MR fingerprinting (MRF) perfusion imaging in cerebral vascular disease

项目摘要/摘要： 缺血性中风是世界范围内的一个主要健康问题。在美国，它是第四大主要原因 死亡是导致重大残疾的主要原因。据估计，超过70万美国人经历了 每年新发或复发的中风。脑灌注成像在中风的几乎所有阶段都扮演着重要的角色。 以及相关的脑血管疾病。 目前，大多数临床灌注成像需要使用造影剂，例如 核磁共振检查。然而，在10%-20%的患者中，由于各种原因，无法使用或未能使用Gd灌注MRI 原因，如过敏反应，肾小球滤过率低，放置静脉导管困难， 适合快速注射，或人为错误的注射时机。因此，另一种替代技术 在临床实践中，Gd灌流将使相当数量的患者受益。 动脉自旋标记(ASL)MRI可以对脑血流量(CBF)进行非对比评估。然而， 在目前的形式下，它不能提供与基于造影剂的灌注所获得的信息相同的信息。 成像。这是因为CBF在卒中描绘中的价值有限。Gd中最有用的参数- 血流灌注是Tmax或团注到达时间(BAT)，但目前的ASL方法不能可靠地测量它们。 这一应用将开发一种新的非对比剂灌注技术，它应用了磁共振的新原理。 ASL的指纹图谱(MRF)。这项技术的主要优点是它允许同时估计 六个参数，CBF，BAT，T1，B1+，血容量和动脉走行时间，在一次扫描中。目标1是 MRF-ASL磁共振成像技术的发展我们将开发MRF-ASL序列计时以实现高效 对灌注参数进行编码。我们还将开发k空间欠采样策略，以获得高 在不增加回声序列长度的情况下进行空间分辨率灌注成像。我们将对 使用基于Gd的灌注磁共振成像技术。该项目的目标2将开发基于云的ASL分析 可为研究人员和临床医生提供免安装、独立于操作系统的平台 ASL分析工具(MRF-ASL以及所有其他类型的ASL数据)。我们在约翰霍普金斯大学的临床团队 长期以来一直对亚急性中风的机制和治疗研究感兴趣。因此，目标3 本项目旨在展示该技术在亚急性卒中中的初步临床应用。 最后，应该强调的是，尽管本项目侧重于其临床应用于 脑血管疾病，开发的方法对其他脑部疾病也有重要的实用价值，如 神经退行性疾病(如阿尔茨海默氏症、帕金森氏病、亨廷顿病)、精神疾病(如 精神分裂症、抑郁症、自闭症、多动症)和肿瘤(原发和转移性脑瘤)。因此，这一点 这项技术预计将产生广泛的临床影响。

Project Summary/Abstract: Ischemic stroke is a major health problem worldwide. In the United States, it is the fourth leading cause of death and the leading cause of major disability. It is estimated that more than 700,000 Americans experience new or recurrent stroke each year. Perfusion imaging plays an important role in virtually all stages of stroke and related cerebrovascular diseases. At present, most clinical perfusion imaging requires the use of contrast agents, e.g. gadolinium (Gd) in MRI. However, Gd perfusion MRI cannot be used or fails to be used in 10-20% of patients, due to a variety of reasons, such as allergic reactions, low glomerular filtration rate, difficulties in placing an intravenous line that is suitable for a rapid injection, or human errors in the timing of injection. Therefore, an alternative technique to Gd-perfusion will benefit a substantial number of patients in clinical practice. Arterial Spin Labeling (ASL) MRI allows for non-contrast evaluation of cerebral blood flow (CBF). However, in its current form, it cannot provide information equivalent to that obtained by contrast-agent-based perfusion imaging. This is because CBF is of limited value in stroke delineation. The most useful parameter in Gd- perfusion is Tmax or bolus-arrive-time (BAT), yet they cannot be measured reliably with current ASL methods. This application will develop a novel non-contrast perfusion technique that applies a new principle of MR fingerprinting (MRF) to ASL. The major strength of this technique is that it allows for simultaneous estimations of six parameters, CBF, BAT, T1, B1+, blood volume, and arterial travel time, in a single scan. Aim 1 is the development of the MRF-ASL MRI technique. We will develop MRF-ASL sequence timing for efficient encoding of perfusion parameters. We will also develop k-space undersampling strategies to obtain high spatial resolution perfusion imaging without increasing echo-train length. We will conduct validation of the technique using Gd-based perfusion MRI. Aim 2 of this project will develop a cloud-based ASL analysis platform that can provide researchers and clinicians with an installation-free, operating-system independent tool for ASL analysis (of MRF-ASL as well as all other types of ASL data). Our clinical team at Johns Hopkins has a long-standing interest in mechanistic and therapeutic studies of sub-acute stroke. Therefore, Aim 3 of the present project is to demonstrate the initial clinical utility of the technique in sub-acute stroke. Finally, it should be emphasized that, although the present project focuses on its clinical applications in cerebrovascular diseases, the method developed also has important utility in other brain diseases, such neurodegenerative diseases (e.g. Alzheimer’s, Parkinson’s, Huntington’s diseases), psychiatric diseases (e.g. schizophrenia, depression, autism, ADHD), and tumor (primary and metastatic brain tumor). Thus, this technique is expected to have a broad clinical impact.