Sharing Clinical and Imaging Data from ADCS Clinical Trials through BIRN

描述(由申请人提供)：阿尔茨海默病合作研究(ADCS)拥有成熟的组织基础设施，可以在学术环境中进行阿尔茨海默病(AD)的大规模临床试验。自成立以来的19年里，ADCS通过协调80多个参与站点的临床试验活动，完成了多项开创性的AD研究。到2011年底，最近的ADCS试验将收集到近3000例脑磁共振成像(MRI)和正电子发射断层扫描(PET)扫描。生物医学信息学研究网络(BIRN)为与更广泛的研究社区共享ADCS临床和脑成像数据提供了理想的资源。这项拟议工作的主要目标是使用BIRN工具分析和共享来自先前和正在进行的ADCS临床试验的横断面和纵向脑成像数据。为了实现这一目标，研究人员将1)使用BIRN工具和程序收集临床和脑成像数据，以进行质量保证和识别。2)使用BIRN工具提供区域脑体积成像数据，用于横断面体积测量、皮质分割和皮质厚度测量，并在有PET成像数据时结合MRI-PET注册以量化区域代谢活动。3)使用纵向脑成像数据和一种新的方法来量化次区域体积随时间的变化，从而提供对区域萎缩的测量。4)在遵循现有本体的情况下提供数据建模和数据对象之间的链接。5)使用BIRN基础设施共享所有原始和处理过的脑图像以及链接的体积、代谢和临床数据。该项目利用加州大学圣地亚哥分校现有的基础设施和专业知识进行大规模的AD临床试验，并对大脑成像数据进行大规模分析。然而，对于一所大学的研究人员来说，数据集的丰富性太大了，无法充分利用，而且数据的重要性要求BIRN基础设施支持跨大学合作。总而言之，拟议的工作将使研究人员能够访问一个有价值的数据集，否则无法在这样的规模上研究这一主题，并将促进合作研究，很可能极大地促进关于AD对大脑结构和功能影响的知识。

DESCRIPTION (provided by applicant): The Alzheimer's Disease Cooperative Study (ADCS) has an established organizational infrastructure to conduct large scale clinical trials in Alzheimer's disease (AD) in the academic setting. Over the 19 years since its inception, the ADCS has completed multiple seminal AD studies by coordinating clinical trial activity across more than 80 participant sites. By the end of 2011, recent ADCS trials will have collected nearly 3000 brain magnetic resonance imaging (MRI) and positron emission tomography (PET) scans. The Biomedical Informatics Research Network (BIRN) provides an ideal resource for sharing ADCS clinical and brain imaging data with the broader research community. The primary goal of the proposed work is to use BIRN tools to analyze and share cross-sectional and longitudinal brain imaging data from prior and ongoing ADCS clinical trials. To achieve this goal, the investigators will 1) Assemble clinical and brain imaging data using BIRN tools and procedures for quality assurance and de-identification. 2) Provide regional volumetric brain imaging data using BIRN tools for cross-sectional volumetry, cortical parcellation, and cortical thickness measurements, combined with MRI-PET registration for quantification of regional metabolic activity when PET imaging data is available. 3) Provide measurements of regional atrophy using longitudinal brain imaging data and a novel procedure to quantify subregional volumetric change over time. 4) Provide data modeling and links between data objects with adherence to existing ontologies. 5) Share all raw and processed brain images as well as linked volumetric, metabolic, and clinical data using BIRN infrastructure. The project leverages the existing infrastructure and expertise assembled at the University of California, San Diego for large scale AD clinical trials and for large scale analyses of brain imaging data. Nevertheless, the richness of the dataset is far too great for researchers at a single university to fully exploit, and the importance of the data calls for collaboration across universities that the BIRN infrastructure enables. In summary, the proposed work will make a valuable dataset accessible to researchers otherwise unable to study this topic on such a scale, and will facilitate collaborative research likely to greatly advance knowledge about the structural and functional consequences of AD on the brain.