Imaging data re-analysis for cocaine addiction

描述(申请人提供)：可卡因成瘾是一种脑部疾病，在美国造成巨大的社会和经济损失。虽然神经成像已越来越多地被用于评估与药物成瘾有关的神经底物，通过检测对药物或药物线索做出反应的大脑活动，但在没有外源性刺激的情况下，对自发脑活动(SBA)的关注要少得多。事实上，SBA是整个大脑活动的主要组成部分，占大脑能量消耗的大部分，并且不可避免地被可卡因成瘾的长期和实质性的神经生物学干扰所改变。因此，评估SBA可提供疾病进展或治疗效果的通用生物标志物。然而，SBA对可卡因成瘾仍然是新的，到目前为止只有两篇论文报道了可卡因依赖脑中基于种子的静息功能连接的差异。使用血氧水平依赖(BOLD)功能磁共振成像来评估SBA是一项主要的研究活动，最近经历了一个密集的增长期。大量大胆的功能磁共振成像衍生的SBA模式已经被证明，其中许多似乎受到疾病状态的调节，也具有巨大的药物成瘾研究潜力。然而，这些模式通常基于相对测量，没有为临床应用提供量化信息。这项研究的目标1是推导出一个量化的 根据我们最近的试点调查，衡量小岛屿发展中国家时间波动的特征。我们将使用合成数据和来自1000功能连接项目的数千名正常受试者的数据来评估这一测量方法。目的2是确定可卡因依赖脑中SBA的改变。我们的中心已经从一大批可卡因患者那里获得了静息BOLD fMRI数据和静息动脉自旋标记(ASL)灌注fMRI数据，为调查原始数据收集项目中未涵盖的SBA问题提供了机会。我们将重复使用这些数据来发现可卡因患者SBA的时间波动变化和幅度变化，如所提出的定量SBA测量和ASL MRI测量的局部脑血流量(CBF)所反映的。此外，我们还将评估可卡因成瘾大脑中功能连接网络的改变。最后，我们将(目标3)探索SBA的实用性(包括时间动力学和大小以及功能连接网络特性)来预测临床结果，包括药物渴求和对可卡因的复发。大量的初步调查证明了拟议目标的可行性。该项目的广泛技术影响是，由此产生的定量时间SBA测量不仅将有利于成瘾研究，而且将有助于在正常和临床人群中进行基于常规静息功能磁共振成像的SBA研究。该项目的临床影响是，它将提供第一个证据，表明可卡因成瘾与颞叶SBA和静息CBF以及整个功能连接网络的改变有关。它还将提供基于SBA的渴望和对药物使用的复发预测的信息。

DESCRIPTION (provided by applicant): Cocaine addiction is a brain disorder that takes a large societal and economical toll in the United States. Although neuroimaging has been increasingly used to assess neural substrates critical for drug addiction by examining brain activity in response to drug or drug cues, much less attention has been paid to spontaneous brain activity (SBA) in the absence of an exogenous stimulus. In fact, SBA is the major component of the whole brain activity that accounts for most of brain energy consumption, and is inevitably altered by the chronic and substantial neurobiological interference of cocaine addiction. Assessing SBA may therefore provide a versatile biomarker of disease progression or treatment effects. However, SBA still remains new to cocaine addiction with only two papers published to date reporting the seed-based resting functional connectivity difference in cocaine dependent brain. The use of blood-oxygen-level-dependent (BOLD) fMRI to assess SBA represents a major research activity that has seen an intensive period of growth recently. A large number of BOLD fMRI-derived SBA patterns have been demonstrated, and many of them appear to be modulated by disease states, carrying a great potential for drug addiction study as well. However, those patterns are generally based on relative measures, providing no quantitative information for clinical applications. AIM 1 of this study is to derive a quantitative measure for characterizing the temporal fluctuations of SBA based on our recent pilot investigations. We will evaluate the measure using synthetic data and thousands of normal subjects' data from the 1000 Functional Connectomes Project. AIM 2 is to identify SBA alterations in cocaine dependent brain. Our center has acquired resting BOLD fMRI data and resting arterial spin labeling (ASL) perfusion fMRI data from a large cohort of cocaine patients, providing an opportunity to investigate SBA questions that were not covered in the original data collection project. We will reuse those data to find both the temporal fluctuation changes and magnitude changes of SBA in cocaine patients as reflected by the proposed quantitative SBA measure and regional cerebral blood flow (CBF) measured by ASL MRI. Moreover, we will assess the functional connection network wise alterations in the cocaine addicted brain. Finally, we will (AIM 3) explore the utility of SBA (including the temporal dynamics and magnitude and the functional connection network properties) for predicting clinical outcomes including drug craving and relapse to cocaine use. The feasibility of the proposed aims is evidenced by the substantial preliminary investigations. The broad technical impact of this project is that the resulting quantitative temporal SBA measure will benefit not only addiction study, but also to the general resting fMRI-based SBA research in normal and clinical populations. The clinical impact of this project is that it will offer the first evidence that cocaine addiction is associated with altered temporal SBA and resting CBF and the entire functional connectivity network. It will also provide information about SBA-based craving and relapse to drug use prediction.