Integrated Tool for Biological Parametric Mapping

生物参数绘图集成工具

• 批准号: 6803804
• 负责人: Joseph A Maldjian
• 金额: $ 51.58万
• 依托单位: WAKE FOREST UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2008-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6803804
• 关键词: automated data processing; bioimaging /biomedical imaging; brain morphology; clinical research; computed axial tomography; computer system design /evaluation; dyslexia; functional magnetic resonance imaging; gray matter; human subject; image processing; magnetic resonance imaging; neural information processing; neuroimaging; neuropsychology; nuclear magnetic resonance spectroscopy; occipital lobe /cortex; parietal lobe /cortex; positron emission tomography; statistics /biometry; temporal lobe /cortex; time resolved data

DESCRIPTION (provided by applicant): The objective of this Phase I project is to provide the neuroscience research community with a unique investigative tool for the seamless real-time integration of data from emerging imaging modalities (fMRI, PET, SPECT, MRS, and diffusion imaging). This tool will allow analysis of an enormous array of biological processes involving multiple cross-platform modalities recording activation, stimulation, biochemistry and tissue contrast. The proposed tool is IDLSPM, a software solution created by the PI incorporating an advanced computational architecture for distributed processing, analysis and visualization of multimodal imaging data. In this application we propose to incorporate Biologic Parametric Mapping (BPM), a new form of functional imaging data analysis that will integrate the information available from multiple functional imaging modalities and combine them into a user-friendly highly extensible and scaleable software environment. The basic idea behind BPM is to allow the probing of functional imaging data using the results of any other form of functional imaging data. The IDLSPM project represents a complete brain imaging solution that will provide the functional imaging community with unparalleled computational capabilities, integrated neuroanatomic and cytoarchitectonic atlases, ease of use, and tight integration to native SPM, allowing rapid advancement in both research and clinical implementations of functional imaging. In the biologic portion of our effort we will apply the neuroinformatics tools developed in this project towards studying the neurofunctional correlates of dyslexia. Developmental dyslexia is a common neurobehavioral disorder affecting a large number of people. Despite the sizeable prevalence of the disorder, there is relatively little known about its neural basis. Recent multimodal imaging data has implicated the left occipitotemporal and temporoparietal areas as regions of abnormality in dyslexics. The tools developed in this project will be used to uncover the neural functional and chemical relationships of dyslexia using crossmodal sensory tasks, diffusion tensor imaging, and 3D spectroscopy. Our informatics goal is to l) extend the functionality of this tool into a multimodal imaging environment for fMRI, PET, SPECT, diffusion imaging, and 3D spectroscopy data, and 2) incorporate biologic parametric mapping capabilities for probing functional MR data with multimodal imaging data. The goal of the biologic element of our project is to use BPM to determine if diffusion and spectroscopy changes in the occipitotemporal and temporoparietal regions are related to functional MRI changes observed in cross-modal sensory processing in dyslexics.

描述（由申请人提供）：该第一阶段项目的目标是为神经科学研究界提供一种独特的研究工具，用于无缝实时集成来自新兴成像模式（fMRI、PET、SPECT、MRS 和扩散）的数据。成像）。该工具将允许分析大量的生物过程，涉及记录激活、刺激、生物化学和组织对比的多种跨平台模式。所提出的工具是 IDLSPM，这是由 PI 创建的软件解决方案，结合了先进的计算架构，用于多模态成像数据的分布式处理、分析和可视化。在此应用中，我们建议结合生物参数映射（BPM），这是一种新形式的功能成像数据分析，它将集成来自多种功能成像模式的可用信息，并将它们组合到用户友好的高度可扩展和可扩展的软件环境中。 BPM 背后的基本思想是允许使用任何其他形式的功能成像数据的结果来探测功能成像数据。 IDLSPM 项目代表了一个完整的脑成像解决方案，将为功能成像社区提供无与伦比的计算能力、集成的神经解剖学和细胞结构图谱、易用性以及与本地 SPM 的紧密集成，从而使功能成像的研究和临床实施能够快速进步。在我们努力的生物学部分，我们将应用本项目中开发的神经信息学工具来研究阅读障碍的神经功能相关性。发育性阅读障碍是一种影响很多人的常见神经行为障碍。尽管这种疾病相当普遍，但人们对其神经基础知之甚少。最近的多模态成像数据表明，左侧枕颞叶和颞顶叶区域是阅读障碍患者的异常区域。该项目开发的工具将用于通过跨模式感觉任务、扩散张量成像和 3D 光谱来揭示阅读障碍的神经功能和化学关系。我们的信息学目标是 l) 将该工具的功能扩展到 fMRI、PET、SPECT、扩散成像和 3D 光谱数据的多模态成像环境中，2) 结合生物参数映射功能，以利用多模态成像数据探测功能性 MR 数据。我们项目的生物元素的目标是使用 BPM 来确定枕颞和颞顶区域的扩散和光谱变化是否与阅读障碍者跨模式感觉处理中观察到的功能性 MRI 变化相关。