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）：本I阶段项目的目的是为神经科学研究社区提供独特的调查工具，用于从新兴成像方式中无缝实时整合数据（fMRI，PET，PET，SPECT，MRS和扩散量）成像）。该工具将允许分析涉及多个跨平台模态的大量生物学过程，记录激活，刺激，生物化学和组织对比度。提出的工具是IDLSPM，这是一种由PI创建的软件解决方案，该软件解决方案结合了高级计算体系结构，用于分布式处理，分析和可视化多模式成像数据。在此应用程序中，我们建议将生物学参数映射（BPM）融合在一起，这是一种新形式的功能成像数据分析，将整合从多种功能成像模式可用的信息，并将它们组合到用户友好型高度可扩展且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探测功能成像数据。 IDLSPM项目代表了一种完整的大脑成像解决方案，它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构造图集，易用性以及与本地SPM的紧密整合，从。在我们努力的生物学部分中，我们将应用该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。发育阅读障碍是一种影响大量患者的常见神经行为疾病。尽管该疾病的患病率很高，但对其神经的基础知之甚少。最近的多模式成像数据已暗示左枕颞和颞叶区域是阅读障碍中异常的区域。该项目中开发的工具将用于使用跨模式感觉任务，扩散张量成像和3D光谱法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光谱镜数据的多模式成像环境中，以及2）结合生物学参数映射能力，以探测功能性MR数据的功能性MR数据。我们项目的生物学元素的目的是使用BPM来确定枕颞和颞叶区域的扩散和光谱变化是否与跨模式感官处理中观察到的功能性MRI变化有关。