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.

项目概要 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 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方法 准确识别有 AD 和 ADRD 风险的个人的工具。先进的非侵入性成像显示 视网膜神经变性和视力缺陷早在 AD 和 ADRD 认知能力下降之前就发生了。这 这一事实提出了确定 AD/ADRD 视网膜病理驱动机制的可能性，这可能会有所帮助 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 视网膜，具有强大的非侵入性成像和电生理学技术来监测视网膜功能， 使其成为研究早期中枢神经系统病理学的最佳替代品。大脑与视网膜有许多相似之处。 这表明视网膜是一个比皮质更容易接近的器官，可以为大脑提供可行的生物标志物。 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 被具有分形和非线性特性的物体和过程包围的非线性世界。为了 例如，环境影响的分形复杂性（即分形性）的不足可能导致分形复杂性 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 神经退行性疾病涉及的生理过程的动力学有坚实的证据基础， 这可以从老年和患病大脑节律活动的分形调节受损中看出。我们的多元 生物标志物方法依赖于视网膜脉管系统的分形复杂性作为潜在的生物标志物。 然而，不同视网膜层产生的时变视网膜电图 (ERG) 信号的分形 尚未探索。因此，我们的目标是利用当前的电生理测量 获得母基金，用于研究与 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来获得更全面的评估，以早期发现 MCI 到公元。在这个项目中，我们将通过研究以下因素进一步创新我们的多变量生物标志物方法： ERG 信号的分形。这项研究将使我们的新方法成为更强大的工具 视网膜功能（ERG 信号）和结构（视网膜脉管系统）的组合分形，可以脱落 对早在发病前就损害视网膜和大脑功能的早期致病机制有了新的认识 可检测到的痴呆症。为此，我们将研究 ERG 信号中的分形失真并探索 ERG 分形测量在具有接收者操作特性的组之间的区分能力 曲线、灵敏度和特异性指标。我们将使用约登指数，曲线下的面积将为 计算为ERG设备计算的特征。该项目可以实现更全面的评估 通过识别认知障碍早期阶段的衰老对眼部和大脑功能的影响 使用眼部异常的相关多模式测量来确定眼睛和大脑并发症的迹象。