An AI-assisted screening platform within a multivariate framework for biomarkers of mild cognitive impairment due to Alzheimer's disease

多变量框架内的人工智能辅助筛查平台，用于阿尔茨海默病引起的轻度认知障碍的生物标志物

• 批准号: 10571773
• 负责人: Delia Cabrera DeBuc
• 金额: $ 2.65万
• 依托单位: ISCREEN 2 PREVENT LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10571773
• 关键词: Aging; Alzheimer' s Disease; Alzheimer' s disease pathology; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Area Under Curve; Artificial Intelligence; Biological Markers; Biophysics; Brain; Brain Diseases; Central Nervous System Diseases; Cerebrum; Cessation of life; Cognitive; Custom; Data; Death Rate; Dementia; Development; Devices; Diagnostic tests; Discrimination; Disease; Early Diagnosis; Elderly; Electrophysiology (science); Electroretinography; Eye; Fractals; Goals; Healthcare; Heart Diseases; Impaired cognition; Impairment; Individual; Intervention; Investigation; Lead; Light; Longevity; Measurement; Measures; Methodology; Methods; Monitor; Nerve Degeneration; Neuraxis; Neurodegenerative Disorders; Neurology; Nonlinear Dynamics; Ophthalmology; Organ; Outcome; Pathogenicity; Pathology; Periodicity; Physiological Processes; Population; Process; Property; ROC Curve; Regulation; Reporting; Research; Retina; Risk; Risk Factors; Sensitivity and Specificity; Signal Transduction; Stroke; Structure; Techniques; Time; United States; Visual; Visual Pathways; aged; clinical practice; cost; diagnostic technologies; diagnostic tool; disorder prevention; evidence base; healthy aging; indexing; innovation; instrument; mild cognitive impairment; mortality; multimodality; nervous system disorder; neuroregulation; new technology; non-invasive imaging; noninvasive diagnosis; novel; parent grant; potential biomarker; prospective; protective factors; retina blood vessel structure; screening; targeted treatment; tool; trend

PROJECT SUMMARY In the past decade, the rate of deaths from Alzheimer's disease (AD) and other dementias escalated more than twice the rate of deaths from heart disease. Unfortunately, there is a lack of low-cost and non-invasive diagnostic instruments to accurately identify individuals at risk of AD and ADRD. Advanced non-invasive imaging shows that retinal neurodegeneration and visual deficits occur long before the cognitive decline in AD and ADRD. This fact raises the possibility of identifying mechanisms that drive retinal pathology in AD/ADRD that could help develop effective diagnostics tools and therapies that target early disease. The well-characterized organization of the retina, with powerful non-invasive imaging and electrophysiology techniques to monitor retinal function, make it an optimal surrogate to study early CNS pathology. The brain shares many similarities with the retina. This suggests that the retina, a more accessible organ than the cortex, may provide a viable brain biomarker for testing diagnostics tools and therapies that target early disease and prevention. Notably, we happen to live in a non-linear world surrounded by objects and processes with the property of fractality and non-linearity. For example, the deficit of fractal complexity (i.e., fractality) of environmental effects can lead to fractal complexity distortion in the brain's visual pathways and abnormalities of development or aging. Particularly, non-linear dynamics of physiological processes involved in neurodegenerative disorders have a strong base of evidence, which is seen in the impaired fractal regulation of rhythmic activity in aged and diseased brains. Our multivariate biomarker methodology relies on the fractal complexity of the retinal vasculature as a potential biomarker. However, the fractality of the time-varying electroretinogram (ERG) signal that arises from different retina layers is not yet explored. Therefore, we aim to take advantage of the current electrophysiological measurements acquired in the parent grant to investigate the distortion of fractal complexity in ERG signals correlated to AD pathology as a possible means to obtain a more comprehensive assessment for the early detection of MCI due to AD. In this project, we will further innovate our multivariate biomarker methodology by investigating the fractality of ERG signals. This investigation would make our novel method a more robust tool by incorporating the combined fractality of the retinal function (ERG signals) and structure (retinal vasculature), which can shed new light on early pathogenic mechanisms that compromise retinal and brain function much before the onset of detectable dementia. To this end, we will investigate the distortion of fractality in ERG signals and explore the discrimination power of ERG's fractality measurements between groups with the receiver operating characteristic curve, sensitivity, and specificity metrics. We will use the Youden index and the area under the curve will be calculated for the ERG device calculated features. This project may enable a more comprehensive assessment of aging on ocular and cerebral function at the early stage of cognitive impairment by identifying the most initial signs of complications in the eye and brain using relevant multimodal measures of ocular abnormalities.

项目摘要 在过去的十年中，阿尔茨海默病（AD）和其他痴呆症的死亡率上升超过20%。 是心脏病死亡率的两倍不幸的是，缺乏低成本和非侵入性的诊断 工具，以准确地识别AD和ADRD风险的个体。先进的非侵入性成像显示 视网膜神经变性和视觉缺陷早在AD和ADRD的认知能力下降之前就已发生。这 这一事实提出了确定驱动AD/ADRD视网膜病理学的机制的可能性， 开发针对早期疾病的有效诊断工具和疗法。特色鲜明的组织 的视网膜，与强大的非侵入性成像和电生理技术，以监测视网膜功能， 使其成为研究早期CNS病理学的最佳替代物。大脑与视网膜有许多相似之处。 这表明，视网膜，一个比皮质更容易接近的器官，可能提供了一个可行的大脑生物标志物， 测试针对早期疾病和预防的诊断工具和疗法。值得注意的是，我们碰巧生活在一个 非线性世界是由具有分形性和非线性的对象和过程所包围的世界。为 例如，分形复杂性的不足（即，分形）的环境影响可以导致分形复杂性 大脑视觉通路的扭曲以及发育或衰老的异常。特别是，非线性 涉及神经变性疾病的生理过程的动力学具有强有力的证据基础， 这在老年和患病大脑节律活动的分形调节受损中可见。我们的多元 生物标志物方法依赖于视网膜血管系统的分形复杂性作为潜在的生物标志物。 然而，来自不同视网膜层的时变视网膜电图（ERG）信号的分形性（fractality）是不确定的。 尚未被探索。因此，我们的目标是利用目前的电生理测量 在母基金中获得，以研究与AD相关的ERG信号中分形复杂性的失真 病理学作为一种可能的手段，以获得更全面的评估，早期发现MCI由于 到AD。在这个项目中，我们将进一步创新我们的多变量生物标志物方法，通过调查 ERG信号的分形性。这项调查将使我们的新方法更强大的工具， 视网膜功能（ERG信号）和结构（视网膜血管系统）的组合分形，其可以脱落 关于早在糖尿病发作之前就损害视网膜和大脑功能的早期致病机制的新认识 可检测的痴呆为此，我们将研究ERG信号中的分形失真，并探索 视网膜电图的分形测量在具有受试者操作特征的组间的辨别能力 曲线、灵敏度和特异性度量。我们将使用Youden指数，曲线下面积为 为ERG设备计算的特征计算。该项目可能有助于进行更全面的评估 在认知障碍的早期阶段，通过识别最初始的 使用眼部异常的相关多模式测量，观察眼部和脑部并发症的体征。