Model-based cerebrovascular markers extracted from hemodynamic data for diagnosing MCI or AD and predicting disease progression.

从血液动力学数据中提取基于模型的脑血管标志物 无创、便携、廉价的MCI或轻度AD的诊断和预测 疾病进展“ 项目总结 拟议的多PI项目的目标是为新的实用程序建立概念证明 脑血管标记物的一类，可帮助改善诊断和预测 轻度认知障碍(MCI)和轻度阿尔茨海默病(AD)的疾病进展。 获得这些标记的手段是非侵入性的、廉价的和便携的，因此它们 可用于初级保健环境中的筛查。这一新类别的科学理论基础 脑血管标记物是由我们小组最近有希望的结果和 越来越多的证据表明MCI/AD与脑血管调节失调有很强的相关性。 最近发表的一项对ADNI的1171名受试者进行的大规模队列回顾研究 数据库使用多因素数据驱动分析评估MCI/AD之间的关系 疾病进展和常用生物标志物(从MRI/PET和血浆/脑脊液获得) 得出结论：脑血管调节失调是最早也是最严重的病理改变。 与AD进展相关的因素，证实了脑血管假说 监管失调。 在这项大规模队列研究中，脑血管失调的量化是通过 ASL-MRI脑血流灌注数据分析。相反，我们打算探索一部小说 分析脑血流动力学的综合动力学建模方法 没有认知障碍的人和MCI/AD患者的方法产生输入- 脑搏动变化之间动态关系的输出预测模型 血流速度(经颅多普勒)或脑组织氧合(近红外 光谱学)，以响应动脉血压和呼气末二氧化碳数据的变化。这个 所获得的基于数据的模型随后被用来计算 脑血管调节。倡导的方法取得了初步成果 46例MCI患者和20例年龄匹配的对照组之间的统计学意义 基于模型的动态血管运动反应性(DVR)标志物的基础。对该计划的评估 DVR标记物与已建立的基于MRI和PET的生物标记物以及 神经心理测试数据，从被提议的项目的更大的队列提供了希望 便携式、非侵入性、廉价和灵敏的脑血管检测手段 在MCI或轻度AD的早期阶段调节失调，并监测疾病进展。 这项研究的重要协变量包括年龄、性别、教育程度、载脂蛋白E基因、地点和 淀粉样蛋白负荷。

"Model-based cerebrovascular markers extracted from hemodynamic data for non-invasive, portable and inexpensive diagnosis of MCI or mild AD and prediction of disease progression" PROJECT SUMMARY The goal of the proposed multi-PI project is to establish proof of concept for the utility of a new class of cerebrovascular markers that may aid in the improved diagnosis and prediction of disease progression in Mild Cognitive Impairment (MCI) and mild Alzheimer's disease (AD). The means for obtaining these markers are non-invasive, inexpensive and portable, so that they can be used for screening in a primary-care setting. The scientific rationale for this new class of cerebrovascular markers is provided by the recent promising results of our group and the mounting evidence of a strong correlation between MCI/AD and cerebrovascular dysregulation. A recently published retrospective study on a large cohort of 1,171 subjects from the ADNI database utilized multi-factorial data-driven analysis to assess the relation between MCI/AD disease progression and commonly used biomarkers (obtained from MRI/PET and plasma/CSF) and concluded that cerebrovascular dysregulation is the earliest and strongest pathologic factor associated with AD progression, corroborating the hypothesis of cerebrovascular dysregulation. Quantification of cerebrovascular dysregulation in that large-cohort study was achieved through analysis of ASL-MRI data of cerebral perfusion. We propose instead to explore a novel integrative dynamic modeling approach that analyzes the cerebral hemodynamics of persons with no cognitive impairment and MCI/AD patients with a methodology that yields input- output predictive models of the dynamic relationships between changes in beat-to-beat cerebral blood flow velocity (via Transcranial Doppler) or cerebral tissue oxygenation (via Near Infrared Spectroscopy) in response to changes in arterial blood pressure and end-tidal CO2 data. The obtained data-based models are subsequently used to compute markers of the dynamics of cerebrovascular regulation. Initial results of the advocated approach have achieved statistically significant delineation between 46 MCI patients and 20 age-matched controls on the basis of a model-based marker of dynamic vasomotor reactivity (DVR). Evaluation of the DVR marker against established MRI-based and PET-based biomarkers, as well as neuropsychological test data, from the larger cohort of the proposed project offers the promise of portable, non-invasive, inexpensive and sensitive means for detecting cerebrovascular dysregulation at the early stages of MCI or mild AD, and monitoring disease progression. Important co-variates of this study include age, gender, education, ApoE genotype, site and amyloid burden.