CENC - Diffusion Tensor Imaging Standardization using Novel MR Diffusion Phantoms

 描述（由申请人提供）： 项目背景/依据：在过去的十年中，扩散成像作为描述各种疾病过程引起的白色损伤的有价值的手段而获得了重要性。弥散成像对于评估经历创伤性脑损伤（TBI）的个体具有特别的希望，因为对白色物质通路的损害被认为是导致TBI导致的许多类型的神经认知障碍的重要组成部分。扩散成像可以使用许多不同的成像技术进行，并且没有一种技术被普遍认为是唯一的最佳方法。因此，大数据池的开发受到以下事实的阻碍：将通过多种技术获得的成像研究相结合会导致难以分析的不均匀数据集。如果使用不同的图像采集协议、成像软件包和成像设备（例如，头线圈）。项目目标：如果要开发扩散成像作为评估疑似TBI退伍军人的一种手段，则需要在VA医院网络内可用的不同类型的成像系统中进行统一类型的图像采集。为了构建这样一个系统，需要一种方法来精确地确定一个扫描仪与另一个扫描仪（或随着时间的推移与自身）的差异。然后，可以执行成像序列的修改以及根据需要的硬件和软件组件的修改，以允许跨扫描仪进行更均匀的数据采集。在本提案中，我们将使用扩散成像体模来评估扫描仪之间的差异，目的是提供采集技术，将不同患者组的数据进行比较，并将其合并为大型数据集。我们的目标是提供一种手段，为许多不同的扫描仪在整个

 DESCRIPTION (provided by applicant): Project Background/Rationale: Diffusion imaging has gained importance in the past decade as a valuable means of depicting white matter injury caused by various disease processes. Diffusion imaging holds particular promise for evaluation of individuals who have experienced traumatic brain injury (TBI) because damage to white matter pathways is considered to be an important component in the causation of the many types of neurocognitive impairment that can result from TBI. Diffusion imaging can be performed using a number of different imaging techniques, and no single technique is universally recognized as the single best method. As a result, development of large pools of data is hampered by the fact that combining imaging studies obtained by multiple techniques results in an inhomogeneous data set that is difficult to analyze. Analytical difficulties arise even in data obtained from two scanners made by the same manufacturer and having the same field strength if different image acquisition protocols, imaging software packages and imaging equipment (e.g., head coils) are used. Project Objectives: If diffusion imaging is to be developed as a means to evaluate Veterans with suspected TBI, a uniform type of image acquisition is needed across the different types of imaging systems available within the VA hospital network. To construct such a system, a means is needed to establish exactly how one scanner differs from another (or from itself over the course of time). Then, modification of imaging sequences and, as needed, hardware and software components, can be performed to allow more uniform data acquisition across scanners. In this proposal, we will use diffusion imaging phantoms to evaluate differences between scanners with the goal of providing acquisition techniques that will data to be compared across different patient groups and combined into large data collections. Our objective is to provide a means for the many different scanners across the