Image-based cerebrovascular network snythesis(iCNS) to model Alzheimer's Disease

与年龄相关的神经变性的大量资源被用于动物研究 假设结果将有助于我们对人类并行过程的理解。然而，目前还没有可靠的方法 存在将脑血流或代谢数据从动物准确转换为人类的技术。因为缺乏严谨 物种间脑代谢参数的数学方法，有价值的研究数据的转换 从老鼠到人类遗骸的猜测。需要一种预测计算框架，该框架 量化正常和疾病人脑状态下的脑血流和新陈代谢。我们的长期目标 是量化衰老和阿尔茨海默病(AD)的基本生理过程，以便它们的影响 可以减慢甚至部分逆转。其目的是通过放大磁共振成像分析的 用机械论数学框架检测人类与年龄相关的微循环变化。它 我们的假设是，年龄和AD相关的微循环变化也会产生宏观 血流动力学和/或氧气灌流状态的扰动，将通过先进的MRI检测到 技术，当在所有相关的长度尺度上的严格的大脑模拟的指导下。理由就是那么关键 老年脑功能障碍的生理指标(=老化生物标记物)将由系统性研究揭示 探索和模拟基本的血流动力学和代谢过程。中心假说将 通过追求三个具体目标来接受考验： 目的1)通过模拟毛细管失速之间的联系来评估机械建模的预测价值， 血管示踪剂传输特性和组织氧输送，并使用高级 小鼠的显微成像。我们确定了衰老和阿尔茨海默病对老龄啮齿动物大脑的影响。 目的2)建立机制多尺度模型以预测脑血流灌注对氧的影响 在正常和病理条件下，人类大脑皮层的代谢。解剖学上详细的机械学 人类脑循环模型将预测AD的结构和功能变化对 用核磁共振技术提取人脑中的氧气。 目的3)评估机械性多尺度建模在量化微血管特性中的预测价值 使用先进的核磁共振技术在健康和疾病的人类大脑皮层进行研究。对机械化翻译的验证 从老鼠到人类，我们将测量老年和阿尔茨海默病队列中与年龄相关的代谢功能 病人。我们确定了与认知衰退相关的血液动力学和代谢指标(=生物标记物) 这一贡献意义重大，因为它将预测血管形态测量和新陈代谢的变化 导致神经功能衰退。它将识别在人类非侵入性诊断成像中可见的生物标记物 在症状发展之前发出与年龄相关的恶化的信号。与在以下方面获得的数据相关的机制框架 从老鼠到人类，将极大地提高动物数据与人类医学的相关性。

Significant resources on age-related neurodegeneration are directed toward animal research in the assumption that results will inform our understanding of parallel processes in human. Yet, no reliable method exists to accurately translate cerebral blood flow or metabolic data from animal to human. For lack of rigorous mathematical methods for cerebral metabolic parameters between species, translation of valuable research data from mouse to human remains guesswork. There is a need for a predictive computational framework that quantifies cerebral blood flow and metabolism in normal and diseased human brain states. Our long term goal is to quantify fundamental physiological processes of aging and Alzheimer’s disease (AD), so that their effects can be slowed or even partially reversed. The objective is to expand the utility of MRI analysis by magnifying the detectability of age-related microcirculatory changes in humans with a mechanistic mathematical framework. It is our hypothesis that age and AD related changes in the microcirculation also generate macroscopic perturbations of hemodynamic and/or oxygen perfusion states that will be detectable with advanced MRI techniques, when guided by rigorous brain simulations over all relevant length scales. The rationale is that critical physiological metrics for dysfunction in aged brains (=aging biomarkers) will be exposed by systematic exploration and simulation of fundamental hemodynamic and metabolic processes. The central hypothesis will be tested by pursuing three specific aims: Aim 1) Assess the predictive value of mechanistic modeling by simulating the link between capillary stalling, vascular tracer transit properties, and tissue oxygen delivery, and validate predictions using advanced microscopic imaging in mouse. We determine the effects of aging and AD in aged rodent brains. Aim 2) Develop mechanistic multiscale model for predicting the impact of cerebral perfusion on oxygen metabolism in the human cortex under normal and pathological conditions. Anatomically detailed mechanistic models of cerebral circulation in human will predict the effect of structural and functional changes in AD on oxygen extraction in the human brain with MRI. Aim 3) Assess the predictive value of mechanistic multiscale modeling to quantify microvascular properties across the human brain cortex in health and disease using advanced MRI. To validate the mechanistic translation from mouse to human, we will measure age-related metabolic functions in cohorts of aged and Alzheimer patients. We identify hemodynamic and metabolic metrics (=biomarkers) that correlate with cognitive decline This contribution is significant because it will predict how changes in vascular morphometry and metabolism lead to neurological decline. It will identify biomarkers visible in noninvasive diagnostic imaging in humans that signal age-related deterioration before symptoms develop. The mechanistic framework relating data acquired in mouse to human will dramatically boost the relevance of animal data for human medicine.