Taking advanced diffusion imaging to the clinic for pediatric patients with ADHD

描述（由申请人提供）：在这项资助申请中，我们建议开发临床可行的方法，用于采集和分析儿科患者的高级弥散磁共振成像（dMRI），并将其应用于研究注意力缺陷多动障碍（ADHD）的微观和宏观病理学。先进的dMRI技术可以提供有关大脑中白色物质通路的布局的细节，这是使用当前的扩散张量成像（DTI）临床标准所不可能实现的。然而，这些高级协议需要长的扫描时间，并且在此期间的任何运动都会导致伪影和信号丢失。因此，儿童的dMRI采集成为一项具有挑战性的任务，特别是如果他们是多动症（如ADHD）。在本申请中，我们提出了几种新的算法，用于快速采集和重建先进的dMRI协议。特别是，我们将使用我们的多切片采集协议（与标准的单切片采集相反），沿着 从很少的测量中恢复dMRI信号的方案。这将大大减少扫描时间，并使其能够获得儿科患者的高级dMRI扫描（在诊所中）。我们将在几个测试对象上验证我们的方法，然后将其应用于ADHD儿童和青少年的研究。特别是，我们将分析全球的解剖神经网络的连接特性，在多动症沿着与局部扩散为基础的微观结构特性，可能会受到影响，由于病理。因此，本提案中建议的改进将为临床带来先进的dMRI方案，并使我们能够量化任何类型的精神或神经系统疾病患者的微观和宏观水平异常。

DESCRIPTION (provided by applicant): In this grant application, we propose to develop clinicaly feasible methods for the acquisition and analysis of advanced diffusion magnetic resonance imaging (dMRI) of pediatric patients and apply it to study micro and macro level pathology in attention-deficit hyperactivity-disorder (ADHD). Advanced dMRI techniques can provide details about the layout of white matter pathways in the brain, that are not possible using the current clinical standard of diffusion tensor imaging (DTI). However, these advanced protocols require long scan times and any motion during this time results in artifacts and loss of signal. As a result, dMRI acquisition of children becomes a challenging task, particularly if they are hyperactive (as in ADHD). In this grant application, we propose several novel algorithms for fast acquisition and reconstruction of advanced dMRI protocols. In particular, we will use our multi-slice acquisition protocol (as opposed to the standard single-slice acquisition) along with a scheme to recover dMRI signals from very few measurements. This will dramatically reduce scan time and make it possible to obtain advanced dMRI scans of pediatric patients (in a clinic). We will validate our methods on several test subjects and then apply them to the study of children and adolescents with ADHD. In particular, we will analyze global connectivity properties of the anatomical neural networks in ADHD along with local diffusion based microstructural properties that may be affected due to pathology. Thus, the improvements suggested in this proposal will bring advanced dMRI protocols to the clinic and allow us to quantify micro and macro level abnormalities in patients with any type of psychiatric or neurological disorder.