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

项目总结 越来越多的证据表明，每65秒就有一人患上阿尔茨海默病(AD) 美国，超过570万美国人患有这种疾病。阿尔茨海默氏症和其他痴呆症将使 到2050年，国家将达到2770亿美元。主要的问题是许多认知障碍(CI)的人可能不知道 他们患有痴呆症是因为痴呆症被低估了诊断和报告。缺乏低成本和非 侵入性筛查仪器可高精度地自动识别脑梗塞高危个体。因此， 考虑到痴呆症流行病的全球和社会影响，需要更好的战略来确定 有患痴呆症风险的患者。眼睛健康评估提供了一个独特的视角来了解我们的眼睛健康和 我们的身体。例如，视觉观察视网膜作为一种诊断手段已经被广泛用于检测 高血压、糖尿病、高胆固醇，甚至脑瘤，因为医生可以看到视神经， 这是大脑的一部分。因此，视力测试也可能是检测CI的一种潜在解决方案。因此，我们的目标是 开发由我们的多元生物标记物支持的低成本、紧凑型和非侵入性神经技术 解决AD更好的诊断和替代标记物的迫切需要的方法。我们将进一步 开发我们的新型眼底相机来开发一种紧凑型神经技术设备，该设备(1)能够实现非侵入性 和便携式视网膜成像，带有一组特定窄光谱波段的新环形LED灯，(2)集成了 用于视网膜刺激的光源，并增加了记录视网膜电活动的光学设计， 与目前基于单模的商用设备相比，设备成本降低了10倍 技术。这些创新将使我们的神经技术成为评估视网膜功能和 非专业操作员易于使用的结构，患者感到舒适，可广泛使用 全球范围内的医疗保健设置。该项目填补了AD诊断领域的关键技术空白。 虽然使用单峰和昂贵生物标志物的筛查工具的数量持续增长，但这些工具 不要以集体和自动化的方式考虑常规护理过程中产生的多变量数据。因此，他们的 诊断潜力是有限的。我们用于检测早期AD所致CI的神经技术的发展， 考虑与认知相关的眼脑异常的多因素变量和相关生物标志物 状态，将允许更早的干预，并有助于更好地管理疾病的主要认知 症状。

PROJECT SUMMARY Accumulating evidence indicates that every 65 seconds, someone develops Alzheimer's disease (AD) in the United States, and over 5.7 million Americans have the condition. Alzheimer's and other dementias will cost the nation $277 Billion by 2050. The major problem is that many people with cognitive impairment (CI) may not know they have it because dementia is underdiagnosed and underreported. There is a lack of low-cost and non- invasive screening instruments to automatically identify individuals at risk for CI with high accuracy. Therefore, considering the global and societal implications of the dementia epidemic, better strategies are needed to identify patients at risk for dementia. An eye health evaluation offers a unique perspective on the health of our eyes and our bodies. For example, visual observation of the retina as a diagnostic modality is already widely used to detect high blood pressure, diabetes, high cholesterol, and even brain tumors since a physician can see the optic nerve, which is part of the brain. Thus, an eye test may also be a potential solution to detect CI. Therefore, we aim to develop a low-cost, compact, and non-invasive neurotechnology supported by our multivariate biomarker methodology to address the pressing need for better diagnostics and surrogate markers of AD. We will further develop our novel fundus camera to develop a compact neurotechnology device that (1) enables non-invasive and portable retinal imaging with a new set of ring LED lights of specific narrow spectral bands, (2) integrates a light source for retinal stimulation and adds an optical design for recordings of the electrical activity of the retina, and (3) reduces the device cost >10 times compared to the current commercial devices based on unimodal technologies. These innovations will make our neurotechnology a rapid tool for assessing retinal function and structure easily usable by the non-expert operator, comfortable for the patient, and readily available in a wide range of healthcare settings globally. This project fills a critical technology gap in the field of AD diagnostics. While the number of screening tools using unimodal and expensive biomarkers continues to grow, these tools do not consider multivariate data generated during routine care in a collective and automated way. Thus, their diagnostic potential is limited. The development of our neurotechnology for detecting CI due to AD earlier, considering multifactorial variables and relevant biomarkers of ocular-brain abnormalities related to cognitive status, will allow earlier intervention and facilitate better management of the disease's primary cognitive symptoms.