Beta-Amyloid Clearance Mapping in Alzheimer’s Disease

项目总结 阿尔茨海默病(AD)是最常见的痴呆症形式，可通过脑成像来表征 方法包括磁共振成像(MRI)和正电子发射断层扫描(PET)。核磁共振解释 结构变化，而PET测量代表了根据疾病在大脑中的斑块沉积 进步。斑块沉积反映了早期AD的病理生理，推测是由于 通过大脑的清洁系统清除β-淀粉样蛋白的速率。最近的研究表明， 脑脊液(CSF)在将脑组织废物运送到清洁系统中的潜在作用。然而， 脑脊液在大脑中的流动是如何影响废物清除的，目前还不清楚。因此，建议的 多学科研究项目将涉及来自不同和互补的研究人员的合作 背景(生物力学工程师、磁共振物理学家、神经放射科医生和认知神经学家) 阐述脑脊液血流相关的AD病理生理学。 为了分析脑脊液在颅骨和脑组织之间的狭窄空间(蛛网膜下腔[SAS])中的流动，我们 将使用计算流体动力学(CFD)建模技术，并将脑脊液流动与神经成像相关联 通过核磁共振和正电子发射计算机断层扫描测量标记物。在这里，最重要的假设是“SAS中的脑脊液流动紊乱” 导致淀粉样斑块沉积。为了验证这一假设，我们将采取以下两个步骤：1) 50名健康的老年人将被招募进行核磁共振扫描。基于解剖和脑脊液速度信息 通过核磁共振测量，将通过CFD模拟分析SAS内的三维流动动力学特性， 2)模拟的脑脊液特性将与局部淀粉样斑块沉积相关联 宠物成像数据来自NIH资助的父母研究(维克森林阿尔茨海默病研究中心)。这里, 我们将提出一种新的成像标记，通过结合成像，为每个大脑功能区域去除淀粉样蛋白， CFD和临床措施。作为一种替代方法，如果新的成像标记在 健康的老年人由于样本量较小，我们将把CFD模型应用于较大的AD早期数据集 成年人。 在这个项目完成时，一种新的成像工具可以量化SAS中的脑脊液流量，并评估其对 淀粉样蛋白的沉积和去除将被提出。老年人早期的AD病理生理学可能是 使用提出的方法进行了分析。最终，这个项目将提供一个生物力学框架 阿尔茨海默病的介入和外科治疗程序的设计和测试。开发的软件 程序和成像协议将通过一个公共软件开发/共享平台共享。

PROJECT SUMMARY Alzheimer’s disease (AD) is the most common form of dementia that can be characterized by brain imaging methods such as magnetic resonance imaging (MRI) and positron emission tomography (PET). MRI explains the structural changes, while PET measures represent plaque deposits in the brain according to the disease progression. The plaque deposition reflects early AD pathophysiology and presumably caused by a decrease in the removal rate of beta-amyloid through the cleaning systems of the brain. Recent studies have suggested the potential role of cerebrospinal fluid (CSF) in carrying waste from brain tissue to the cleaning system. However, it is still not well understood how CSF flow in the brain affects waste removal. Therefore, the proposed multidisciplinary research project will involve the collaboration of investigators from diverse and complementary backgrounds (a biomechanical engineer, an MR physicist, a neuroradiologist, and cognitive neuroscientists) to address CSF flow-related AD pathophysiology. To analyze CSF flow in the narrow space between the skull and brain tissue (subarachnoid space [SAS]), we will employ computational fluid dynamic (CFD) modeling technique and correlate CSF flow with neuroimaging markers measured by MRI and PET. Here, the overarching hypothesis is, “Disturbed CSF flow in the SAS leads to the deposition of Amyloid plaque.” To test the hypothesis, we will take the following two steps: 1) Fifty healthy older adults will be recruited for an MRI scan. Based on anatomical and CSF velocity information measured by MRI, three-dimensional flow dynamic properties in SAS will be analyzed through CFD simulation, 2) The simulated CSF properties will be correlated with local amyloid plaque deposition by taking advantage of PET imaging data from the NIH-funded parent study (Wake Forest Alzheimer’s Disease Research Center). Here, we will propose a new imaging marker for amyloid removal for each functional brain region by combining imaging, CFD, and clinical measures. As an alternative approach, in case the new imaging markers are not useful in healthy older adults due to the small sample size, we will apply the CFD model to larger datasets for early AD adults. At the completion of this project, a new imaging tool to quantify CSF flow in the SAS and evaluate its effects on amyloid deposition and removal will be proposed. AD pathophysiology at an early stage in older adults can be analyzed using the proposed approach. Ultimately, this project will provide a biomechanical framework for the design and test of interventional and surgical procedures for the treatment of AD. The developed software programs and imaging protocols will be shared through a public software development/sharing platform.