BrainSuite: Software for Analysis and Visualization of Multimodal Brain Imaging Data

摘要 在过去的20年里，我们开发并分发了BrainSuite，这是一个开源软件工具的集合 为脑MRI的分析和可视化提供高级功能。自2011年以来，这一努力一直是 主要由母公司NINDS Grant R01-NS078940支持。家长奖助金是根据 生物医学计算、信息学技术的扩展发展、强化和传播 和大数据科学机制(PA-14-156)，主要致力于开发新的联合注册工具 多模式成像数据的建模和分析，扩散数据的建模和分析，以及功能和 结构性互联互通。开发这些工具的目标是支持广泛的 神经成像研究，但我们以前没有在这个项目上有阿尔茨海默病(AD)。 在本应用程序中，我们确定了可以应用和扩展BrainSuite以创建新的 专门为探测脑成像数据而设计的方法，以识别功能和结构变化 表明阿尔茨海默病早期受试者的神经退化。这些新方法将集中于 在大脑的两个区域，内侧颞叶的经鼻嗅区和内嗅区，这是已知的 在疾病的早期阶段显示tau缠结。尤其是经嗅觉皮质，它具有 不经常使用计算解剖学方法进行分析，尽管它在早期AD中有意义。 我们的建议建立在最近开发的纵向微分同胚分析方法的基础上，并将它们应用于 经鼻内嗅皮层(TEC)和内嗅皮层(ERC)的研究 确定TEC和ERC。鉴于这些新方法在AD研究中具有很高的价值潜力，我们已经 制定了补充建议的目标1，以适应BrainSuite的注册和标签工具，制定了 在父母的资助下，自动识别TEC和ERC。这将加速纵向的使用 微分同胚分析方法。在补充建议的目标2下，我们将发展纵向 作为集成到BrainSuite中的工具的微分同形管道。这将加快调查人员申请 这个框架是在研究背景下提出的。在目标2中，我们还将开发工具来检查与AD相关的功能 静息状态fMRI数据的变化。这将建立在我们在母基金中为 分析fMRI数据，并能够检查与TEC和 ERC很可能是与AD相关的神经退行性变的产物。 我们预计，本附录支持的新研究将导致将提供AD的新工具 提供AD早期指标的生物标记物，以及跟踪AD进展的机制。和以前一样 所有BrainSuite工具，这些新方法将作为开源软件免费提供。通过这种方式，我们 预计这些工具将导致其他研究人员以及我们自己的团队进行新的研究，这些研究使用 这些工具用于AD的影像研究。

Abstract For the past 20 years, we have developed and distributed BrainSuite, a collection of open-source software tools that provide advanced capabilities for analysis and visualization of brain MRI. Since 2011, this effort has been largely supported by the parent NINDS Grant R01-NS078940. The parent grant was awarded under the “Extended Development, Hardening and Dissemination of Technologies in Biomedical Computing, Informatics and Big Data Science” mechanism (PA-14-156), and is largely focused on developing new tools for coregistration of multimodal imaging data, modeling and analysis of diffusion data, and quantitative analysis of functional and structural connectivity. These tools have been developed with the goal of supporting a broad a range of neuroimaging studies, but we have not previously had an Alzheimer’s disease (AD) on this project. In the present application, we identified key areas where BrainSuite can be applied and extended to create new methods specifically designed for probing brain imaging data to identify functional and structural changes that indicate neurodegeneration in subjects in the early stages of Alzheimer’s disease. These new methods will focus on two areas of the brain, the transentorhinal and entorhinal region of the medial temporal lobe, that are known to show tau tangles in the earliest stages of the disease. The transentorhinal cortex in particular is one that has not often been analyzed using computational anatomy methods despite its implication in early-stage AD. Our proposal builds on recently developed longitudinal diffeomorphic analysis methods and applying them to the study of the transentorhinal cortex (TEC) and entorhinal cortex (ERC), which relied upon manual delineation to identify TEC and ERC. Given the high potential for these new methods to be of value in AD research, we have developed Aim 1 of the supplement proposal to adapt BrainSuite’s registration and labeling tools, developed under the parent grant, to automatically identify TEC and ERC. This will accelerate the use of the longitudinal diffeomorphic analysis methods. Under Aim 2 of the supplement proposal, we will develop the longitudinal diffeomorphic pipeline as a tool integrated into BrainSuite. This will accelerate the ability of investigators to apply this framework in the research setting. In Aim 2, we will also develop tools to examine AD-related functional changes in resting-state fMRI data. This will build on the methods we have developed in the parent grant for analyzing fMRI data, and enable the examination of changes in functional connectivity associated with TEC and ERC that are likely to result as a product of neurodegeneration associated with AD. We anticipate that the new research supported by this supplement will lead to new tools that will provide an AD biomarker that provides an early indicator of AD, as well as a mechanism for tracking AD progression. As with all BrainSuite tools, these new methods will be made available freely as open source software. In this way, we expect that these tools will lead to new studies, both by other investigators as well as our own team, that use these tools in imaging studies of AD.