and compatibility support for other popular DTI tools. Proposed usability enhancement includes the implementation of a MATLAB toolbox to support the integration of the DTI-TK spatial normalization routine within SPM5 workflows. Proposed improvements to documentation involve both systematic cataloging of detailed usage instructions for all of the tools and task-oriented tutorials for common usage scenarios that combine DTI-TK with other neuroimaging tools. Toward increasing its accessibility, DTI-TK will leverage the NIH Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) for dissemination. This effort will help expose many more users to the tool and create an environment in which users and developers can interact productively, leading to additional high- impact enhancements to interoperability and usability. PUBLIC HEALTH RELEVANCE: The proposed project aims to improve the interoperability, usability and documentation of DTI-TK, a software toolkit designed to support and improve the analysis of data acquired using diffusion tensor imaging (DTI), a novel magnetic resonance imaging modality that has opened the way to in vivo imaging studies of brain white matter in health and disease. Specifically, the toolkit will give researchers access to state-of-the-art DTI registration and normalization functionality, including the construction of population-specific templates, that will significantly enhance the sensitivity and specificity of group studies of white matter changes. This will multiply the effect of this project with each new user and have a wide influence on the quality and significance of scientific output.