Development and Validation of MRI Mapping of Brain Oxygen Metabolism for Clinical Use

本研究的目的是开发一种无创、无挑战、广泛可用的脑氧提取分数（OEF）定量测定方法。由于大脑持续消耗总供氧量的20%，缺氧容易造成严重的脑组织损伤，如中风和阿尔茨海默病中的缺血缺氧。区域OEF是组织活力和功能的重要、直接的生物标志物，是评估和分层治疗这些神经系统疾病的高度期望。广泛分布的MRI提供了克服15O PET的潜力，15O PET是目前的参考标准，但由于其可用性有限，临床上尚未使用。在MRI中，OEF的定量制图需要从MRI信号中估计脱氧血红素浓度[dH]。从MRI震级信号估计[dH]的方法主要有三种。然而，由于它们使用的MRI震级信号对[dH]具有复杂的依赖性，因此它们通常具有较差的灵敏度和繁琐的数据采集方案。因此，没有基于mri的OEF定位在临床常规使用。此外，这些方法都没有在现行的参考标准15O PET上得到验证。最近，我们开发了一种很有前途的、新颖的、无创的基于mri的OEF方法，该方法不需要血管挑战，并且使用单一的常规MR序列。我们的模型（QSM+qBOLD=QQ）将常被忽视的MRI相位信号的定量敏感性映射（QSM）建模和MRI幅值信号的定量血氧水平依赖（qBOLD）建模相结合，可以将静脉血管中的脱氧血红素铁与弥漫性的其他敏感性源区分开来。在我们的初步数据中，QQ已经在健康成人中进行了15O-PET验证，并在缺血性卒中、多发性硬化和脑肿瘤中显示出OEF异常。然而，在临床应用中，QQ的数据采集和处理方案有待改进，以保证OEF的准确性，因为在较短的回波时间内缺乏数据，并且当前设置下基于梯度求解器的非最优信号建模阻碍了OEF的准确估计。在这个K99/R00项目中，我们将通过改进QQ，建立一套临床易于应用的MRI工具集，用于定量绘制OEF，该工具集经过验证并可供每台MRI扫描仪使用。我们将通过四个具体目标来实现这一目标。Aim1。为MRI-OEF制图开发最佳数据采集。目标2。开发稳健OEF估计的数据处理算法。目标3。根据15O PET对MRI-OEF进行技术验证。目标4。对颅内狭窄患者进行MRI-OEF的临床验证。我们的经验和初步数据使我们有信心，我们很有可能成功完成这个拟议的项目。该项目将及时带来一种新颖、有效、无创、无挑战、常规可用的定量MRI OEF测绘，有可能取代侵入性、复杂的现行标准15O PET OEF。该工具将有助于更好地理解和管理神经血管疾病，例如中风。

The objective of this proposed research is to develop a noninvasive, challenge-free, and widely available method for quantitative mapping of cerebral oxygen extraction fraction (OEF). As the brain continuously consumes 20% of the total oxygen supply, oxygen deficiency easily causes severe brain tissue damages as in hypoxia in ischemia in stroke and Alzheimer's disease. Regional OEF is an essential, direct biomarker for tissue viability and function and highly desired for evaluating and stratifying treatments in these neurologic disorders. Widely distributed MRI provides the potential to overcome the 15O PET, the current reference standard but clinically not used due to its limited availability. In MRI, quantitative mapping of OEF requires estimating deoxyheme concentration [dH] from the MRI signal. Three major approaches have been proposed to estimate [dH] from MRI magnitude signal. However, they commonly suffer from poor sensitives and burdensome data acquisition schemes as the MRI magnitude signal which they utilize has a complex dependence on [dH]. Consequently, no MRI-based OEF mapping has been routinely used in clinical setting. Furthermore, none of these methods have been validated against the current reference standard, 15O PET. Recently, we developed a promising, novel, non-invasive MRI-based OEF method that requires no vascular challenge and utilizes a single routine MR sequence. By integrating quantitative susceptibility mapping (QSM) modeling of often neglected MRI phase signal and quantitative blood oxygenation level dependent (qBOLD) modeling of MRI magnitude signal, our model (QSM+qBOLD=QQ) can distinguish deoxyheme iron in venous vasculature from diffusive other susceptibility sources. In our preliminary data, QQ has been validated against 15O-PET in healthy adults and showed OEF abnormalities in ischemic stroke, multiple sclerosis, and brain tumor. However, for clinical use, data acquisition and processing scheme of QQ should be improved to ensure the accuracy of OEF as a lack of data at short echo time and a non-optimal signal modeling with gradient-based solvers in current setting hinders the accurate OEF estimation. In this K99/R00 project, we will establish a clinically readily applicable MRI toolset for quantitative OEF mapping, which is validated and available to every MRI scanner, by improving QQ. We will achieve this through 4 specific aims. Aim1. Develop optimal data acquisition for MRI-OEF mapping. Aim 2. Develop data processing algorithms for robust OEF estimation. Aim 3. Perform technical validation of MRI-OEF against 15O PET. Aim 4. Perform clinical validation of MRI-OEF in patients with intracranial stenosis. Our experience and preliminary data give us confidence that we will very likely succeed this this proposed project. In a timely fashion, the project will lead to a novel, validated, non-invasive, challenge-free, routinely usable and quantitative MRI OEF mapping, offering the potential to replace invasive, complicated current standard 15O PET OEF. This tool will lead to better understanding and management of neurovascular disorders, e.g. stroke.