Developing a novel EEG-based index for evaluating amyloid and tau burden in Alzheimer's Disease

开发一种基于脑电图的新型指数来评估阿尔茨海默病中淀粉样蛋白和 tau 蛋白的负担

基本信息

批准号：
10602059
负责人：
Che Lucero
金额：
$ 131.5万
依托单位：
SPARK NEURO INC.
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-02-01 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10602059
关键词：
Acceleration Accounting Affect Age Algorithms Alzheimer disease screening Alzheimer&apos s Disease Alzheimer&apos s disease diagnosis Alzheimer&apos s disease diagnostic Alzheimer&apos s disease model Alzheimer&apos s disease pathology Amyloid Amyloid beta-42 Amyloid beta-Protein Behavioral Symptoms Biological Markers Cerebrospinal Fluid Classification Clinical Clinical Research Cognitive Computer software Consumption Country Data Dementia Detection Devices Diagnosis Diagnostic Disease Disease Progression Elderly Electroencephalography Ensure Health Health Care Costs Human Impaired cognition Machine Learning Measures Medical Methods Monitor Nerve Degeneration Neurologic Neurologist Outcome Measure Output Pathologic Pathology Patient Care Patient-Focused Outcomes Patients Performance Persons Phase Physicians Radiologic Health Reporting Research Rest Scanning Severity of illness Small Business Innovation Research Grant Standardization Symptoms System Technology Testing Tissues Training United States Universities Update Work aging population burden of illness cloud based commercialization cost cost effective diagnostic tool drug development human old age (65+)improved indexing insight machine learning algorithm novel performance tests predictive modeling research and development satisfaction success symptom management tau Proteins tau-1 tool usability user-friendly β-amyloid burden

项目摘要

PROJECT SUMMARY Alzheimer’s disease (AD) is a progressive, neurodegenerative condition that impacts 44 million people globally. It is the most common cause of dementia—accounting for 80% of all dementia diagnoses—and predominantly affects older people. To date, AD has no cure. Thus, it is imperative to diagnose patients as early as possible to maximize the efficacy of symptom management strategies. However, existing AD diagnostic and monitoring options remain subpar, leaving urgent need for sensitive, reliable, and convenient methods to measure AD. New research suggests that electroencephalography (EEG) -based biomarkers can assess neural degeneration caused by AD long before tissue loss or behavioral symptoms appear. SPARK Neuro aims to unlock the full potential of EEG through a novel software platform: SPARK Scan. Combining EEG with the capabilities of machine learning, SPARK Scan better assesses cognitive health and neurodegeneration, aiding the diagnosis of AD. In the proposed Direct-to-Phase II SBIR project, the company will enhance the existing SPARK platform by developing a novel Alzheimer’s Disease Pathology Index that tracks patient amyloid and tau burden. Developed with CSF data collected from Johns Hopkins University, the Pathology Index will be a continuous score that corresponds to a patient’s pathological disease burden. After updating the software, the SPARK team will employ Human Factors testing to enhance the usability and utility of the updated platform and clinical report before submitting findings for FDA De Novo approval. This work will progress the SPARK platform by providing a granular measure of AD-related pathology, extending beyond current capabilities.

项目摘要阿尔茨海默氏病（AD）是一种进步的神经退行性疾病，在全球影响4400万人。它是痴呆症的最常见原因，占所有痴呆诊断的80％，主要是影响老年人。迄今为止，广告无法治愈。这是必须尽早诊断患者的最大化症状管理策略的效率。但是，现有的广告诊断和监视选项仍然不及格，迫切需要敏感，可靠和方便的方法来测量AD。新研究表明，脑电图（EEG）基于生物标志物可以评估神经退行性在组织丧失或行为症状出现之前，由AD引起的。 Spark Neuro旨在解锁完整 EEG通过新颖的软件平台的潜力：Spark Scan。将脑电与脑电图结合在一起机器学习，火花扫描更好地评估认知健康和神经退行性，帮助诊断广告。在拟议的直接直接到第II SBIR项目中，该公司将增强现有的Spark平台通过开发一种新型的阿尔茨海默氏病病理学指数，该指数跟踪患者淀粉样蛋白和陶伯恩。通过从约翰·霍普金斯大学收集的CSF数据开发的病理指数将是一个连续的与患者的病理疾病伯恩相对应的评分。更新软件后，Spark团队员工人为因素测试是否会增强更新平台和临床报告的可用性和实用性在提交FDA NOVO批准的调查结果之前。这项工作将通过提供Spark平台广告相关病理的颗粒状测量，超出了当前能力。