CENC - Diffusion Tensor Imaging Standardization using Novel MR Diffusion Phantoms

 描述(由申请人提供)： 项目背景/基本原理：在过去的十年中，扩散成像作为一种描述由各种疾病过程引起的脑白质损伤的有价值的手段，已经变得越来越重要。弥散成像在评估经历过创伤性脑损伤(TBI)的个体方面具有特殊的前景，因为白质通路的损伤被认为是脑损伤导致的多种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最好的方法。因此，将多种技术获得的成像研究组合在一起会导致难以分析的不均匀数据集，这一事实阻碍了大型数据池的开发。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，磁头线圈)，则即使在从同一制造商制造的并且具有相同场强的两个扫描仪获得的数据中，也会出现分析困难。项目目标：如果要开发扩散成像作为评估疑似脑外伤退伍军人的一种手段，则需要在退伍军人医院网络中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，需要一种方法来准确地确定一台扫描仪与另一台扫描仪(或在一段时间内与其本身)的不同之处。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，以允许跨扫描仪进行更统一的数据采集。在这项提案中，我们将使用扩散成像模体来评估扫描仪之间的差异，目的是提供采集技术，以便将不同患者组的数据进行比较，并合并到大型数据集合中。我们的目标是为世界各地的众多不同扫描仪提供一种手段

 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