Quantitative cerebral blood vessel imaging biomarkers for AD and VCID

项目概要/摘要 阿尔茨海默病 (AD) 和血管性认知障碍和痴呆 (VCID) 是导致老年痴呆症的两个主要原因 老年人的认知能力下降和痴呆症都与脑血管疾病（CVD）有关。 尸检结果表明，AD 和 VCID 的血管病理学基本类型不同。在 AD 中，Aβ 经常积聚在软脑膜和皮质小动脉中（称为脑淀粉样血管病（CAA））， 而在 VCID 中，动脉粥样硬化或动脉粥样硬化 (ASCVD) 会影响大的进食和小穿孔 动脉（例如，豆纹动脉（LSA））。然而，让事情变得复杂的是，混合 AD/VCID 病理现象很常见，尤其是随着年龄的增长。迄今为止，血管病理学的研究 AD/VCID 主要限于脑实质血管性脑损伤的间接测量（例如，白 物质高信号、梗塞和微出血），其严重程度和类型缺乏特异性 潜在的血管病理学。动脉僵硬度和动脉搏动是血管的重要指标 功能障碍。动脉僵硬度增加或动脉搏动增加可导致过度传导 脉动能量进入下游微血管，导致内皮功能障碍和血管 炎症。目前，这些评估主要在中央或主要大脑动脉上进行。 脑血管形态也反映了脑血管的健康状况，但脑血管分支存在个体差异。 脑血管的存在使得跨受试者提供可靠的定量形态学指标变得困难。 因此，直接评估脑血管的健康和功能状态（例如动脉僵硬度、 脑血管树各个层次的搏动和形态）可以提供更全面的信息 了解 AD/VCID 的血管病理学并有助于区分 CAA/ASCVD。此举的目标 应用程序是开发一类脑血管血流动力学和形态学指标并 AD 和 VCID 中脑血管功能障碍的特征。 Aim1 将开发和验证定量 使用先进的 MRI 技术和新颖的图像进行血流动力学和形态血管指标 (VM) 脑血管树不同层次的处理算法管道。 Aim2将导出这些血管 100 名老年受试者样本中的指标，丰富了 apoE 基因型和心血管危险因素。瞄准 如图 2a 所示，我们将 VM 与脑血流量、血管性脑损伤和认知障碍相关联。在目标 2b 中，我们 将软脑膜动脉或豆纹动脉中的 VM 与淀粉样蛋白 PET 配体的摄取相关联， 心血管风险概况，以确定特定位点 VM 的改变是否有助于区分 CAA 与非心血管疾病。 ASCVD。成功完成拟议的研究将提供一类可靠的脑血管 用于表征和区分 AD/VCID 血管病理学的生物标志物。

PROJECT SUMMARY/ABSTRACT Alzheimer’s disease (AD) and Vascular Cognitive Impairment and Dementia (VCID) are two leading causes of cognitive decline and dementia in the elderly and are both associated with cerebrovascular disease (CVD). Postmortem findings show that the underlying type of vascular pathology differs in AD and VCID. In AD, Aβ often accumulates in leptomeningeal and cortical arterioles (known as cerebral amyloid angiopathy (CAA)), while in VCID, atherosclerosis or arteriolosclerosis (ASCVD) affects large feeding and small perforating arteries (e.g., lenticulostriate arteries (LSA)), respectively. However, to complicate matters, mixed AD/VCID pathologies are common, especially with increasing age. To date, the investigations of vascular pathology in AD/VCID are mainly limited to indirect measures of vascular brain injury in brain parenchyma (e.g., white matter hyperintensity, infarcts, and microbleeds), which lack specificity vis a vis the severity and type of underlying vascular pathology. Arterial stiffness and arterial pulsatility are important indicators of blood vessel dysfunction. Increased arterial stiffness or elevated arterial pulsatility can result in transmission of excessive pulsatile energy into downstream microvasculature, and lead to endothelial dysfunction and vascular inflammation. Currently, these assessments are mostly carried out on central or major cerebral arteries. Cerebral vascular morphology also reflects the health of brain vessels, but individual variation in branching of cerebral vessels has made it difficult to provide reliable quantitative morphological metrics across subjects. Therefore, directly assessing the health and functional status of cerebral blood vessels (e.g., arterial stiffness, pulsatility, and morphology) at various levels of the cerebral vascular tree could provide a more comprehensive understanding of the vascular pathology in AD/VCID and help differentiate CAA/ASCVD. The goal of this application is to develop a class of cerebral blood vessel hemodynamic and morphological metrics and to characterize cerebral blood vessel dysfunction in AD and VCID. Aim1 will develop and validate quantitative hemodynamic and morphological vascular metrics (VM) using advanced MRI technologies and novel image- processing algorithm pipelines at different levels of cerebrovascular tree. Aim2 will derive these vascular metrics in a sample of 100 elderly subjects enriched for apoE genotype and cardiovascular risk factors. In Aim 2a, we will correlate VM with cerebral blood flow, vascular brain injury, and cognitive impairment. In Aim 2b, we will correlate VM in leptomeningeal arteries or lenticulostriate arteries with uptake of amyloid PET ligands and cardiovascular risk profile to determine whether alterations in site-specific VM can help differentiate CAA vs. ASCVD. Successful completion of the proposed research would deliver a class of reliable cerebral vascular biomarkers to characterize and differentiate vascular pathology in AD/VCID.