Core F: Neuroimaging Core

摘要 加州大学旧金山分校阿尔茨海默病研究中心(ADRC)的成像核心通过以下方式积极支持该中心 管理高质量结构和功能MRI和PET数据集的获取、归档和处理 并将这些数据提供给ADRC和其他调查人员。在我们P50中心的前几个周期中，成像 CORE一直是将尖端结构、功能和分子成像技术应用于 临床核心研究中紧随其后的是不同类型的队列。在这个新的P30应用程序中，成像核心将追求 以下目标：目标1：图像的收集和存档以及图像数据库的维护。我们 将监督ADRC参与者的以下MRI和PET序列的管理：MP-RAGE、FLAIR、 T2加权、DTI、ASL灌注、ICN-fMRI、淀粉样蛋白和tau PET扫描。我们会将未确认的身份存档 其他ADRC调查人员可以访问的服务器上的图像，并提供工具来定位和 正在下载图像以进行分析。我们还将把MRI和PET成像数据集上传到NACC，以便于 分享，我们将可以为对使用这些图像感兴趣的调查人员回答问题。目标2： 图像质量控制和预处理：我们将为MPRAGE采用QC和预处理框架， DTI、ASL-MRI、ICN-fMRI以及淀粉样蛋白和tau PET图像，便于AD研究人员和他们的 集成到多通道分析中。目标3：制定和传播标准和创新 分析工具：我们将维护和改进一系列工具，以表征大脑中与疾病相关的变化 体积、脑白质微结构、脑白质信号高信号、基于功能磁共振成像的连接、大脑 灌流和PET配体结合，包括优化管道以进行横截面和纵向分析。 我们将进一步开发复杂的分类引擎，能够利用多种形式的数据和 数据中的关系类型，例如基于机器学习的工具和基于体素的实现 混合线性模型。目标4：支持研究培训：我们将与研究教育合作 组件将图像采集和分析的基本原理整合到研究性培训计划中 并支持对希望将图像分析纳入其研究集的个人进行额外培训 技能。在追求这些目标的过程中，成像核心将与所有其他ADRC核心广泛互动， 朝着提高诊断准确性、促进我们对疾病的理解的共同目标前进 机制，并通过改进临床试验设计使药物发现成为可能。

ABSTRACT The Imaging Core of the UCSF Alzheimer’s Disease Research Center (ADRC) actively supports the Center by managing acquisition, archiving, and processing of high quality structural and functional MRI and PET datasets and providing these data to ADRC and other investigators. In previous cycles of our P50 center, the Imaging Core has been a leader in applying cutting-edge structural, functional, and molecular imaging techniques to the heterogeneous cohorts followed in the Clinical Core. In this new P30 application, the Imaging Core will pursue the following aims: Aim 1: Collection and archiving of images and maintenance of an image database. We will supervise management of the following MRI and PET sequences from ADRC enrollees: MP-RAGE, FLAIR, T2-weighted, DTI, ASL perfusion, ICN-fMRI, and amyloid and tau PET scans. We will archive de-identified images on a server accessible to the rest of the ADRC investigators and provide tools for locating and downloading images for analysis. We will also upload MRI and PET imaging datasets to the NACC to facilitate sharing, and we will be available to answer questions for investigators interested in using these images. Aim 2: Image quality control and preprocessing: We will employ QC and pre-processing frameworks for MPRAGE, DTI, ASL-MRI, ICN-fMRI, and amyloid and tau PET images, facilitating their use by AD researchers and their integration into multi-modality analyses. Aim 3: Development and dissemination of standard and innovative analytic tools: We will maintain and refine an array of tools to characterize disease related changes in brain volume, white matter microstructure, white matter signal hyperintensity, fMRI-based connectivity, cerebral perfusion, and PET ligand binding, including optimizing pipelines for cross-sectional and longitudinal analyses. We will further develop sophisticated classification engines capable of utilizing multiple forms of data and multiple types of relationships within our data, such as machine-learning based tools and voxel-wise implementation of mixed linear models. Aim 4: Support research training: We will work with the Research Education Component to integrate basic principles of image acquisition and analysis into the research training program and support additional training of individuals who wish to incorporate image analysis into their set of research skills. In pursuing these aims, the Imaging Core will interact extensively with all other ADRC cores, working towards the common goals of improving diagnostic accuracy, forwarding our understanding of disease mechanisms, and enabling drug discovery by improving clinical trial design.