Digital biomarkers for Alzheimer's Disease with compact dual-mode brain sensing

紧凑型双模式脑传感阿尔茨海默病的数字生物标志物 2018年，美国国家老龄与阿尔茨海默氏症协会联合打造了一份《研究框架》， 为阿尔茨海默病(AD)提供新的生物学定义 侧重于用生物标记物在活人中诊断AD[1]。现在，“阿尔茨海默病(AD)被定义为 通过其潜在的病理过程，可以通过尸检或体内通过 生物标记物。“[1]开发和验证用于AD早期检测的数字生物标记物是非常必要的。它是 如果这样的数字生物标记物可以用紧凑型设备测量，那就更好了。 众所周知，阿尔茨海默病的大脑在解剖学、生物学和病理学上都有显著的退行性改变 方面。这种恶化必须伴随着大脑的代谢、血流动力学和 阿尔茨海默病患者脑电生理(MHE)活动。此外，AD从早期到晚期的进展需要 多年来，通常在早期没有或很少出现症状。然而，尖端的生物构造- 基于大脑传感技术，可能能够检测到MHE活动的进行性退化。 这项研究的假设是AD患者的大脑MHE功能受损，可以 通过数字生物标志物进行感知，这些数字生物标志物来自15分钟的静息状态大脑测量，同时进行 紧凑、双模、宽带近红外光谱(BbNIRS)和干/无线脑电 (DwlEEG)，来自潜在的AD患者。 具体地说，我们希望进行一项原则证明研究，即开发、测试和演示一部小说 集成bbNIRS和DWLEEG(bbNIRS+DWLEEG)的广告传感系统是一种紧凑型、双模、低成本、 和高效率的设备。所提出的bbNIRS+dwlEEG装置使我们能够进行静息状态的人体 大脑测量，将导致量化(1)脑代谢，(2)脑血容量 和氧合，以及(3)大脑节律功率和连接性分别以不同的频率振荡， 来自正常受试者和AD患者。具体来说，对于这个R21提案，我们有两个目标：目标1是 建立基于静息状态的健康人脑MHE活动的数字生物标志物或特征 使用紧凑型bbNIRS+dwlEEG系统进行状态、神经生理测量。目标2是找出合适的 能够准确区分健康老年人和AD患者以及对AD进行分层的生物标志物 根据痴呆症的不同阶段(轻度和中度至重度)的患者。 R21的结果将为双模bbNIRS+DWLEEG系统提供原理证明 能够识别关键的数字生物标记物，从而实现AD的准确检测和分层 处于轻度或中度至重度阶段，允许我们进行更大的研究项目(即R01)以 通过紧凑、低成本、有效的双模式大脑推动数字生物标志物用于AD的早期检测 传感系统。

Digital biomarkers for Alzheimer's Disease with compact dual-mode brain sensing In 2018, the National Institute on Aging and Alzheimer's Association jointly created a “research framework,” providing a new biological definition of Alzheimer's disease (AD) by emphasizing a biological construct and focuses on the diagnosis of AD with biomarkers in living persons [1]. Now, “Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers.” [1] It is highly desirable to develop and validate digital biomarkers for early detection of AD. It is even better if such digital biomarkers can be measured with compact devices. It is known that the AD brain has significant degenerations in all anatomical, biological, and pathological aspects. Such deteriorations must be accompanied by cerebral dysfunctions of metabolic, hemodynamic, and electrophysiological (MHE) activities in the AD brain. Also, the progression from early to late stage of AD takes years and often shows no or few symptoms at the early stage. However, cutting-edge, biological-construct- based, brain-sensing technology may enable to detect progressive degeneration of MHE-activity. The hypothesis of this study is that patients with AD are impaired in their cerebral MHE functions and can be sensed by digital biomarkers derived from 15-min, resting-state brain measurements concurrently taken with compact, dual-mode, broadband near infrared spectroscopy (bbNIRS) and dry/wireless electroencephalogram (dwlEEG) from potential patients with AD. Specifically, we wish to conduct a proof-of-principle study, namely, to develop, test, and demonstrate a novel AD-sensing system by integrating bbNIRS and dwlEEG (bbNIRS+dwlEEG) as a compact, dual-mode, low-cost, and high-efficient device. The proposed bbNIRS+dwlEEG device enables us to perform resting-state human brain measurements which will result in quantifications of (1) cerebral metabolism, (2) cerebral blood volume and oxygenation, and (3) brain rhythm powers and connectivity oscillating at different frequencies, respectively, from both normal subjects and patients with AD. For this R21 proposal, specifically, we have two aims: Aim 1 is to establish digital biomarkers or features of cerebral MHE-activities of the healthy human brain based on resting- state, neurophysiological measures with a compact bbNIRS+dwlEEG system. Aim 2 is to identify appropriate biomarkers that can accurately separate healthy older adults from patients with AD as well as to stratify AD patients based on the stages of dementia (mild and moderate-to-severe). The outcome of this R21 will provide proof of principle that the dual-mode bbNIRS+dwlEEG system enables to identify critical digital biomarkers that will enable accurate detection and stratification of AD at mild or moderate-to-severe stage, permitting us to pursue a larger research project (i.e., R01) for promoting digital biomarkers for early detection of AD by a compact, low-cost, effective, dual-mode brain sensing system.